phd in mathematics at mit

Academic Programs

• CSE PhD Overview
• Dept-CSE PhD Overview
• CSE Doctoral Theses
• Program Overview and Curriculum
• For New CCSE Students
• Terms of Reference

MIT Doctoral Programs in Computational Science and Engineering

The Center for Computational Science and Engineering (CCSE) offers two doctoral programs in computational science and engineering (CSE) – one leading to a standalone PhD degree in CSE offered entirely by CCSE (CSE PhD) and the other leading to an interdisciplinary PhD degree offered jointly with participating departments in the School of Engineering and the School of Science (Dept-CSE PhD).

While both programs enable students to specialize at the doctoral level in a computation-related field via focused coursework and a thesis, they differ in essential ways. The standalone CSE PhD program is intended for students who intend to pursue research in cross-cutting methodological aspects of computational science. The resulting doctoral degree in Computational Science and Engineering is awarded by CCSE via the the Schwarzman College of Computing. In contrast, the interdisciplinary CSE PhD program is intended for students who are interested in computation in the context of a specific engineering or science discipline. For this reason, this degree is offered jointly with participating departments across the Institute; the interdisciplinary degree is awarded in a specially crafted thesis field that recognizes the student’s specialization in computation within the chosen engineering or science discipline.

For more information about CCSE’s doctoral programs, please explore the links on the left. Information about our application and admission process is available via the ‘ Admissions ‘ tab in our menu. MIT Registrar’s Office provides graduate tuition and fee rates as set by the MIT Corporation and the Graduate Admissions section of MIT’s Office of Graduate Education (OGE) website contains additional information about costs of attendance and funding .

MIT Mathematics Homepage

Latest news.

• Department News Archive
• Mathematics in the MIT News

George Lusztig Receives Gold Medal

Abdun-Nur Professor of Mathematics George Lusztig received a gold medal from the West University of Timișoara in Romania . George was born and raised in Timișoara. This Honorary Distinction for Excellence is given to international personalities for excellence in various fields.

Read more in the MIT News .

Felicitări, George!

PRIMES and RSI Students Awarded at Regeneron

Joseph Vulakh won a Fourth Grand Award in the Mathematics category, as well as the NSA Research Directorate Second Place Award and an Honorable Mention from the AMS. His project, “Twisted Homogeneous Racks Over the Alternating Groups,” was mentored by Prof. Julia Plavnik and Dr. Héctor Peña Pollastri of Indiana University Bloomington. Joseph is coming to MIT as an undergraduate in the fall.

Jason Mao has won the Mu Alpha Theta Second Award for his project “Factorization Properties of Puiseux Monoids,” mentored by SHSU Prof. Scott Chapman and our postdoc Felix Gotti .

At the talent search competition, Michelle won 3rd Place ($150,000 scholarship) for her project “Solving Second-Order Cone Programs Deterministically in Matrix Multiplication Time,” mentored by EECS’ Guanghao Ye.

Congratulations to the winners, and a big thank you to PRIMES Director Slava Gerovitch , PRIMES Chief Research Advisor Pavel Etingof , RSI Faculty Advisor David Jerison , PRIMES/RSI head mentor Tanya Khovanova , and the students’ mentors!

See all of the award winners:

• 2024 Regeneron Science Talent Search Competition
• ISEF grand awards
• ISEF special awards

2024 Baddoo Community Awards

Several math community members received the 2024 Peter Baddoo Community Building Award, for individuals who have made significant contributions to building and strengthening our MIT Math community.

At the Senior Dinner on May 8, Paige Bright was awarded for her Department volunteering efforts, PRIMES Circle outreach, and TA work. Mehrab Jamee was recognized for his work as Undergraduate Math Association president, including organizing social events and academic talks, creating math course resources and Putnam practice sessions, and overseeing the distribution of the popular UMA hoodies. Daniel Santiago-Alvarez was praised for increasing undergrad involvement in DEI, and running panels, mentorship workshops, and coffee chats.

At the May 22 Spring Social, graduate student recipients were Tang-Kai Lee , for dedication to his role as TA for 18.02 and 18.06; and Catherine Wolfram , for her efforts as a TA in 18.600. Instructor Keaton Naff was recognized for his leadership in sections such as 18.100P. All three recipients are actively involved in organizations including the Geometric Analysis Reading seminar and DRP .

This award is named in honor of the late Department instructor Peter Baddoo , who received the Community Building Award in 2022 for organizing tea and coffee hours for the postdoc community.

Congratulations, Catherine, Daniel, Keaton, Mehrab, Paige, and Tang-Kai!

Saba Lepsveridze and Frank Wang Receive Bucsela Prizes

The 2024 Jon A. Bucsela Prize in Mathematics has been awarded to senior math majors Saba Lepsveridze and Frank Wang for distinguished scholastic achievement, professional promise, and enthusiasm for mathematics.

Congratulations, Frank and Saba!

2024 Housman Teaching and Learning Awards

The 2024 Charles and Holly Housman Award for Excellence in Teaching goes to seniors Yiming Chen (TA for courses including 6.122 and 18.800) and Katie Miner (18.02 TA); to graduate student Ryan Chen (TA for 18.06); and to instructors Alex Pieloch (18.901 fall 2023, 18.03 spring 2024), Thomas Rüd (18.01A and 18.02A fall 2023, 18.781 spring 2024) and Jonathan Zung (18.904 fall 2023, 18.900 spring 2024).

Undergraduate awards were presented at the Senior Dinner on May 8, and graduate, postdoc, and instructor awards at the Spring Social on May 22.

Congratulations, Alex, Jonathan, Katie, Ryan, Thomas, and Yiming!

Davis Evans Earns Benney Prize

Graduate student Davis Evans is the recipient of the David J. Benney Prize.

This award recognizes excellence in applied mathematics, with preference given to students in physical applied math, computational science, numerical analysis, computational biology, or theoretical physics. Davis is a PhD candidate working on hydrodynamic quantum analogues in John Bush’s lab.

This award honors David Benney, an applied math professor who died in 2015. Benney chaired the Applied Mathematics Committee from 1983-1985, and served as Department Head for two terms, 1989-1999.

Congratulations, Davis!

Calder Morton-Ferguson and Kai Zhe Zheng Receive Johnson Prize

The 2024 Charles W. and Jennifer C. Johnson Prize, for a research paper accepted for publication in a major journal, has been awarded to graduate student Calder Morton-Ferguson for his paper "Symplectic Fourier-Deligne transforms on G/U and the algebra of braids and ties," in International Mathematics Research Notices, April 2024, and to Kai Zhe Zheng for his paper “Near Optimal Alphabet-Soundness Tradeoff PCPs” in Electronic Colloquium on Computational Complexity, Report No. 27, 2024.

Congratulations, Calder and Kai Zhe!

Phi Beta Kappa Inducts 54 Mathematics Seniors

The Xi Chapter of Phi Beta Kappa has elected 54 mathematics majors, among 127 electees from MIT's Class of 2024, to become members.

Founded in 1776, Phi Beta Kappa is the nation’s oldest academic honor society. Membership is awarded to students in recognition of excellent academic records and commitment to the objectives of a liberal education. The annual Phi Beta Kappa lecture and initiation ceremony is May 29, during MIT’s Commencement week.

Full list of Mathematics Inductees

Congratulations to our newest members of Phi Beta Kappa!

Ben Lou and Kenta Suzuki Receive Goldwater Scholarships

Ben is majoring in physics and math with a minor in philosophy. Under the mentorship of the LIGO Group’s Nergis Mavalvala, dean of the School of Science, and graduate student Hudson Loughlin, he is working on research to advance the field of quantum measurement, with potential applications including quantum gravity. He thanks his advisors Janet Conrad from Physics and Thomas Rüd from Math. He also acknowledges support from Math’s Elijah Bodish and Roman Bezrukavnikov ; Physics’ Alan Guth, Barton Zwiebach, and Richard Price; and David W. Brown of the San Diego Math Circle.

An alum of the PRIMES and SPUR programs, Kenta is a math major who works with Roman on research at the intersection of number and representation theory, using geometric methods to represent p-adic groups. Kenta says he was also inspired to research representation theory by Zhiwei Yun and Wei Zhang .

They were among 438 U.S. college students selected on the basis of academic merit.

Congratulations, Ben and Kenta!

• MIT Calendar
• Conferences

Upcoming Conference

The Many Combinatorial Legacies of Richard P. Stanley

Immense Birthday Glory of the Epic Catalonian Rascal

June 3-7, 2024

Harvard Geological Lecture Hall

Office of Graduate Education -

Apply to become a part of the Massachusetts Institute of Technology community.

Discover & explore

Why choose MIT? Our own graduate students have asked this very same question, and have shared their insights through insightful blog posts . Diverse students explore topics from choosing an advisor to balancing mental health and wellness.

Incoming students

We’re excited to welcome you to MIT! As you prepare to come to Cambridge, lean on these important updates and helpful resources .

Quick links

• Frequently asked questions
• Costs & funding
• Admitted applicants
• International applicants
• Master’s degrees
• Doctoral degrees

This site uses cookies to give you the best possible experience. By browsing our website, you agree to our use of cookies.

If you require further information, please visit the Privacy Policy page.

Smart. Open. Grounded. Inventive. Read our Ideas Made to Matter.

Which program is right for you?

Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

Executive Programs

A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.

This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

Non-degree programs for senior executives and high-potential managers.

A non-degree, customizable program for mid-career professionals.

PhD Program

Program overview.

Now Reading 1 of 4

Rigorous, discipline-based research is the hallmark of the MIT Sloan PhD Program. The program is committed to educating scholars who will lead in their fields of research—those with outstanding intellectual skills who will carry forward productive research on the complex organizational, financial, and technological issues that characterize an increasingly competitive and challenging business world.

Start here.

Learn more about the program, how to apply, and find answers to common questions.

Admissions Events

Check out our event schedule, and learn when you can chat with us in person or online.

Start Your Application

Visit this section to find important admissions deadlines, along with a link to our application.

Click here for answers to many of the most frequently asked questions.

PhD studies at MIT Sloan are intense and individual in nature, demanding a great deal of time, initiative, and discipline from every candidate. But the rewards of such rigor are tremendous:  MIT Sloan PhD graduates go on to teach and conduct research at the world's most prestigious universities.

PhD Program curriculum at MIT Sloan is organized under the following three academic areas: Behavior & Policy Sciences; Economics, Finance & Accounting; and Management Science. Our nine research groups correspond with one of the academic areas, as noted below.

MIT Sloan PhD Research Groups

Behavioral & policy sciences.

Economic Sociology

Institute for Work & Employment Research

Organization Studies

Technological Innovation, Entrepreneurship & Strategic Management

Economics, Finance & Accounting

Accounting  

Management Science

Information Technology

System Dynamics  

Those interested in a PhD in Operations Research should visit the Operations Research Center .  

PhD Program Structure

Additional information including coursework and thesis requirements.

MIT Sloan Predoctoral Opportunities

MIT Sloan is eager to provide a diverse group of talented students with early-career exposure to research techniques as well as support in considering research career paths.

Rising Scholars Conference

The fourth annual Rising Scholars Conference on October 25 and 26 gathers diverse PhD students from across the country to present their research.

Now Reading 2 of 4

The goal of the MIT Sloan PhD Program's admissions process is to select a small number of people who are most likely to successfully complete our rigorous and demanding program and then thrive in academic research careers. The admission selection process is highly competitive; we aim for a class size of nineteen students, admitted from a pool of hundreds of applicants.

What We Seek

• Outstanding intellectual ability
• Excellent academic records
• Previous work in disciplines related to the intended area of concentration
• Strong commitment to a career in research

MIT Sloan PhD Program Admissions Requirements Common Questions

Dates and Deadlines

Admissions for 2024 is closed. The next opportunity to apply will be for 2025 admission. The 2025 application will open in September 2024. 

More information on program requirements and application components

Students in good academic standing in our program receive a funding package that includes tuition, medical insurance, and a fellowship stipend and/or TA/RA salary. We also provide a new laptop computer and a conference travel/research budget.

Funding Information

Throughout the year, we organize events that give you a chance to learn more about the program and determine if a PhD in Management is right for you.

PhD Program Events

June phd program overview.

During this webinar, you will hear from the PhD Program team and have the chance to ask questions about the application and admissions process.

July PhD Program Overview

August phd program overview, september 12 phd program overview.

Complete PhD Admissions Event Calendar

Unlike formulaic approaches to training scholars, the PhD Program at MIT Sloan allows students to choose their own adventure and develop a unique scholarly identity. This can be daunting, but students are given a wide range of support along the way - most notably having access to world class faculty and coursework both at MIT and in the broader academic community around Boston.

Now Reading 3 of 4

Profiles of our current students

MIT Sloan produces top-notch PhDs in management. Immersed in MIT Sloan's distinctive culture, upcoming graduates are poised to innovate in management research and education.

Academic Job Market

Doctoral candidates on the current academic market

Academic Placements

Graduates of the MIT Sloan PhD Program are researching and teaching at top schools around the world.

view recent placements 

MIT Sloan Experience

Now Reading 4 of 4

The PhD Program is integral to the research of MIT Sloan's world-class faculty. With a reputation as risk-takers who are unafraid to embrace the unconventional, they are engaged in exciting disciplinary and interdisciplinary research that often includes PhD students as key team members.

Research centers across MIT Sloan and MIT provide a rich setting for collaboration and exploration. In addition to exposure to the faculty, PhD students also learn from one another in a creative, supportive research community.

Throughout MIT Sloan's history, our professors have devised theories and fields of study that have had a profound impact on management theory and practice.

From Douglas McGregor's Theory X/Theory Y distinction to Nobel-recognized breakthroughs in finance by Franco Modigliani and in option pricing by Robert Merton and Myron Scholes, MIT Sloan's faculty have been unmatched innovators.

This legacy of innovative thinking and dedication to research impacts every faculty member and filters down to the students who work beside them.

Faculty Links

• Accounting Faculty
• Economic Sociology Faculty
• Finance Faculty
• Information Technology Faculty
• Institute for Work and Employment Research (IWER) Faculty
• Marketing Faculty
• Organization Studies Faculty
• System Dynamics Faculty
• Technological Innovation, Entrepreneurship, and Strategic Management (TIES) Faculty

Student Research

“MIT Sloan PhD training is a transformative experience. The heart of the process is the student’s transition from being a consumer of knowledge to being a producer of knowledge. This involves learning to ask precise, tractable questions and addressing them with creativity and rigor. Hard work is required, but the reward is the incomparable exhilaration one feels from having solved a puzzle that had bedeviled the sharpest minds in the world!” -Ezra Zuckerman Sivan Alvin J. Siteman (1948) Professor of Entrepreneurship

Sample Dissertation Abstracts - These sample Dissertation Abstracts provide examples of the work that our students have chosen to study while in the MIT Sloan PhD Program.

We believe that our doctoral program is the heart of MIT Sloan's research community and that it develops some of the best management researchers in the world. At our annual Doctoral Research Forum, we celebrate the great research that our doctoral students do, and the research community that supports that development process.

The videos of their presentations below showcase the work of our students and will give you insight into the topics they choose to research in the program.

Attention To Retention: The Informativeness of Insiders’ Decision to Retain Shares

2024 PhD Doctoral Research Forum Winner - Gabriel Voelcker

Watch more MIT Sloan PhD Program  Doctoral Forum Videos

• [email protected]

Keep Exploring

Ask a question or register your interest

Faculty Directory

Meet our faculty.

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Social justice
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

Grad student John Urschel tackles his lifelong balance of math and football in new memoir

Press contact :.

Previous image Next image

It’s been nearly two years since John Urschel retired from the NFL at the age of 26, trading a career as a professional football player at the height of his game for a chance at a PhD in mathematics at MIT. From the looks of it, he couldn’t be happier.

The former offensive lineman for the Baltimore Ravens is now a full-time graduate student who spends his days in Building 2, poring over academic papers and puzzling over problems in graph theory, machine learning, and numerical analysis.

In his new memoir, “Mind and Matter: A Life in Math and Football,” co-written with his wife, journalist and historian Louisa Thomas, Urschel writes about how he has balanced the messy, physically punishing world of football, with the elegant, cerebral field of mathematics.

Urschel presents his life chronologically, through chapters that alternate in focus between math and football, as it often did in real life. For instance, he writes about a moment, following an ecstatic win as part of Penn State’s offensive line, when a coach pulled him aside with a message: With a little more work, he had a shot at the NFL.

With that in mind, he writes, “I went home elated. … I left the football building with a new sense of purpose, a mission.” That same night, he opened his laptop and got to work on a paper that he planned to submit with his advisor to a top linear algebra journal. “Suddenly, surprisingly, I had a strange feeling: I felt torn,” he recalls.

For those who see Urschel as a walking contradiction, or praise him as an exceptional outlier, he poses, in his book, a challenge:

“So often, people want to divide the world into two: matter and energy. Wave and particle. Athlete and mathematician. Why can’t something (or someone) be both?”

A refuge in math

Before he could speak in full sentences, Urschel’s mother could tell that the toddler had a mind for patterns. To occupy the increasingly active youngster, she gave him workbooks filled with puzzles, which he eagerly devoured at the kitchen table. As he got older, she encouraged him further, and often competitively, with games of reasoning and calculation, such as Monopoly and Battleship. And in the grocery store, she let him keep the change if he could calculate the correct amount before the cashier rang it up.

His mother made math a game, and by doing so, lit a lifelong spark. He credits her with recognizing and nurturing his natural interests — something that he hopes to do for his own toddler, Joanna, to whom he dedicates the book.

When he was 5 years old, he saw a picture of his father in full pads, as a linebacker for the University of Alberta — his first exposure to the sport of football. From that moment, Urschel wanted to be like his dad, and he wanted to play football.

And play he did, though he writes that he wasn’t driven by any innate athletic talent.

“The only thing that set me apart from other kids when I played sports was my intensity as a competitor. I couldn’t stand losing — so much so that I would do everything in my power to try to win,” Urschel writes.

This fierce drive earned him a full ride to Penn State University, where he forged a lasting connection with the college and its football team. His seemingly disparate talents in math and football started gaining some media attention, as a bright spot for Penn State in an otherwise dark period. (The team was facing national scrutiny as a consequence of the trial of former coach Jerry Sandusky.) But the more news outlets referred to him as a “student-athlete,” the more the moniker grated against him.

“[The term ‘student-athlete’] is widely considered a joke of sorts in America,” Urschel says. “But it’s something you can actually do. It takes up a great deal of your time, and it’s not easy. But it is possible to be good at sports while tearing it up in academics.”

Urschel proved this in back-to-back years at Penn State, culminating in 2013 with a paper he co-wrote with his advisor, Ludmil Zikatanov, on the spectral bisection of graphs and connectedness, which would later be named the Urschel-Zikatanov theorem. The following year, he was drafted, in the fifth round, by the Baltimore Ravens.

He played his entire professional football career as a guard with the Ravens, in 40 games over two years, 13 of which he started. In 2015, in a full-pads practice at training camp with the team, Urschel was knocked flat with a concussion. Just weeks earlier, he had learned that he had been accepted to MIT, where he hoped to pursue a PhD in applied mathematics, during the NFL offseason.

In the weeks following the concussion, he writes: “I’d reach for a theorem that I knew I knew, and it wouldn’t be there. I would try to visualize patterns, or to stretch or twist shapes — a skill that had always come particularly easy to me — and I would be unable to see the structures or make things move.”

He eventually did regain his facility for math, along with, surprisingly, his need to compete on the field. Despite the possibility of suffering another concussion, he continued to play with the Ravens through 2015. During the off-season, in January 2016, Urschel set foot on the MIT campus to begin work on his PhD.

A quantitative mindset

“It was like stepping into my personal vision of paradise ,” Urschel writes of his first time walking through MIT’s math department in Building 2, noting the chalkboards that lined the hallways, where “casual conversations quickly became discussions of open conjectures . ” Urschel was no less impressed by MIT’s football team, whose practices he joined each Monday during that first semester.

“These students have so much to do at MIT — it’s a very stressful place,” Urschel says. “And this is Division III football. It’s not high level, and they don’t have packed stands of fans — they’re truly just playing for the love of the game.”

He says he was reluctant to return to pro football that summer, and realized throughout that season that he couldn’t wait for Sundays and the prospect of cracking open a math book and tackling problems with collaborators back at MIT and Penn State.

An article in the New York Times in July 2017 tipped the scales that had, up until then, kept math and football as equal passions for Urschel. The article outlined a brain study of 111 deceased NFL players, showing 110 of those players had signs of CTE, or chronic traumatic encephalopathy, associated with repeated blows to the head. Urschel writes that the study didn’t change his love for football, but it did make him reevaluate his choices.

Two days after reading that article, Urschel announced his retirement from the NFL and packed his bags for a permanent move to MIT.

Since then, he has focused his considerable energy on his  research, as well as teaching. Last spring, he was a teaching assistant for the first time, in 18.03 (Differential Equations).

“I love teaching,” says Urschel, who hopes to be a university math professor and encourages students in class to think creatively, rather than simply memorize the formulas that they’re taught.

“I’m fighting against the idea of blindly applying formulas you just learned, and instead teaching students to use their brains,” Urschel says.

He’s also making time to visit local high schools to talk math, and STEM education in general.

“I’m a visible mathematician,” says Urschel — an understatement to be sure. “I have a responsibility to try to help popularize math, and remove some of its stigma.”

His enthusiasm for the subject is highly effective, judging from the overwhelmingly positive reviews from his 18.03 students. Above all, though, he hopes to convey the importance of a “quantitative mindset.”

“I don’t care so much if a random person on the street knows the quadratic formula,” Urschel says. “But I do care if they’re able to think through different problems, whether involving loans of two different rates, or how much you need to put in your 401k. Being capable of thinking quantitatively — it’s the single most important thing.”

Share this news article on:

Press mentions.

Graduate student John Urschel speaks with Forbes contributor Talia Milgrom-Elcott about how his mother helped inspire his love of mathematics and the importance of representation. “It’s very hard to dream of being in a career if you can’t relate to anyone who’s actually in that field,” says Urschel. “One of my main goals in life as a mathematician is to increase representation of African American mathematicians.”

Education Week

Graduate student John Urschel speaks with Education Week reporter Kevin Bushweller about his work aimed at encouraging more students of color to pursue studies in the STEM fields, particularly math. “What really matters is resources, what really matters is how much a child is nurtured and fed things,” says Urschel. “This is just my opinion, but I would say that, by and large, if I had to choose between giving a child a little bit more innate math talent or a little bit more resources, I think, really, resources is what is a very good and bigger predictor [of future success].”

Graduate student John Urschel speaks with Jamison Hensley of ESPN about his efforts aimed at empowering and encouraging more Black students to pursue careers in STEM fields. “Now more than ever, it’s really important that we highlight some of the diverse areas of mathematics that don’t typically get seen every day,” says Urschel.

Associated Press

A new book by graduate student John Urschel chronicles his decision to retire from the NFL and pursue his passion for mathematics at MIT, reports the Associated Press. Urschel explains that through his book, he “wanted to share my love of math and also perhaps train certain peoples’ thinking about math and show them some of the beauty, elegance and importance of mathematics.”

Good Morning America

Graduate student John Urschel appears on Good Morning America to discuss his new book chronicling his career and passion for football and math. “Math is something that I have loved ever since I was very little,” explains Urschel. “I love puzzles, I love problem solving. Math, truly, is just a set of tools to try to solve problems in this world. 

New York Times

Writing for The New York Times , graduate student John Urschel recounts how his high school football coaches motivated him, noting that similar tactics might encourage more children to study math. “There are many ways to be an effective teacher, just as there are many ways to be an effective coach,” writes Urschel. “But all good teachers, like good coaches, communicate that they care about your goals.”

Graduate student John Urschel speaks with Karen Given of WBUR’s Only a Game about how his mother helped encourage his passion for mathematics. "Most kids get their allowance by, you know, mowing the lawn — things like this," Urschel says. "My mom, because she recognized that I was strong in math, wanted to encourage me with respect to math."

TIME reporter Sean Gregory visits MIT to speak with graduate student John Urschel about his new book, and his passion for both mathematics and football. “The United States, more than any other culture, has the strange marriage of athletics and academics,” Urschel says. “I thought it was important to show that this is something that really can co-exist.”

Graduate student John Urschel discusses his new book and passion for both math and football on Fox and Friends . “Football coaches, they tell their best players to dream big,” says Urschel. “I would love to see math teachers telling their students you can be an elite mathematician, you can be a top physicist, you can even dream to be the next Einstein.”

Graduate student John Urschel visits the Today Show to discuss his new book and what inspired him to pursue a PhD in mathematics. Urschel explains that his mother tried to ensure that “whatever I wanted to be the only thing that would limit me was a lack of talent, bad luck, lack of hard work, but it wasn’t going to be the household I was born into or a lack of resources.”

Boston Globe

Boston Globe reporter Ben Volin speaks with graduate student John Urschel about his new book “Mind and Matter: A Life in Math and Football.” “I love solving sort of interesting and tough problems that have to do with our world in some way,” says Urschel of his dreams for after he graduates from MIT. “And I also love teaching.”

Previous item Next item

Related Links

• John Urschel
• Department of Mathematics
• Article: “From the NFL to MIT: The Double Life of John Urschel”

Related Topics

• Mathematics
• Sports and fitness
• STEM education
• Books and authors
• Graduate, postdoctoral

Related Articles

Big issues on the table at the MIT Sloan Sports Analytics Conference

From football to physics

MIT Football tackles diversity and inclusion conversations

A record crowd in Washington celebrates MIT’s culture of innovation and discovery

More mit news.

Ultrasound offers a new way to perform deep brain stimulation

Read full story →

Helping robots grasp the unpredictable

“Rosetta Stone” of cell signaling could expedite precision cancer medicine

A technique for more effective multipurpose robots

MIT Corporation elects 10 term members, two life members

Diane Hoskins ’79: How going off-track can lead new SA+P graduates to become integrators of ideas

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

• Core Members
• Affiliate Members

Interdisciplinary Doctoral Program in Statistics

• Minor in Statistics and Data Science
• MicroMasters program in Statistics and Data Science
• Data Science and Machine Learning: Making Data-Driven Decisions
• Norbert Wiener Fellowship
• Stochastics and Statistics Seminar
• IDSS Distinguished Seminars
• IDSS Special Seminar
• SDSC Special Events
• Online events
• IDS.190 Topics in Bayesian Modeling and Computation
• Past Events
• LIDS & Stats Tea

The Interdisciplinary PhD in Statistics (IDPS) is designed for students currently enrolled in a participating MIT doctoral program who wish to develop their understanding of 21st century statistics, using concepts of computation and data analysis as well as elements of classical statistics and probability within their chosen field of study.

Participating programs: Aeronautics & Astronautics Brain and Cognitive Sciences Economics Mathematics Mechanical Engineering Physics Political Science Social and Engineering Systems

How to join IDPS:

Doctoral students in participating programs may submit a selection form between the end of their second semester and penultimate semester in their doctoral program. Selection forms are due by the current semester add date, and students will be notified of a decision by the drop date.

Required documents include a CV, unofficial transcript, anticipated course plan and thesis proposal or statement of interest in statistics.  For access to the selection form or for further information, please contact the IDSS Academic Office at [email protected]

Graduate Departments:

MIT Statistics + Data Science Center Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge, MA 02139-4307 617-253-1764

• Accessibility
• Interdisciplinary PhD in Aero/Astro and Statistics
• Interdisciplinary PhD in Brain and Cognitive Sciences and Statistics
• Interdisciplinary PhD in Economics and Statistics
• Interdisciplinary PhD in Mathematics and Statistics
• Interdisciplinary PhD in Mechanical Engineering and Statistics
• Interdisciplinary PhD in Physics and Statistics
• Interdisciplinary PhD in Political Science and Statistics
• Interdisciplinary PhD in Social & Engineering Systems and Statistics
• LIDS & Stats Tea
• Spring 2023
• Spring 2022
• Spring 2021
• Fall – Spring 2020
• Fall 2019 – IDS.190 – Topics in Bayesian Modeling and Computation
• Fall 2019 – Spring 2019
• Fall 2018 and earlier

• Skip to Content
• Bulletin Home

• Degree Charts >
• Computational Science and Engineering (PhD)
• Around Campus
• Academic Program
• Administration
• Arts at MIT
• Campus Media
• Fraternities, Sororities, and Independent Living Groups
• Medical Services
• Priscilla King Gray Public Service Center
• Religious Organizations
• Student Government
• Work/​Life and Family Resources
• Advising and Support
• Digital Learning
• Disability and Access Services
• Information Systems and Technology
• Student Financial Services
• Writing and Communication Center
• Major Course of Study
• General Institute Requirements
• Independent Activites Period
• Undergraduate Research Opportunities Program
• First-​Year Advising Seminars
• Interphase EDGE/​x
• Edgerton Center
• Grading Options
• Study at Other Universities
• Internships Abroad
• Career Advising and Professional Development
• Teacher Licensure and Education
• ROTC Programs
• Financial Aid
• Medical Requirements
• Graduate Study at MIT
• General Degree Requirements
• Other Institutions
• Registration
• Term Regulations and Examination Policies
• Academic Performance and Grades
• Policies and Procedures
• Privacy of Student Records
• Abdul Latif Jameel Poverty Action Lab
• Art, Culture, and Technology Program
• Broad Institute of MIT and Harvard
• Center for Archaeological Materials
• Center for Bits and Atoms
• Center for Clinical and Translational Research
• Center for Collective Intelligence
• Center for Computational Science and Engineering
• Center for Constructive Communication
• Center for Energy and Environmental Policy Research
• Center for Environmental Health Sciences
• Center for Global Change Science
• Center for International Studies
• Center for Real Estate
• Center for Transportation &​ Logistics
• Computer Science and Artificial Intelligence Laboratory
• Concrete Sustainability Hub
• D-​Lab
• Deshpande Center for Technological Innovation
• Division of Comparative Medicine
• Haystack Observatory
• Initiative on the Digital Economy
• Institute for Medical Engineering and Science
• Institute for Soldier Nanotechnologies
• Institute for Work and Employment Research
• Internet Policy Research Initiative
• Joint Program on the Science and Policy of Global Change
• Knight Science Journalism Program
• Koch Institute for Integrative Cancer Research
• Laboratory for Financial Engineering
• Laboratory for Information and Decision Systems
• Laboratory for Manufacturing and Productivity
• Laboratory for Nuclear Science
• Legatum Center for Development and Entrepreneurship
• Lincoln Laboratory
• Martin Trust Center for MIT Entrepreneurship
• Materials Research Laboratory
• McGovern Institute for Brain Research
• Microsystems Technology Laboratories
• MIT Center for Art, Science &​ Technology
• MIT Energy Initiative
• MIT Environmental Solutions Initiative
• MIT Kavli Institute for Astrophysics and Space Research
• MIT Media Lab
• MIT Office of Innovation
• MIT Open Learning
• MIT Portugal Program
• MIT Professional Education
• MIT Sea Grant College Program
• Nuclear Reactor Laboratory
• Operations Research Center
• Picower Institute for Learning and Memory
• Plasma Science and Fusion Center
• Research Laboratory of Electronics
• Simons Center for the Social Brain
• Singapore-​MIT Alliance for Research and Technology Centre
• Sociotechnical Systems Research Center
• Whitehead Institute for Biomedical Research
• Women's and Gender Studies Program
• Architecture (Course 4)
• Art and Design (Course 4-​B)
• Art, Culture, and Technology (SM)
• Media Arts and Sciences
• Planning (Course 11)
• Urban Science and Planning with Computer Science (Course 11-​6)
• Aerospace Engineering (Course 16)
• Engineering (Course 16-​ENG)
• Biological Engineering (Course 20)
• Chemical Engineering (Course 10)
• Chemical-​Biological Engineering (Course 10-​B)
• Chemical Engineering (Course 10-​C)
• Engineering (Course 10-​ENG)
• Engineering (Course 1-​ENG)
• Electrical Engineering and Computer Science (Course 6-​2)
• Electrical Science and Engineering (Course 6-​1)
• Computation and Cognition (Course 6-​9)
• Computer Science and Engineering (Course 6-​3)
• Computer Science and Molecular Biology (Course 6-​7)
• Electrical Engineering and Computer Science (MEng)
• Computer Science and Molecular Biology (MEng)
• Health Sciences and Technology
• Archaeology and Materials (Course 3-​C)
• Materials Science and Engineering (Course 3)
• Materials Science and Engineering (Course 3-​A)
• Materials Science and Engineering (PhD)
• Mechanical Engineering (Course 2)
• Mechanical and Ocean Engineering (Course 2-​OE)
• Engineering (Course 2-​A)
• Nuclear Science and Engineering (Course 22)
• Engineering (Course 22-​ENG)
• Anthropology (Course 21A)
• Comparative Media Studies (CMS)
• Writing (Course 21W)
• Economics (Course 14-​1)
• Mathematical Economics (Course 14-​2)
• Data, Economics, and Design of Policy (MASc)
• Economics (PhD)
• Global Studies and Languages (Course 21G)
• History (Course 21H)
• Linguistics and Philosophy (Course 24-​2)
• Philosophy (Course 24-​1)
• Linguistics (SM)
• Literature (Course 21L)
• Music (Course 21M-​1)
• Theater Arts (Course 21M-​2)
• Political Science (Course 17)
• Science, Technology, and Society/​Second Major (STS)
• Business Analytics (Course 15-​2)
• Finance (Course 15-​3)
• Management (Course 15-​1)
• Biology (Course 7)
• Chemistry and Biology (Course 5-​7)
• Brain and Cognitive Sciences (Course 9)
• Chemistry (Course 5)
• Earth, Atmospheric and Planetary Sciences (Course 12)
• Mathematics (Course 18)
• Mathematics with Computer Science (Course 18-​C)
• Physics (Course 8)
• Department of Electrical Engineering and Computer Science
• Institute for Data, Systems, and Society
• Chemistry and Biology
• Climate System Science and Engineering
• Computation and Cognition
• Computer Science and Molecular Biology
• Computer Science, Economics, and Data Science
• Humanities and Engineering
• Humanities and Science
• Urban Science and Planning with Computer Science
• African and African Diaspora Studies
• American Studies
• Ancient and Medieval Studies
• Applied International Studies
• Asian and Asian Diaspora Studies
• Biomedical Engineering
• Energy Studies
• Entrepreneurship and Innovation
• Environment and Sustainability
• Latin American and Latino/​a Studies
• Middle Eastern Studies
• Polymers and Soft Matter
• Public Policy
• Russian and Eurasian Studies
• Statistics and Data Science
• Women's and Gender Studies
• Advanced Urbanism
• Computational and Systems Biology

Computational Science and Engineering

• Design and Management (IDM &​ SDM)
• Joint Program with Woods Hole Oceanographic Institution
• Leaders for Global Operations
• Microbiology
• Music Technology and Computation
• Operations Research
• Real Estate Development
• Social and Engineering Systems
• Supply Chain Management
• Technology and Policy
• Transportation
• School of Architecture and Planning
• School of Engineering
• Aeronautics and Astronautics Fields (PhD)
• Artificial Intelligence and Decision Making (Course 6-​4)
• Biological Engineering (PhD)
• Nuclear Science and Engineering (PhD)
• School of Humanities, Arts, and Social Sciences
• Humanities (Course 21)
• Humanities and Engineering (Course 21E)
• Humanities and Science (Course 21S)
• Sloan School of Management
• School of Science
• Brain and Cognitive Sciences (PhD)
• Earth, Atmospheric and Planetary Sciences Fields (PhD)
• Interdisciplinary Programs (SB)
• Climate System Science and Engineering (Course 1-​12)
• Computer Science, Economics, and Data Science (Course 6-​14)
• Interdisciplinary Programs (Graduate)
• Computation and Cognition (MEng)
• Computational Science and Engineering (SM)
• Computer Science, Economics, and Data Science (MEng)
• Leaders for Global Operations (MBA/​SM and SM)
• Music Technology and Computation (SM and MASc)
• Real Estate Development (SM)
• Statistics (PhD)
• Supply Chain Management (MEng and MASc)
• Technology and Policy (SM)
• Transportation (SM)
• Aeronautics and Astronautics (Course 16)
• Aerospace Studies (AS)
• Civil and Environmental Engineering (Course 1)
• Comparative Media Studies /​ Writing (CMS)
• Comparative Media Studies /​ Writing (Course 21W)
• Computational and Systems Biology (CSB)
• Computational Science and Engineering (CSE)
• Concourse (CC)
• Data, Systems, and Society (IDS)
• Earth, Atmospheric, and Planetary Sciences (Course 12)
• Economics (Course 14)
• Edgerton Center (EC)
• Electrical Engineering and Computer Science (Course 6)
• Engineering Management (EM)
• Experimental Study Group (ES)
• Global Languages (Course 21G)
• Health Sciences and Technology (HST)
• Linguistics and Philosophy (Course 24)
• Management (Course 15)
• Media Arts and Sciences (MAS)
• Military Science (MS)
• Music and Theater Arts (Course 21M)
• Naval Science (NS)
• Science, Technology, and Society (STS)
• Special Programs
• Supply Chain Management (SCM)
• Urban Studies and Planning (Course 11)
• Women's and Gender Studies (WGS)

Doctoral Programs in Computational Science and Engineering

Doctor of philosophy in computational science and engineering, program requirements, programs offered by ccse in conjunction with select departments in the schools of engineering and science.

The interdisciplinary doctoral program in Computational Science and Engineering ( PhD in CSE + Engineering or Science ) offers students the opportunity to specialize at the doctoral level in a computation-related field of their choice via computationally-oriented coursework and a doctoral thesis with a disciplinary focus related to one of eight participating host departments, namely, Aeronautics and Astronautics; Chemical Engineering; Civil and Environmental Engineering; Earth, Atmospheric and Planetary Sciences; Materials Science and Engineering; Mathematics; Mechanical Engineering; or Nuclear Science and Engineering.

Doctoral thesis fields associated with each department are as follows:

• Aerospace Engineering and Computational Science
• Computational Science and Engineering (available only to students who matriculate in 2023–2024 or earlier)
• Chemical Engineering and Computation
• Civil Engineering and Computation
• Environmental Engineering and Computation
• Computational Materials Science and Engineering
• Mechanical Engineering and Computation
• Computational Nuclear Science and Engineering
• Nuclear Engineering and Computation
• Computational Earth, Science and Planetary Sciences
• Mathematics and Computational Science

As with the standalone CSE PhD program, the emphasis of thesis research activities is the development of new computational methods and/or the innovative application of state-of-the-art computational techniques to important problems in engineering and science. In contrast to the standalone PhD program, however, this research is expected to have a strong disciplinary component of interest to the host department.

The interdisciplinary CSE PhD program is administered jointly by CCSE and the host departments. Students must submit an application to the CSE PhD program, indicating the department in which they wish to be hosted. To gain admission, CSE program applicants must receive approval from both the host department graduate admission committee and the CSE graduate admission committee. See the website for more information about the application process, requirements, and relevant deadlines .

Once admitted, doctoral degree candidates are expected to complete the host department's degree requirements (including qualifying exam) with some deviations relating to coursework, thesis committee composition, and thesis submission that are specific to the CSE program and are discussed in more detail on the CSE website . The most notable coursework requirement associated with this CSE degree is a course of study comprising five graduate subjects in CSE (below).

Computational Concentration Subjects

Note: Students may not use more than 12 units of credit from a "meets with undergraduate" subject to fulfill the CSE curriculum requirements

Print this page.

The PDF includes all information on this page and its related tabs. Subject (course) information includes any changes approved for the current academic year.

Doctoral Degrees

A doctoral degree requires the satisfactory completion of an approved program of advanced study and original research of high quality..

Please note that the Doctor of Philosophy (PhD) and Doctor of Science (ScD) degrees are awarded interchangeably by all departments in the School of Engineering and the School of Science, except in the fields of biology, cognitive science, neuroscience, medical engineering, and medical physics. This means that, excepting the departments outlined above, the coursework and expectations to earn a Doctor of Philosophy and for a Doctor of Science degree from these schools are generally the same. Doctoral students may choose which degree they wish to complete.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Some departments require a doctoral candidate to take a “minor” program outside of the student’s principal field of study; if you wish to apply to one of these departments, please consider additional fields you may like to pursue.

Below is a list of programs and departments that offer doctoral-level degrees.

This site uses cookies to give you the best possible experience. By browsing our website, you agree to our use of cookies.

If you require further information, please visit the Privacy Policy page.

Latest human H5N1 bird flu case in US is 1st to cause respiratory symptoms

This infection, tied to an ongoing outbreak in cows, is the first in the U.S. to cause respiratory symptoms, but not the first H5N1 case in the world to do so.

A third human case of bird flu has been linked to the ongoing outbreak in cows on U.S. dairy farms — and this one came with respiratory symptoms, such as cough, the Centers for Disease Control and Prevention (CDC) reported May 30.

Officials first became aware of bird flu spreading among U.S. dairy cows in March, and since then, the viral disease has been detected among cattle on farms in nine states. The type of bird flu spreading is known as H5N1, which has sporadically infected individual humans in the past but has never spread widely from person to person. However, these rare human infections can sometimes be fatal, and there's concern about the virus picking up the necessary mutations to spread easily through the populace.

Prior to the outbreak in cows, only one person in the U.S. had ever been infected with H5N1, as far as we know. Now, since the outbreak began, three people have likely been infected via exposure to sick cows. The first person infected by a cow was in Texas , and the second was in Michigan ; both are dairy-farm workers and developed only eye infections from the virus before recovering.

The third, newly reported case linked to cow exposure was also in Michigan but on a different farm. The person was given treatment and is now isolating at home as their symptoms resolve. This infection is notable because it is the first human H5N1 case in the U.S. associated with respiratory symptoms. 

Related: H5N1: What to know about the bird flu cases in cows, goats and people  

"This is the first human case of H5 in the United States to report more typical symptoms of acute respiratory illness associated with influenza virus infection, including A(H5N1) viruses," the CDC reported. "The patient reported upper respiratory tract symptoms, including cough without fever, and eye discomfort with watery discharge." 

In humans, bird flu viruses, including H5N1, can cause both mild symptoms — including pink eye, cough, sore throat, runny nose and body aches — as well as severe ones, such as pneumonia, difficulty breathing and seizures. If severe, the infections can be fatal , but antiviral drugs available for seasonal flu can help treat the disease.

Sign up for the Live Science daily newsletter now

Get the world’s most fascinating discoveries delivered straight to your inbox.

Finding another case of human H5N1 infection is "not surprising," given the extent of the spread of this virus in dairy cows, the CDC says. H5N1 was also already known to cause respiratory symptoms — however, seeing this is still concerning because, generally, symptoms like coughing and sneezing can make it easier for a virus to spread between people, The New York Times reported .

Each time the virus jumps to people, it gains an opportunity to pick up mutations that make it capable of spreading sustainably between humans — a chain of events that, in the worst scenario, could precipitate a pandemic . 

— 21-year-old student dies of H5N1 bird flu in Vietnam

— 1st polar bear death from bird flu spells trouble for species

— China reported 1st human death from H3N8 bird flu, WHO says

With that possibility in mind, the CDC continues to closely monitor for unusual flu activity across the country. So far, "there has been no sign of unusual influenza activity in people, including no increase in emergency room visits for influenza and no increase in laboratory detection of human influenza cases," the agency reported. 

Scientists are also looking to see if the virus has picked up any mutations that would raise the risk of spread, although thus far, there's no evidence of person-to-person transmission. 

Based on the available information, the risk of spread to the general public remains low, the CDC noted. As always, health authorities still recommend against drinking raw milk . Dairy-farm workers currently face the highest risk of exposure, the agency emphasized. 

Some experts have argued that federal officials should be screening many more workers for H5N1 and offering optional experimental bird flu vaccines, The New York Times reported. At this point, only about 40 farm workers have consented to being tested for H5N1, while a few hundred are being monitored for possible symptoms, according to news reports.

This article is for informational purposes only and is not meant to offer medical advice.

Ever wonder why some people build muscle more easily than others or why freckles come out in the sun ? Send us your questions about how the human body works to [email protected] with the subject line "Health Desk Q," and you may see your question answered on the website!

Nicoletta Lanese is the health channel editor at Live Science and was previously a news editor and staff writer at the site. She holds a graduate certificate in science communication from UC Santa Cruz and degrees in neuroscience and dance from the University of Florida. Her work has appeared in The Scientist, Science News, the Mercury News, Mongabay and Stanford Medicine Magazine, among other outlets. Based in NYC, she also remains heavily involved in dance and performs in local choreographers' work.

H5N1 bird flu has spread to human from cow in 2nd probable case, CDC reports

H5N1: What to know about the bird flu cases in cows, goats and people

China lands Chang'e 6 sample-return probe on far side of the moon

Most Popular

• 2 Space photo of the week: James Webb telescope spots galaxy churning out stars in overtime
• 3 Things are finally looking up for the Voyager 1 interstellar spacecraft
• 4 How people without 'inner voices' could help reveal the mysteries of consciousness
• 5 Auroras could paint Earth's skies again in early June. Here are the key nights to watch for.
• 2 3,500-year-old rock art of wild sheep and double-humped camels revealed in Kazakhstan
• 3 GPT-4 didn't ace the bar exam after all, MIT research suggests — it didn't even break the 70th percentile
• 4 32 unusual medical cases
• 5 China's secret space plane has released another unknown object over Earth

When the PhD path leads to career struggles

A doctoral degree is a major commitment. Think carefully.

I appreciated reading Kara Miller’s The Big Idea column “PhD: Pretty heavily disappointed” (Business, May 22), about people with doctoral degrees struggling to build careers in academia. It made me think back to a conversation I had when I was about to graduate from high school.

I happened to run into a former track coach of mine, and as we were reminiscing he asked me what I planned as a major in college. “History,” I responded. He said, “Why don’t you take some computer classes also? It never hurts to be able to do something useful.”

I did not reflect on his motivation at the time, but my track coach was a young guy, and he was probably giving me advice straight from his own life, as a parent trying to raise his own young children. I did take computer classes in college and ultimately received a PhD in chemical engineering. I always remember that conversation as being a kind of turning point.

Earning a doctoral degree is a life commitment of great proportion. It can take, as Miller notes, between four and seven years. If we think of working life as roughly between the ages of 22 and 65, then a PhD requires more than 10 percent of a person’s working life. People need to think carefully about that investment.

Advertisement

Two powerful arguments in favor of the path of science, technology, engineering, and math are that there tend to be more STEM jobs for PhDs, and many universities’ STEM departments are generous in covering their PhD students’ tuition and cost of studies, including a stipend toward food, rent, and other expenses.

Stuart Gallant

Not much has changed in 30 years

As I prepared to graduate in 1995 with a doctor of education degree from the Harvard Graduate School of Education, my mother memorably said to me, “Of my four children, you are the one with the most education and the smallest salary.” Apparently not much has changed in 30 years.

I must congratulate these students, however, on following their passion rather than following the money. I can’t help but think that their lives, though stressful, may contain greater happiness.

Peggy Clark

Lawyers & electricians & philosophers, oh my!

Kara Miller’s column on the career challenges for people with doctoral degrees generated more than 260 comments on Boston.Globe.com. The following is an edited sample of readers’ reactions:

Lots of law school grads are underemployed as well. (PL)

So true, PL. The market in Massachusetts is flooded with talented lawyers seeking work. (Roforma)

Supply and demand, the market at work. (guk)

Investing in education and research in all fields is the hallmark of a society with staying power. Disinvesting from these endeavors signals decline and decay. (Massachusetts citizen)

Electricians, plumbers, mechanics, and other skilled technical professions have no problems getting $100k jobs with great benefits. (ramsen)

Not enough turnover from tenured professors, leaving little space for new faculty. Although the tenured, well-established professors are needed, it’s the junior faculty who are hungry and with new ideas that help build new programs. The whole graduate program model is a bad model. I worked two jobs, had my tuition and some type of minimal student health insurance and could barely cover the rent with my stipend, and the second job paid for everything else. Though I was working on many faculty projects, it was the faculty who said this would be good for me. Never did they say it was also good for them. (TravelerofNJ2)

I just retired from a tenured faculty position in science. I’m in my early 70s. I have colleagues who are still doing what they do well into their 70s, a couple approaching 80. There is no active incentive from the university to move the older faculty on, to make way for a new generation. (Lola-lola)

The next step is for adjuncts to go on strike across the nation and hold colleges and universities accountable. The current system is completely absurd. (Wordsmith2358)

Universities should be required to release disclosure data about the fate of their PhD graduates. (davidman820)

I knew an attorney who managed a Cheesecake Factory. She had worked in food services through school. As an attorney, she really did not make that much money and was not doing the field of law of her choice. How many real estate closings can you do without dying of boredom? She went into management in the food industry and makes the same salary. (Antietem)

It was always a question and puzzling to me why people study philosophy. (Blazer27)

Globe Opinion

Share Options

• Share to Facebook
• Share to Linkedin

How Science, Math and Tech Can Propel Swimmers to New Heights

One hundred years ago, in the 1924 Paris Olympics, American Johnny Weissmuller won the men’s 100m freestyle with a time of 59 seconds. Nearly 100 years later in the most recent Olympics, the delayed 2020 Games in Tokyo, Caeleb Dressel took home the same event with a time that was 12 seconds faster than Weissmuller’s.

Swimming times across the board have become much faster over the past century, a result of several factors, including innovations in training, recovery strategy, nutrition, and some equipment advances.  

One component in the improvement in swimming performances over the years is the role of biomechanics — that is, how swimmers optimize their stroke, whether it's the backstroke, breaststroke, butterfly or freestyle. 

Swimmers for decades have experimented with different techniques to gain an edge over their competitors. But in more recent years, the application of mathematics and science principles as well as the use of wearable sensor technology in training regimens has allowed some athletes to elevate their performances to new heights, including members of the University of Virginia’s swim team.

In a new research paper , a UVA professor who introduced these concepts and methods to the team and some of the swimmers who have embraced this novel approach to training — two of whom are UVA School of Engineering and Applied Science alumni — lay out how the use of data is helping to transform how competitive swimmers become elite.

‘Swimming in Data’

Ken Ono thought his time working with swim teams was over. Ono is a UVA mathematics professor, professor of data science by courtesy, and STEM advisor to the University provost. He had spent years working with competitive swimmers, first during his time at Emory University in Atlanta and then with other college teams, including Olympians, over the years.

However, he didn’t plan to continue that aspect of his work when he arrived at UVA in 2019. But after a meeting with Todd DeSorbo, who took over the UVA swim program in 2017, Ono soon found himself once again working closely with athletes, beginning his work as a consultant for the team during the 2020-2021 season . The UVA women’s swim team would win their first of four consecutive national championships that year.

“One of the things that I like quite a bit about this work is that swimming is crazy hard,” Ono said. “We were never meant to be swimmers, and it is both an athletic challenge as well as a scientific challenge — it has it all.”

Last fall, following a suggestion from DeSorbo, Ono offered a class that outlined the science-focused approach to improving swimming performances that had proven so successful at UVA, but he wanted to make sure there were no misconceptions about the seriousness of the material.

“We don’t want people thinking that it’s a cupcake course that’s offered for the swimmers,” Ono said.

So, Ono teamed up with UVA students Kate Douglass, August Lamb and Will Tenpas, as well as MIT graduate student Jerry Lu who had worked with Ono and the UVA swim team while a systems engineering and economics undergraduate at the University, to produce a paper that covered the key elements of the class and Ono’s work with swimmers.

Tenpas and Lamb both recently completed the residential master’s program at the School of Data Science as well as their careers as competitive collegiate swimmers. Douglass, who finished her UVA swim career in 2023 as one of the most decorated swimmers in NCAA history, is a graduate student in statistics at the University and is set to compete in the Paris Olympics after winning a bronze medal in the 2020 games.

The group drafted the paper, which they titled “Swimming in Data,” over the course of two months, and it was quickly accepted by The Mathematical Intelligencer. There, Ono said, it has become one of the most-read papers on a STEM subject since tracking began. In July, a version of the paper will also be published in Scientific American.

“It seems to have taken off,” Ono said.

The Impact of Digital Twins

After outlining the evolution of swimming over the past 100 years, the paper explains how an understanding of math and physics, combined with the use of technology to acquire individual-level data, can help maximize performances.

Essential to understanding the scientific principles involved with the swimming stroke, the paper says, are Newton’s laws of motion. The laws — which cover inertia, the idea that acceleration depends on an object’s mass and the amount of force applied, and the principle that an action exerted by an object on another elicits an equal and opposite reaction — help simplify how one should think about the many biomechanical factors involved with swimming, according to Tenpas.

“There are all sorts of flexibility limitations. You have water moving at you, you have wakes, you have currents — it’s easy to kind of get paralyzed by the number of factors,” said Tenpas, who after four years at Duke, where he studied mechanical engineering, enrolled in UVA’s data science program and joined the swim team with a fifth year of eligibility.

“I think having Newton’s laws is nice as it gives you this baseline we can all agree on,” he added.  

It’s a way to understand pool mechanics given the counterintuitive motion swimmers must use to propel themselves forward, according to Ono. 

“The reason that we go to great extent to recall Newton’s laws of motion is so that we can break down the factors that matter when you test a swimmer,” he said. 

To conduct these tests, Ono and his team use sensors that can be placed on swimmers’ wrists, ankles or backs to gather acceleration data, measured as inertial measurement units. That information is then used to generate what are called digital twins, which precisely replicate a swimmer’s movements.

These twins reveal strengths and weaknesses, allowing Ono and the coaching staff to make recommendations on technique and strategy — such as how to reduce drag force, a swimmer’s true opponent — that will result in immediate improvement. In fact, through the analysis of data and the use of Newton’s laws, it is possible to make an accurate prediction about how much time a swimmer can save by making a given adjustment.

Lamb, who swam for UVA for five years while a computer science undergrad then as a data science master’s student, likened digital twins to a feature in the popular Nintendo game Mario Kart where you can race against a ghost version of yourself.  

“Being able to have this resource where you can test at one month and then spend a month or two making that adjustment and then test again and see what the difference is — it’s an incredibly valuable resource,” he said. 

To understand the potential of digital twins, one need only look at the example of Douglass, one of the co-authors, which is cited in the paper.

A flaw was identified in her head position in the 200m breaststroke. Using her digital twin, Ono and the coaching staff were able to quantify how much time she could save per streamline glide by making a modification, given her obvious talent and aerobic capacity. She did, and the results were remarkable. In November 2020, when her technique was tested, the 200m breaststroke wasn’t even on her event list. Three years later, she held the American record.

‘Everyone’s Doing It Now’

Swimming will be front and center in the national consciousness this summer. First, the U.S. Olympic Team Trials will be held in Indianapolis in June, leading up to the Paris Olympics in July and August, where DeSorbo, UVA’s coach who embraced Ono’s data-driven strategic advice, will lead the women’s team.

Many aspiring swimmers will undoubtedly be watching over the coming weeks, wondering how they might realize their full athletic potential at whatever level that might be.

For those who have access to technology and data about their technique, Tenpas encouraged young swimmers to take advantage.

He noted the significant amount of time a swimmer must put in to reach the highest levels of the sport, estimating that he had been swimming six times per week since he was 12 years old.  

“If you’re going to put all of this work in, at least do it smart,” Tenpas said.

At the same time, Lamb urged young swimmers who may not yet have access to this technology to not lose faith in their potential to improve.

“While this is an incredibly useful tool to make improvements to your technique and to your stroke, it’s not the end all, be all,” he said.

“There are so many different ways to make improvements, and we’re hopeful that this will become more accessible as time goes on,” Lamb said of the data methods used at UVA.

As for where this is all going, with the rapidly expanding use and availability of data and wearable technology, Ono thinks his scientific approach to crafting swimming strategies will soon be the norm.

“I think five years from now, our story won’t be a story. It’ll be, ‘Oh, everyone’s doing it now,’” he said.

Story republished with permission from the UVA School of Data Science.

Questions? Comments?

Office of communications.

The Office of Communications is charged with keeping all stakeholders well informed about the School's mission, vision, activities, progress and achievements.  Web Issue? SUBMIT A REQUEST

Microscopic defects in ice shape how massive glaciers flow, study shows

The findings should help scientists refine predictions of future sea-level rise..

As they seep and calve into the sea, melting glaciers and ice sheets are raising global water levels at unprecedented rates. To predict and prepare for future sea-level rise, scientists need a better understanding of how fast glaciers melt and what influences their flow.

Now, a study by MIT scientists offers a new picture of glacier flow, based on microscopic deformation in the ice. The results show that a glacier's flow depends strongly on how microscopic defects move through the ice.

The researchers found they could estimate a glacier's flow based on whether the ice is prone to microscopic defects of one kind versus another. They used this relationship between micro- and macro-scale deformation to develop a new model for how glaciers flow. With the new model, they mapped the flow of ice in locations across the Antarctic Ice Sheet.

Contrary to conventional wisdom, they found, the ice sheet is not a monolith but instead is more varied in where and how it flows in response to warming-driven stresses. The study "dramatically alters the climate conditions under which marine ice sheets may become unstable and drive rapid rates of sea-level rise," the researchers write in their paper.

"This study really shows the effect of microscale processes on macroscale behavior," says Meghana Ranganathan PhD '22, who led the study as a graduate student in MIT's Department of Earth, Atmospheric and Planetary Sciences (EAPS) and is now a postdoc at Georgia Tech. "These mechanisms happen at the scale of water molecules and ultimately can affect the stability of the West Antarctic Ice Sheet."

"Broadly speaking, glaciers are accelerating, and there are a lot of variants around that," adds co-author and EAPS Associate Professor Brent Minchew. "This is the first study that takes a step from the laboratory to the ice sheets and starts evaluating what the stability of ice is in the natural environment. That will ultimately feed into our understanding of the probability of catastrophic sea-level rise."

Ranganathan and Minchew's study appears this week in the Proceedings of the National Academy of Sciences .

Glacier flow describes the movement of ice from the peak of a glacier, or the center of an ice sheet, down to the edges, where the ice then breaks off and melts into the ocean -- a normally slow process that contributes over time to raising the world's average sea level.

In recent years, the oceans have risen at unprecedented rates, driven by global warming and the accelerated melting of glaciers and ice sheets. While the loss of polar ice is known to be a major contributor to sea-level rise, it is also the biggest uncertainty when it comes to making predictions.

"Part of it's a scaling problem," Ranganathan explains. "A lot of the fundamental mechanisms that cause ice to flow happen at a really small scale that we can't see. We wanted to pin down exactly what these microphysical processes are that govern ice flow, which hasn't been represented in models of sea-level change."

The team's new study builds on previous experiments from the early 2000s by geologists at the University of Minnesota, who studied how small chips of ice deform when physically stressed and compressed. Their work revealed two microscopic mechanisms by which ice can flow: "dislocation creep," where molecule-sized cracks migrate through the ice, and "grain boundary sliding," where individual ice crystals slide against each other, causing the boundary between them to move through the ice.

The geologists found that ice's sensitivity to stress, or how likely it is to flow, depends on which of the two mechanisms is dominant. Specifically, ice is more sensitive to stress when microscopic defects occur via dislocation creep rather than grain boundary sliding.

Ranganathan and Minchew realized that those findings at the microscopic level could redefine how ice flows at much larger, glacial scales.

"Current models for sea-level rise assume a single value for the sensitivity of ice to stress and hold this value constant across an entire ice sheet," Ranganathan explains. "What these experiments showed was that actually, there's quite a bit of variability in ice sensitivity, due to which of these mechanisms is at play."

A mapping match

For their new study, the MIT team took insights from the previous experiments and developed a model to estimate an icy region's sensitivity to stress, which directly relates to how likely that ice is to flow. The model takes in information such as the ambient temperature, the average size of ice crystals, and the estimated mass of ice in the region, and calculates how much the ice is deforming by dislocation creep versus grain boundary sliding. Depending on which of the two mechanisms is dominant, the model then estimates the region's sensitivity to stress.

The scientists fed into the model actual observations from various locations across the Antarctic Ice Sheet, where others had previously recorded data such as the local height of ice, the size of ice crystals, and the ambient temperature. Based on the model's estimates, the team generated a map of ice sensitivity to stress across the Antarctic Ice Sheet. When they compared this map to satellite and field measurements taken of the ice sheet over time, they observed a close match, suggesting that the model could be used to accurately predict how glaciers and ice sheets will flow in the future.

"As climate change starts to thin glaciers, that could affect the sensitivity of ice to stress," Ranganathan says. "The instabilities that we expect in Antarctica could be very different, and we can now capture those differences, using this model."

• Global Warming
• Snow and Avalanches
• Oceanography
• Severe Weather
• Greenland ice sheet
• Antarctic ice sheet

Story Source:

Materials provided by Massachusetts Institute of Technology . Original written by Jennifer Chu. Note: Content may be edited for style and length.

Journal Reference :

• Meghana Ranganathan, Brent Minchew. A modified viscous flow law for natural glacier ice: Scaling from laboratories to ice sheets . Proceedings of the National Academy of Sciences , 2024; 121 (23) DOI: 10.1073/pnas.2309788121

Cite This Page :

Explore More

• More Effective Multipurpose Robots
• CO2 Conversion at a Much Larger Scale
• The Embryo Assembles Itself
• Thawing Permafrost: Not A Tipping Point
• Climate Change Was No Problem for Sharks
• Fungus Breaks Down Ocean Plastic
• Kinship and Ancestry of the Celts
• How Statin Therapy May Prevent Cancer
• Origins of 'Welsh Dragons' Exposed
• Resting Brain: Neurons Rehearse for Future

Trending Topics

Strange & offbeat.

How Science, Math, and Tech Can Propel Swimmers to New Heights

One hundred years ago, in the 1924 Paris Olympics, American Johnny Weissmuller won the men’s 100m freestyle with a time of 59 seconds. Nearly 100 years later in the most recent Olympics, the delayed 2020 Games in Tokyo, Caeleb Dressel took home the same event with a time that was 12 seconds faster than Weissmuller’s.  

Swimming times across the board have become much faster over the past century, a result of several factors, including innovations in training, recovery strategy, nutrition, and some equipment advances.  

One component in the improvement in swimming performances over the years is the role of biomechanics — that is, how swimmers optimize their stroke, whether it's the backstroke, breaststroke, butterfly, or freestyle.  

Swimmers for decades have experimented with different techniques to gain an edge over their competitors. But in more recent years, the application of mathematics and science principles as well as the use of wearable sensor technology in training regimens has allowed some athletes to elevate their performances to new heights, including members of the University of Virginia’s swim team.  

In a new research paper , a UVA professor who introduced these concepts and methods to the team and some of the swimmers who have embraced this novel approach to training lay out how the use of data is helping to transform how competitive swimmers become elite.

‘Swimming in Data’

Ken Ono thought his time working with swim teams was over. Ono — a UVA mathematics professor, professor of data science by courtesy, and STEM advisor to the University provost — had spent years working with competitive swimmers, first during his time at Emory University in Atlanta and then with other college teams, including Olympians, over the years.

However, he didn’t plan to continue that aspect of his work when he arrived at UVA in 2019. But after a meeting with Todd DeSorbo, who took over the UVA swim program in 2017, Ono soon found himself once again working closely with athletes, beginning his work as a consultant for the team during the 2020-21 season . The UVA women’s swim team would win their first of four consecutive national championships that year.  

“One of the things that I like quite a bit about this work is that swimming is crazy hard,” Ono said. “We were never meant to be swimmers, and it is both an athletic challenge as well as a scientific challenge — it has it all.”

Last fall, following a suggestion from DeSorbo, Ono offered a class that outlined the science-focused approach to improving swimming performances that had proven so successful at UVA, but he wanted to make sure there were no misconceptions about the seriousness of the material.

“We don’t want people thinking that it’s a cupcake course that’s offered for the swimmers,” Ono said.

So, Ono teamed up with UVA students Kate Douglass, August Lamb, and Will Tenpas, as well as MIT graduate student Jerry Lu who had worked with Ono and the UVA swim team while an undergraduate at the University, to produce a paper that covered the key elements of the class and Ono’s work with swimmers.  

Tenpas and Lamb both recently completed the residential master’s program at the School of Data Science as well as their careers as competitive collegiate swimmers. Douglass, who finished her UVA swim career in 2023 as one of the most decorated swimmers in NCAA history, is a graduate student in statistics at the University and is set to compete in the Paris Olympics after winning a bronze medal in the 2020 games.

The group drafted the paper, which they titled “Swimming in Data,” over the course of two months, and it was quickly accepted by The Mathematical Intelligencer. There, Ono said, it has become one of the most-read papers on a STEM subject since tracking began. In July, a version of the paper will also be published in Scientific American.  

“It seems to have taken off,” Ono said.

The impact of digital twins

After outlining the evolution of swimming over the past 100 years, the paper explains how an understanding of math and physics, combined with the use of technology to acquire individual-level data, can help maximize performances.  

Essential to understanding the scientific principles involved with the swimming stroke, the paper says, are Newton’s laws of motion. The laws — which cover inertia, the idea that acceleration depends on an object’s mass and the amount of force applied, and the principle that an action exerted by an object on another elicits an equal and opposite reaction — help simplify how one should think about the many biomechanical factors involved with swimming, according to Tenpas.

“There are all sorts of flexibility limitations. You have water moving at you, you have wakes, you have currents — it’s easy to kind of get paralyzed by the number of factors,” said Tenpas, who after four years at Duke, where he studied mechanical engineering, enrolled in UVA’s data science program and joined the swim team with a fifth year of eligibility.

“I think having Newton’s laws is nice as it gives you this baseline we can all agree on,” he added.  

It’s a way to understand pool mechanics given the counterintuitive motion swimmers must use to propel themselves forward, according to Ono.  

“The reason that we go to great extent to recall Newton’s laws of motion is so that we can break down the factors that matter when you test a swimmer,” he said.  

To conduct these tests, Ono and his team use sensors that can be placed on swimmers’ wrists, ankles, or backs to gather acceleration data, measured as inertial measurement units. That information is then used to generate what are called digital twins, which precisely replicate a swimmer’s movements.  

These twins reveal strengths and weaknesses, allowing Ono and the coaching staff to make recommendations on technique and strategy — such as how to reduce drag force, a swimmer’s true opponent — that will result in immediate improvement. In fact, through the analysis of data and the use of Newton’s laws, it is possible to make an accurate prediction about how much time a swimmer can save by making a given adjustment.

Lamb, who swam for UVA for five years while a computer science undergrad then as a data science master’s student, likened digital twins to a feature in the popular Nintendo game Mario Kart where you can race against a ghost version of yourself.  

“Being able to have this resource where you can test at one month and then spend a month or two making that adjustment and then test again and see what the difference is — it’s an incredibly valuable resource,” he said.  

To understand the potential of digital twins, one need only look at the example of Douglass, one of the co-authors, which is cited in the paper.

A flaw was identified in her head position in the 200m breaststroke. Using her digital twin, Ono and the coaching staff were able to quantify how much time she could save per streamline glide by making a modification, given her obvious talent and aerobic capacity. She did, and the results were remarkable. In November 2020, when her technique was tested, the 200m breaststroke wasn’t even on her event list. Three years later, she held the American record.

‘Everyone’s doing it now’

Swimming will be front and center in the national consciousness this summer. First, the U.S. Olympic Team Trials will be held in Indianapolis in June, leading up to the Paris Olympics in July and August, where DeSorbo, UVA’s coach who embraced Ono’s data-driven strategic advice, will lead the women’s team.  

Many aspiring swimmers will undoubtedly be watching over the coming weeks, wondering how they might realize their full athletic potential at whatever level that might be.  

For those who have access to technology and data about their technique, Tenpas encouraged young swimmers to take advantage.  

He noted the significant amount of time a swimmer must put in to reach the highest levels of the sport, estimating that he had been swimming six times per week since he was 12 years old.  

“If you’re going to put all of this work in, at least do it smart,” Tenpas said.  

At the same time, Lamb urged young swimmers who may not yet have access to this technology to not lose faith in their potential to improve.  

“While this is an incredibly useful tool to make improvements to your technique and to your stroke, it’s not the end all, be all,” he said.

“There are so many different ways to make improvements, and we’re hopeful that this will become more accessible as time goes on,” Lamb said of the data methods used at UVA.

As for where this is all going, with the rapidly expanding use and availability of data and wearable technology, Ono thinks his scientific approach to crafting swimming strategies will soon be the norm.  

“I think five years from now, our story won’t be a story. It’ll be, ‘Oh, everyone’s doing it now,’” he said. 

MSDS Student Profiles: August Lamb and Will Tenpas on Balancing Swimming and Graduate School

Ken Ono Talks About Using Data to Improve Swimmer Performance on CBS19 for “Inside The Numbers”

Data Science Master’s Students Tackle Diverse, Real-World Challenges in Capstone Projects

Get the latest news.

Subscribe to receive updates from the School of Data Science.

• Prospective Student
• School of Data Science Alumnus
• UVA Affiliate
• Industry Member