acm doctoral dissertation award 2023

SIGSAC Doctoral Dissertation Awards

"for outstanding phd thesis in computer and information security".

The SIGSAC Awards Committee is pleased to announce the awardees of the SIGSAC 2021 awards. The award recipients are:

The ACM Special Interest Group for Security Audit and Control (SIGSAC) is soliciting nominations for the 2024 SIGSAC Doctoral Dissertation Award. This annual award by SIGSAC recognizes excellent research and dissertation by doctoral candidates in computer and information security and privacy. The SIGSAC Doctoral Dissertation Award winner and up to two runners-up will be recognized at the ACM CCS 2024 conference. The award winner will receive a plaque, a $1,500 honorarium and a complimentary registration to CCS 2024. The runners-up each will receive a plaque and complimentary registration to CCS 2024.

Nomination Deadline:

Eligibility:, nomination procedure:.

A nomination statement summarizing the candidate's PhD thesis contribution and potential impact, and justification of the nomination (two pages maximum);

Three endorsement letters supporting the nomination including the significant PhD thesis contributions of the candidate. Each endorsement should be no longer than 500 words with clear specification of nominee PhD thesis contributions and potential impact on the computer and information security field. Note that the three endorsement letters must be submitted in addition to the nomination statement .

Also, the committee will adhere to the ACM Awards Committee Conflict of Interest (COI) guidelines . Particularly, the SIGSAC dissertation award committee members and chair are not allowed to nominate and endorse candidates.

Decision Notification:

The award honorarium, the award plaques and the conference registration fee for the winner to attend the ACM CCS Conference will be fully funded by SIGSAC and included in its annual budget.

Further Information and Inquiry:

Submission instructions and a list of past winners are available at https://www.sigsac.org/award/diss-awards.html . For information not found in this message or for any other inquiries, contact the SIGSAC Doctoral Dissertation Award Committee Chair, Zhiqiang Lin.

A potential conflict of interest occurs when a person is involved in making a decision that:

could result in that person, a close associate of that person, or that person's company or institution receiving significant financial gain, such as a contract or grant, or

could result in that person, or a close associate of that person, receiving significant professional recognition, such as an award or the selection of a paper, work, exhibit, or other type of submitted presentation.

Some examples of instances of associations that could cause a conflict of interest are:

Prior Award Recipients:

ACM PODC 2023

June 19-23, 2023, Orlando, Florida

2023 Dissertation Award

Principles of Distributed Computing Doctoral Dissertation Award awarded jointly by ACM Symposium on Principles of Distributed Computing EATCS Symposium on Distributed Computing

Call for Nominations

We are soliciting nominations for the 2023 Principles of Distributed Computing Doctoral Dissertation Award.  The award will be presented at the 42nd ACM Symposium on Principles of Distributed Computing in Orlando, Florida, on June 19-23, 2023.

Submission deadline: February 19th, 2023 Submission link: https://podc-dda23.hotcrp.com/paper/new Information about the award: https://www.podc.org/dissertation/

Submission Guidelines

Please nominate excellent dissertations in the area of Distributed Computing that were successfully defended (or, in lieu of a defense, obtained a final approval) in the period January 1st, 2021 through December 31st, 2022.

Detailed submission guidelines can be found at the bottom of the current page and of the award page: https://www.podc.org/dissertation/

Award Committee

• Shlomi Dolev, (chair), Ben-Gurion University of the Negev, Israel 
• Fabian Kuhn, University of Freiburg, Germany
• Christian Scheideler, Universität Paderborn, Germany
• Philipp Woelfel, University of Calgary, Canada

All questions about submissions should be emailed to Shlomi Dolev ( [email protected] )

Nomination and Submission

A one-page nomination letter must be submitted by the thesis advisor. The nomination should highlight the dissertation’s contributions and justify why the dissertation is worthy of the award.

Submission Checklist

A nomination must include:

• Contact details (affiliation and email addresses) of the advisor and the doctoral student.
• A formal document from the student’s department/institution/organization verifying the date that the dissertation was successfully defended (a scanned version is acceptable for the submission, but the original document might be required at a later stage of the evaluation). If not indicated by the document, also state the period of time the student was enrolled in the doctoral program.
• A one page justification letter.
• Publications that contain material from the thesis, detailing what material was taken from which part of the thesis and the parts that are not contained in the thesis.
• Publications that are cited in the thesis, but do not contain material that also appears in the thesis.
• Papers currently under review, including journal submissions of previously published work, that contain material from the thesis, what material was taken from which part of the thesis and the parts that are not contained in the thesis.
• Those parts of the thesis which are not included in the other lists.
• A list of awards the student received for the thesis and/or publications related to the thesis.
• One copy of the dissertation in electronic form (preferably in pdf).
• A separate copy of the abstract in electronic form (either as pdf or plain text).

Review Process

The committee will consist of four core members and a number of ad-hoc members, selected as described below. The review process will consist of two stages:

The first selection phase, carried out by the core members, will be based on the nomination letters and publication lists. At the end of this phase, a short list of dissertations to be considered in the second round will be compiled.

Based on the short list, the four core members will identify experts on the topics of the dissertations and invite them to serve as additional (ad hoc) members of the committee. The committee should include sufficiently many members to allow each dissertation to be reviewed by three members without requiring any member to review more than two dissertations.

Evaluation Criteria

The nominated dissertations will be reviewed for technical depth and significance of the research contributions in the area of Distributed Computing, the potential impact on theory and practice, and quality of presentation/writing, including thoroughness of description of related work and understandability of algorithms and proofs.

•  The award presentation will alternate between DISC (even years) and PODC (odd years).
•  The winning dissertation will receive a plaque and a monetary prize.
•  The committee reserves the right to split or decline to give the award.
•  The committee can give Honorable Mentions to up to two non-winning dissertations meriting special recognition (or one Honorable Mention in case the award is split).

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Call for Nominations: ACM Doctoral Dissertation Award – Due: Sep 22, 2023 (8AM)

September 8, 2023

ACM Doctoral Dissertation Award

ACM established the Doctoral Dissertation Award program to recognize and encourage superior research and writing by doctoral candidates in computer science and engineering. The award is presented each June at the ACM Awards Banquet and is accompanied by a prize of $20,000 plus travel expenses to the banquet.  As of January 1, 2014 all winning dissertations are published exclusively in print and electronic formats as part of the ACM Books Series, which includes distribution through the ACM Digital Library.  Honorable Mention(s) may also be awarded, with a prize of $10,000 shared among recipients.

• Note regarding the competitiveness of this award: UBC may nominate only 2 dissertations to the international competition, and only 1 ACM Doctoral Dissertation Award is offered by ACM annually worldwide.
• Nomination :  Supervisors need to submit the nomination statement(s)  (nomination statement should be written by the supervisor of 200-300 words in length),  via  [email protected]  by 8:00AM on Friday, 22 September 2023.

Note that, should the student be selected to be one of UBC’s nominees, the PhD student’s thesis supervisor will be responsible for submitting the nomination items to ACM by the October 31 institution nomination deadline.  ACM requires that the nomination be submitted by the PhD student’s thesis supervisor.

The full nomination package includes:

• Suggested citation if the candidate is selected.  This should be a concise statement (maximum of 25 words) describing the key technical or professional accomplishment for which the candidate merits this award.
• Nomination statement (200-300 words in length) addressing why the candidate should receive this award.  This should address the significance of the dissertation, not simply repeat the information in the abstract.
• An endorsement letter from the department head.
• At least 3, and not more than 5, supporting letters should be included from experts in the field who can provide additional insights or evidence of the dissertation’s impact.  (The nominator/advisor may not write a letter of support.)
• Copy of the dissertation, together with a  copyright transfer form filled out by the candidate and assigning exclusive publication rights to ACM.  Copyright will revert to the author if it is not selected for publication.

For further information, including detailed nomination procedures, please visit:  https://www.grad.ubc.ca/awards/acm-doctoral-dissertation-award

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2023 ACM SIGMIS Doctoral Dissertation Award (extended deadline)

1.  2023 acm sigmis doctoral dissertation award (extended deadline).

Invitation to submit to the 2023 ACM SIGMIS Doctoral Dissertation Award Competition. We are seeking outstanding doctoral dissertations from around the globe in the field of Information Systems that have been completed in the time period from July 1, 2022, to June 30, 2023.

Nominations should be submitted no later than midnight (UTC -7), January 15th, 2024 (note: deadline extension). The candidate's Ph.D. advisor or department chair should submit the nomination. Only one nomination can be made from an institution.

The following 3 items of documentation are required :

• A paper derived from the dissertation. The initial screening of submissions will be based on a purposefully written paper designed to highlight the significance and contribution of the research. If the dissertation consists of several essays, the paper should tie the essays in a coherent manner. The paper is expected to cover the whole dissertation research.
• The complete dissertation.
• A nomination letter from the student's dissertation advisor or department chair.

For instructions on the submission requirements and more details, please see the Call for Nominations at:

https://icis2023.aisconferences.org/acm-sigmis-doctoral-dissertation-award/

We look forward to your nominations!

Atreyi Kankanhalli, Natalia Levina, Andrea Carugati

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Call for Award Nominations

(1) call for nominations: acm sigkdd 2023 innovation, service, and rising star awards.

ACM SIGKDD invites your nominations for its 2023 Innovation Award, Service Award, and Rising Star Award.

ACM SIGKDD, ACM’s Special Interest Group on Knowledge Discovery and Data Mining (KDD), is the premier global professional organization for researchers and professionals dedicated to the advancement of the science and practice of knowledge discovery and data mining. It established the Innovation and Service Awards to recognize outstanding technical and service contributions to the KDD field. It established the Rising Star Award to promote young KDD researchers as they build up their careers.

Nominations due Monday May 1, 2023

Send your nomination package in one zip file to Philip S. Yu via email: [email protected] after April 20.

ACM SIGKDD Innovation Award

The SIGKDD Innovation Award recognizes one individual or one group of collaborators whose outstanding technical innovations in the field of Knowledge Discovery and Data Mining have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems. This award is chosen by the SIGKDD Awards Committee.

The previous SIGKDD Innovation Award winners were Rakesh Agrawal, Jerome Friedman, Heikki Mannila, Jiawei Han, Leo Breiman, Ramakrishnan Srikant, Usama M. Fayyad, Raghu Ramakrishnan, Padhraic Smyth, Christos Faloutsos, J. Ross Quinlan, Vipin Kumar, Jon Kleinberg, Pedro Domingos, Hans-Peter Kriegel, Philip S. Yu, Jian Pei, Bing Liu, Charu Aggarwal, Thorsten Joachims, Johannes Gehrke, and Huan Liu.

Eligibility:  The nominees can be anyone except the SIGKDD Executive Committee Chair and the members of the SIGKDD Innovation/Service/Rising Star Awards Committee.

Nomination Process:   Anyone in the field can put forward a nomination (self-nominations are excluded). Nominations should include a proposed citation (up to 25 words) and a detailed statement to justify the nomination (500 words or less). The nomination should explicitly indicate the specific nature of the impact. Three or more supporting letters should be submitted. The letters need to address the significance of the contributions cited in the nomination. Recipients of other awards are eligible if the SIGKDD nomination is for different contributions. The nomination and letters should describe the difference and the impact of the new contributions.

Nominations must be received by May 1, 2023, to be considered for this year’s award. Please include a detailed CV for the nominee in the nomination. Nominations are valid for three years and can be resubmitted or updated in subsequent years. The Awards Committee will evaluate all nominations and decide on zero or more winners.

ACM SIGKDD Service Award

The SIGKDD Service Award recognizes one individual or one group for their outstanding professional services contributions to the field of knowledge discovery and data mining. Services recognized include significant contributions to the activities of professional KDD societies and conferences, educating students, researchers and practitioners, funding R&D activities, professional volunteer services in disseminating technical information to the field, and contributions to society at large through applications of KDD.

The previous SIGKDD Service Award winners were Gregory Piatetsky-Shapiro, Ramasamy Uthurusamy, Usama M. Fayyad, Xindong Wu, the Weka team led by Ian Witten and Eibe Frank, Won Kim, Robert Grossman, Sunita Sarawagi, Osmar R. Zaiane, R. Bharat Rao, Ying Li, Gabor Melli, Ted Senator, Jian Pei, Wei Wang, Qiang Yang, Jie Tang, Balaji Krishnapuram, Michael Zeller, Shipeng Yu, and Charu Aggarwal.

Eligibility:  The nominee(s) can be anyone except the SIGKDD Executive Committee Chair and the members of the SIGKDD Innovation/Service/Rising Star Awards Committee.

Nomination Process:  Anyone in the field can put forward a nomination (self-nominations are excluded). Nominations should include a proposed citation (up to 25 words) and a detailed statement to justify the nomination (500 words or less). Three supporting letters should be submitted. The letters need to address the significance of the service contributions cited in the nomination.

Nominations must be received by May 1, 2023, to be considered for this year’s award. Please include a detailed CV for nominee in the nomination. Nominations are valid for three years and can be resubmitted or updated in subsequent years. The Awards Committee will evaluate all nominations and decide on zero or more winners.

SIGKDD Rising Star Award

ACM SIGKDD decided to establish the Rising Star Award starting in 2020. This award is based on an individual’s whole body of work in the first five years after the PhD. The award aims to promote current SIGKDD researchers as they build up their career.

The previous SIGKDD Rising Star Award winners were Danai Koutra, Jiliang Tang, Xia Ben Hu, and Yuxiao Dong.

Eligibility:  The nominee(s) should have completed all the requirements for the PhD no earlier than December 31, 2017; parental leaves will move the date by the duration of the parental leave. The nominee can be anyone except the SIGKDD Chair and the members of the SIGKDD Innovation/Service/Rising Star Awards Committee.

Nomination Process:  Anyone in the field can nominate one person (self-nominations are excluded). Nominations should include a proposed citation (up to 25 words) and a detailed statement to justify the nomination (500 words or less). Three supporting letters should be submitted. Both the nomination and the letters need to address the significance of the contributions in the first five years after the PhD cited in the nomination. The contributions may build on the nominee’s Ph.D. work, but the emphasis should not be put on the continuing impact of the Ph.D. work.

Nominations must be received by May 1, 2023, to be considered for this year’s award. Please include a detailed CV for the nominee in the nomination. Nominations that did not result in an award can be resubmitted or updated in subsequent years as long as the eligibility conditions for the award still hold. The Awards Committee will evaluate all nominations and decide on zero or more winners.

(2) Call For Nominations: 2023 SIGKDD Test of Time Awards

Description: SIGKDD makes two annual test of time awards, one for a paper from the research track and the other for a paper from the applied science track (formerly called the industrial track). The SIGKDD Awards Committee is chartered with selecting one paper from the research track of the SIGKDD Proceedings from 10 to 12 years ago and one paper from the industrial track of the SIGKDD Proceedings from 10 to 15 years ago that have best met the “test of time,” that is, it have had the most influence since their publication. The 2023 awards will be presented at the  29th ACM KDD Conference .

Eligibility: All papers from the research tracks of SIGKDD 2011 – 2013 are eligible for the ACM SIGKDD Research Test of Time Award. All papers from the industrial tracks of SIGKDD 2008 – 2013 are eligible for the ACM SIGKDD Applied Science Test of Time Award. Papers that have received a previous ACM SIGKDD Test of Time Award are not eligible. Both awards will be chosen by the 2023 SIGKDD Test of Time Awards Committee. There is no formal nomination process for this award, but we greatly appreciate input from the SIGKDD community. We are especially interested in first-hand accounts of ways in which a paper has influenced subsequent research and practice.

Nominations due Monday May 1, 2023

Send your nominations to Geoff Webb ( [email protected] ) with subject line “SIGKDD 2023: nomination”.

(3) Call For KDD Doctoral Dissertation Award

Description: This annual award by ACM SIGKDD recognizes outstanding research by doctoral candidates in the field of data science, data mining and knowledge discovery. The KDD Doctoral Dissertation Award winner and up to two runners-up will be recognized at the KDD conference, and their dissertations will have the opportunity to be published on the KDD Web site . The award winner will receive a plaque, a check for $2,500. The award winner will also receive a free registration to attend the KDD conference. The runners-up will receive a plaque at the conference. The winner and runners-up will be invited to present their work in a special session at the KDD conference.

Nominations due: May 1, 2023

The previous winners of this award can be found at: http://www.kdd.org/awards/sigkdd-dissertation-award

Eligibility: Nominations are limited to one doctoral dissertation per department or academic unit. Submissions must be received by the submission deadline. The dissertation defense should have taken place and been accepted by the candidate’s academic unit before the submission deadline. Furthermore, the dissertation defense must not have taken place prior to January 1st, 2022. An English version of the dissertation must be submitted with the nomination. A dissertation can be nominated for both the SIGKDD Doctoral Dissertation Award and the ACM Doctoral Dissertation Award.

Important Dates:

Submission Deadline: May 1, 2023 Notification of Awards: July 11, 2023 Award Presentation at KDD 2023: August 6 – 10,  2023

Nomination Requirements

Nominations must be made by the doctoral advisor. All nomination materials must be in English and in PDF format. Late submissions will not be accepted. A nomination must include:

• A nomination letter, written by the dissertation advisor of the candidate. This letter must include full contact information for both the advisor and the nominee as well as a one or two-page summary of the significance of the dissertation.
• An endorsement letter signed by the department head.
• The nomination may include up to two supporting letters from other individuals, discussing the significance of the dissertation.
• One PDF copy of the doctoral dissertation.
• A copyright transfer form signed by the candidate is required giving permission for the dissertation to appear on KDD.org Web site if the dissertation is selected as an award recipient (but if the nomination is also being submitted for the ACM Doctoral Dissertation Award, only one form needs to be signed). See: https://www.acm.org/binaries/content/assets/publications/copyreleaseproc-8-16.pdf

Submission Procedure All nomination materials must be submitted electronically to Nitesh Chawla at this email address:  [email protected] . Please use “[SIGKDD Dissertation Award]” in your subject line. All required documents must be attached in a single email.

202 3 SIGHPC Doctoral Dissertation Award Winner 

202 3 Outstanding Doctoral Dissertation Award Winner, Dr. Keren Zhou of Rice University

R ecognized for his dissertation "Performance Measurement, Analysis, and Optimization of GPU-accelerated Applications"

Advisor: John Mellor-Crummey

202 3 SIGHPC Doctoral Dissertation Award Winner  

ACM's Special Interest Group on High Performance Computing (SIGHPC) is pleased to announce that Dr. Keren Zhou has won the 2023 SIGHPC Doctoral Dissertation Award.  This award is given each year for the best doctoral dissertation completed in high performance computing (HPC) in the previous year.  Nominations were evaluated on the novelty of the work, quality of scholarship, significance of the research contributions, and potential impact on theory and practice.  The award includes a $2,000 cash prize, a plaque, and recognition at the International Supercomputing Conference (SC23) in November.

Dr. Zhou's dissertation tackled the difficult research problem of understanding the performance of application codes accelerated on graphical processing units (GPUs), through the design and development of innovative techniques for performance instrumentation, measurement, and analysis, particularly in the context of the latest GPU technologies in use on high-end HPC platforms.  His work not only made novel contributions to the state of performance art, but the methods have been integrated in real HPC tools and applied in the optimization of real-world heterogeneous HPC applications on modern supercomputers.

"The increasing use of GPUs in a variety of fields highlights the importance of rapidly identifying performance bottlenecks in complex GPU-accelerated applications," said Dr. Zhou.  "I am pleased that our collaborations with hardware companies have led to the development of critical performance monitoring functionalities in GPUs.  Moreover, GPU application developers are beginning to use these features for performance measurement and analysis.  It is my humble hope that the techniques described in my dissertation will also provide useful insights for analysis and optimization of GPU-accelerated applications."  

Dr. Zhou received his PhD in Computer Science from Rice University in 2022.  Following completion of his graduate studies, Dr. Zhou worked as a member of the technical staff at OpenAI. Dr. Zhou will be an Assistant Professor at George Mason University starting in August 2023.

"The nomination pool was exceptionally strong this year," said Christine Harvey, SIGHPC Chair. "The tour de force of Dr. Zhou's research together with its strong technical translation in real tools demonstrates the importance of HPC's dual nature of theory AND practice that is need to drive future innovations.  We hope all of the nominees will continue to contribute to HPC techniques and technologies in the future.”

The Doctoral Dissertation Award committee was composed of six HPC researchers: Florina Ciorba (University of Basel), Camille Coti (Ecole de Technologie Superiere), Shantenu Jha (Rutgers University), Andrew "Barney" Maccabe (University of Arizona), Allen D. Malony (Chair, University of Oregon), and Dingwen Tao (Indiana University).

Award Information

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Previous Winners

2022 Winner

2021 Winner

2020 Winner

2018 Winner

Outstanding Doctoral Dissertation Award

Launched in 2016, the Doctoral Dissertation Award is awarded annually to recognize a recent doctoral candidate who has successfully defended and completed his or her Ph.D. dissertation in computer graphics and interactive techniques. Recognizing young researchers who have already made a notable contribution very early during their doctoral study, the award is presented each year at the SIGGRAPH Conference and is accompanied by a plaque, complimentary full conference registration and travel to the award ceremony. Honorable Mentions may also be awarded.

Current Recipient

Zachary ferguson.

For a dissertation which significantly extends the state of the art in physical simulation by presenting new groundbreaking methods to handle contacts in dynamic simulations of rigid and deformable objects

“Provably Robust and Accurate Methods for Rigid and Deformable Simulation with Contact”

ACM SIGGRAPH is pleased to announce Zachary Ferguson as the 2024 recipient of the Outstanding Doctoral Disseration Award. In his dissertation he presents a new method called Incremental Potential Contact (IPC) that handles collisions and contacts in an accurate, efficient and robust way. In contrast to previous approaches, the new method comes with strong theoretical guarantees that safely preventinter-penetration of objects. At the same time the method is of high practical value due to its superior computational efficiency as well as the absence of parameters that require fine tuning.

While the rigid motion and elastic deformation of individual objects under external forces is relatively straightforward to simulate, it remains a challenge to reliably handle the interaction of dynamic objects when they touch or collide. This is due to complex constellations of penetrating objects that need to be resolved in each time step. There is a long tradition of computational approaches to detect and respondto contacts in mechanical simulations. However, state of the art methods usually require the tedious adjustment of several parameters whenever the geometry, material properties, or time steps change, making parameter studies and inverse problem settings (e.g., simulation-based shape optimization) infeasible.

The Incremental Potential Contact method by Zachary Ferguson, in contrast, only has a single parameter that the user can tune to trade compute cost for accuracy. The robustness of the method is unconditional and not affected by this adjustment. The revolutionary method supports notoriously difficult settings with highly complex geometries, sliding friction, co-dimensional objects, extremely high velocities, and long time steps. It has the potential to considerably push the complexity limits of what can be simulated in graphics and computational engineering applications.

The results of Zachary Ferguson’s research are not only of a theoretical nature, as he also develops reference implementations and makes them available to the research community. His software is very successful on GitHub and is used by academic and industrial research groups worldwide.

 The committee also decided to award an honorable mention to Dr. Yu Wang for his outstanding work on exploring alternatives to the standard Laplace operator in geometry processing tasks as well as to Dr. Fangcheng Zhong for his exceptional dissertation in which he develops a Perceptually Realistic Graphics pipeline.

Previous Recipients

• 2023 Cheng Zhang
• 2022 Xue Bin Peng
• 2021 Minchen Li
• 2020 Tzu-Mao Li
• 2019 Lingqi Yan
• 2018 Jun-Yan Zhu
• 2017 Felix Heide
• 2016 Eduardo Simões Lopes Gastal

Honorable Mentions

• 2023 Georg Sperl
• 2022 Yuanming Hu, MIT
• 2021 David B. Lindell
• 2020 Yun Raymond Fei
• 2020 Mina Konakovic Lukovic
• 2019 Angela Dai
• 2019 Hao Su
• 2019 Adriana Schulz
• 2017 Myers Abraham (Abe) Davis
• 2017 Matthew O’Toole
• 2016 Sofien Bouaziz

Nomination Procedure

All doctoral dissertations successfully defended (or thesis accepted) during the calendar year prior to the nomination deadline are eligible for consideration. There is no limit on the number of nominations that can be made from any single institution or advisor. The key criteria used to evaluate the nominations include technical depth, significance of the research contribution, potential impact on theory and practice, and quality of presentation.

The submitted dissertation should be a finalized version. Nominations are welcomed from any country, but only English language versions will be accepted. Nominations are evaluated by the Outstanding Doctoral Dissertation Award Committee . Nominations, including all supporting materials and endorsement letters, are due by January 31 of each year. Click the button below to submit a nomination.

Requirements

• Name, address, phone number, and email address of the nominator
• Name, address, and email address of the candidate
• Suggested citation (maximum of 25 words)
• Nomination statement (maximum of 500 words in length) addressing why the candidate should receive this award
• Copy of the dissertation in pdf format
• The nominee’s vitae
• Endorsement letters: at most three supporting letters could be included from experts in the field

Carnegie Mellon University School of Computer Science

Scs alum wins top sigecom dissertation award.

Marylee Williams Tuesday, May 21, 2024 Print this page.

Gabriele Farina , who earned his Ph.D. from the School of Computer Science in 2023, has won the Association for Computing Machinery's Special Interest Group on Economics and Computation (ACM SIGecom) Dissertation Award, which recognizes the previous year's best dissertation in economics and computation.

Farina's thesis, " Game-Theoretic Decision Making in Imperfect-Information Games: Learning Dynamics, Equilibrium Computation and Complexity " focused on imperfect-information extensive-form games, such as poker or negotiations. His work addressed challenges in these games and provided theoretical and algorithmic foundations for strategic, game-theoretic decision-making. His thesis adviser was Tuomas Sandholm , the Angel Jordan University Professor of Computer Science in the Computer Science Department .

Farina's research details the fundamental computation of equilibria in imperfect information games and how to use learning in these computations. It also shares how to employ learning to compute extensive form-correlated and team equilibria. His work also examines what happens when human players are introduced into these models.

Farina is now an assistant professor at the Massachusetts Institute of Technology in the Electrical Engineering and Computer Science Department. Learn more about the award on the ACM Special Interest Group on Economics and Computation website .

Aaron Aupperlee | 412-268-9068 | [email protected]

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Outstanding Doctoral Dissertation Award

The SIGSOFT Outstanding Doctoral Dissertation Award is presented annually to the author of an outstanding doctoral dissertation in the area of Software Engineering. The author of the winning dissertation will be invited to publish a dissertation summary in the SIGSOFT newsletter, Software Engineering Notes (SEN). The award includes a $1000 honorarium and a plaque for the author, which is presented at the International Conference on Software Engineering (ICSE), and funding support for the recipient to travel to ICSE to receive the award (including a registration to ICSE). A public citation for the award dissertation will be placed on the SIGSOFT web site. The award recipient also receives support for travel to ICSE up to $2500 within their home continent and up to $3000 outside their home continent, including airfare, hotel, and conference registration for ICSE.

The award is for an outstanding dissertation (in software engineering) dated within the year preceding the nomination due date. For nominations for the October 30, 2023, deadline, dissertations dated December 15, 2022 to October 15, 2023 are eligible. The dissertation date can refer to the “deposit date,” “committee approval date,” or another reasonable and relevant date, depending on the process followed by the nominee’s institution. However, please note that a dissertation can be nominated only once. Thus, if, e.g., the “deposit date” and “committee approval date” would fall into two award periods, the thesis cannot be nominated twice, and the nominee would have to choose one period.

To submit a nomination for the award, please use the awards nomination portal . Please note that:

An intent to nominate must be submitted in the nomination system by October 16, 2023. The intent submission is very lightweight and only requires: (1) full name and affiliation of the nominee, (2) contact information of the nominator, and (3) some metadata. If no intent is received by the deadline, the nomination will be deemed late and not considered for this round of award selection.

A single PDF containing the nomination package must be submitted through the portal to complete the submission by October 30, 2023. The PDF should contain the following:

• Full name and affiliation of the nominee
• One- to two-page summary of the nominee’s dissertation (in English)
• Link to download the nominee’s dissertation (in any language)
• List of nominee’s publications (that were used as the basis of chapters in the nominated dissertation)
• Succinct description of why the nominee is well-qualified for the award (200-500 words)
• Up to three support letters (200-300 words will be sufficient for each support letter, although longer statements of support are of course welcome). Each support letter must include the following sentence: “To the best of my knowledge, the candidate I am endorsing has not committed any action that violates the ACM Code of Ethics and ACM’s Core Values.

The selection committee shall have the option to decline to make an award in a given year, if no suitable nominations are presented. If you have questions about this award, please contact sigsoft-dissertation-award (at) acm (dot) org.

• 2024 Bianca Trinkenreich, Understanding and Supporting Women’s Participation in Open Source Software, Northern Arizona University, advisors: Igor Steinmacher and Marco Aurelio Gerosa
• 2023 David Shriver, Increasing the Applicability of Verification Tools for Neural Networks, University of Virginia, advisors: Matt Dwyer and Sebastian Elbaum
• 2022 Wing Lam, Detecting, Characterizing, and Taming Flaky Tests, University of Illinois at Urbana-Champaign, advisors: Darko Marinov and Tao Xie
• 2021 August Shi, Improving Regression Testing Efficiency and Reliability via Test-Suite Transformations, University of Illinois at Urbana-Champaign, advisor: Darko Marinov
• 2020 Rachel Tzoref-Brill, Comprehension and Evolution of Combinatorial Models and Test Plans, Tel Aviv University
• 2019 Sergey Mechtaev, Semantic Program Repair, National University of Singapore; Honorable Mention: Christoffer Quist Adamsen, Automated Testing Techniques for Event-Driven and Dynamically Typed Software Applications, Aarhus University
• 2018 Fan Long, Automatic Patch Generation via Learning from Successful Human Patches, Massachusetts Institute of Technology
• 2017 Srdan Krstic, Trace Checking of Quantitative Properties, Politecnico di Milano
• 2016 Milos Gligoric, Regression Test Selection: Theory and Practice, University of Illinois at Urbana-Champaign, Darko Marinov, advisor
• 2015 Muath Alkhalaf, Automatic Detection and Repair of Input Validation and Sanitization Bugs, University of California, Santa Barbara, Tevfik Bultan, advisor
• 2014 Nicolas Mangano, Calico: An early-phase software design tool, University of California, Irvine, André van der Hoek, advisor
• 2013 Jeff Huang, Effective Methods for Debugging Concurrent Software, Hong Kong University of Science and Technology, Charles Zhang, advisor
• 2012 Mark Gabel, Inferring Programmer Intent and Related Errors from Software, University of California, Davis, Zhendong Su, advisor
• Myra B. Cohen, Iowa State University, United States (chair)
• Gordon Fraser, University of Passau, Germany (deputy chair)
• Aldeida Aleti, Monash University, Australia
• Kelly Blincoe, University of Auckland, New Zealand
• Gregory Gay, Chalmers and the University of Gothenburg, Sweden
• Cindy Rubio-Gonzalez, UC Davis, United States
• Rachel Tzoref-Brill, IBM, Israel
• Shin Yoo, Korea Advanced Institute of Science and Technology, South Korea
• Lingming Zhang, University of Illinois at Urbana-Champaign, United States
• Thomas Zimmermann, Microsoft Research, United States (SIGSOFT chair, non-voting)
• David Lo, Singapore Management University, Singapore (SIGSOFT award chair, non-voting)
• Natalia Juristo, Universidad Politecnica de Madrid, Spain (chair)
• Grace A. Lewis, Carnegie Mellon University, United States
• Shahar Maoz, Tel Aviv University, Israel
• Ignacio Panach, Universitat de Valencia, Spain
• Birgit Penzenstadler, Chalmers University of Technology, Sweden
• Federica Sarro, University College London, United Kingdom
• Francisco Servant, Universidad de Malaga, Spain
• Ayse Tosun, Istanbul Technical University, Turkey
• Tao Xie, Peking University, China
• Christian Bird, Microsoft Research, United States (chair)
• Paolo Tonella, Università della Svizzera Italiana, Switzerland
• Jeff Huang, Texas A&M University, United States
• Shing-Chi Cheung, Hong Kong University of Science and Technology, China
• Dan Hao, Peking University, China
• Natalia Juristo, Universidad Politécnica de Madrid, Spain
• Myra B. Cohen, Iowa State University, United States
• Lin Tan, Purdue University, United States (non-voting)
• Chris Bird (chair)
• Andy Zaidman
• Gabriele Bavota
• Mario Linares-Vasquez
• Paola Spoletini
• Peter Rigby
• Venera Arnaoudova

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UB Awards 320 Biomedical Science Degrees; 35 Earn PhDs

Commencement 2024.

Lauryn Alexandria Scott, a biomedical sciences undergraduate student, is all smiles as she walks across the stage during the May 19 biomedical sciences commencement ceremony.

By Dirk Hoffman

Published May 29, 2024

Thirty-five doctoral, 76 master’s and 209 baccalaureate candidates were eligible to receive degrees in biomedical science fields during the May commencement ceremony.

2024 Commencement Video

Related Links

• Commencement Program
• Full Gallery of Biomedical Sciences Commencement Photos

Six graduate students and nine senior undergraduates were singled out for special honors, including four graduates who received a Chancellor’s Award, the highest State University of New York undergraduate honor.

Graduates completed work in 14 departments or programs of the Jacobs School of Medicine and Biomedical Sciences :

• biochemistry
• biomedical informatics
• biomedical sciences
• biotechnical and clinical laboratory sciences
• genetics, genomics and bioinformatics
• medical physics
• microbiology and immunology
• natural sciences interdisciplinary
• neuroscience
• nuclear medicine technology
• pathology and anatomical sciences
• pharmacology and toxicology
• physiology and biophysics
• structural biology

Graduates also completed the following programs offered in alliance with the  Roswell Park Comprehensive Cancer Center Graduate Division : cancer pathology and prevention, cancer sciences, immunology, and molecular pharmacology and cancer therapeutics.

Fifteen of the doctoral degrees and eight of the master’s degrees were awarded in Roswell Park’s programs.

Allison Brashear, MD, MBA, UB’s vice president for health sciences and dean of the Jacobs School, congratulates the Class of 2024.

Lessons Learned From Recent Solar Eclipse

Allison Brashear, MD, MBA , UB’s vice president for health sciences and dean of the Jacobs School, welcomed attendees to the May 19 event at UB’s Center for the Arts and addressed the graduates.

“It fills my heart with immense joy to see all of you gathered here today,” she said.

“In the face of the challenges that have beset us in recent times, these bright scholars and scientists have exhibited extraordinary resilience, determination and perseverance in their academic endeavors. I am confident that these qualities will serve as guiding lights as they embark upon their journeys in their respective fields.”

She noted that biomedical science is one of the broadest areas of medical science and underpins much of modern medicine.

“Biomedical scientists are at the heart of multidisciplinary teams in health care. Biomedical research looks at ways to prevent and treat disease,” Brashear said. “Your innovative approaches and unwavering dedication will continue to push the boundaries of scientific discoveries and technology, leading to a brighter and healthier future for all of us.”

In his address, UB President Satish K. Tripathi, PhD, told the graduates they could learn a lot from the recent solar eclipse that generated excitement in Western New York in early April.

“Allow me to share three tips of advice gathered from the path of totality,” he quipped.

“Reconnect with the natural world, as often as possible. Instead of taking selfies, take time for self-reflection,” he said. “When you give wide berth to the stressors of modern life, you allow yourself space to find both your place in the world and your responsibility to it.”

“Do not regret circumstances beyond your control,” Tripathi added, noting the sunny days leading up to the eclipse, but the extreme cloudiness that persisted over much of WNY on April 8, the day of the event. “Notwithstanding the uncooperative weather, we all experienced a breathtaking moment. Magnify your disappointments and you miss occasions for learning, enrichment and wonder.”

“Lastly, use your expertise for the greater good. When you apply what you have learned for others’ benefit, you put your UB education to its highest purpose,” he said.

Doctoral graduate Haley Victoria Hobble won two separate graduate awards for her research and dissertation. She is flanked by Mark R. O’Brian, PhD, left, and John C. Panepinto, PhD.

Outstanding Graduates Recognized

Biochemistry graduate student research achievement award.

Doctoral graduate Haley Victoria Hobble was honored for research that received national or international recognition and for being selected to give an oral presentation at a major national or international meeting.

Dissertation: “Intrafamily Heterooligomerization of the N-Terminal Methyltransferase METTL11A”

Mentor: Christine E. Schaner-Tooley, PhD , associate professor of biochemistry

Roswell Park Graduate Division Award for Excellence in Research

Doctoral graduate Abigail Cornwell was the recipient of this award for outstanding research for her dissertation titled “Impact of Benzodiazepines on the Pancreatic Ductal Adenocarcinoma Tumor Microenvironment”

Mentor: Michael Feigin, PhD, associate professor of oncology, Roswell Park Comprehensive Cancer Center

The Dean’s Award for Outstanding Dissertation Research

Doctoral graduate Haley Victoria Hobble was the winner of this award that recognizes demonstrated excellence in research.

She was honored for her dissertation: “Intrafamily Heterooligomerization of the N-Terminal Methyltransferase METTL11A”

Mentor:  Christine E. Schaner-Tooley, PhD , associate professor of  biochemistry

The Microbiology and Immunology Award for Excellence in Dissertation Research in Memory of Dr. Murray W. Stinson

Doctoral graduate Katherine Shannon Wackowski was honored for her dissertation “Cooperation of RESC Proteins in Trypanosome RNA Editing and Holoenzyme Dynamics”

Mentor: Laurie K. Read, PhD , professor of microbiology and immunology

Dennis Higgins Award for PhD Dissertation Research in Pharmacology and Toxicology

Doctoral graduate Shirley Xu was honored for her dissertation “Troponin-Mediated Autoimmune Mechanisms of Immune Checkpoint Inhibitor-Induced Myocarditis”

Mentor: Umesh Sharma, MD, PhD , associate professor of medicine

Bishop Neuroscience Thesis Award

Doctoral graduate Richard Adam Seidman was honored for his dissertation “Oscillatory Calcium Mediated Regulation of Human Oligodendrocyte Progenitor Cells”

Mentor: Fraser J. Sim, PhD , professor of pharmacology and toxicology

The Structural Biology Award for Excellence in Dissertation Research in Memory of Dr. Robert H. Blessing

Doctoral graduate Nicholas David Clark was honored for his dissertation “Structure/Function Studies of Virulence Factors from Periodontal Pathogens and Membrane Sphingolipid Hydroxylases”

Mentor: Michael G. Malkowski, PhD , professor and chair of structural biology

The four undergraduate SUNY Chancellor’s Award winners, from left, Bryan R. Renzoni, Lea Kyle, Rachel Esther Sanyu and Sarah Bukhari, along with Jennifer A. Surtees, PhD.

SUNY Chancellor’s Award for Student Excellence

Sarah Bukhari, Lea Kyle, Bryan R. Renzoni and Rachel Esther Sanyu were recognized with the SUNY Chancellor’s Award. It recognizes students for their integration of academic excellence with other aspects of their lives that may include leadership, athletics, community service, creative and performing arts, entrepreneurship or career achievement.

Bukhari graduates with a bachelor’s degrees in biochemistry. She is an undergraduate researcher in the lab of  Jennifer A. Surtees, PhD , professor of  biochemistry . Bukhari secured funding from the Experiential Learning Network and a Mentored Research micro-credential.

Beyond academics, the Grand Island, New York, native is deeply involved in community engagement, serving as both the volunteer coordinator and vice president of the largest student-run pre-health organization, the Association of Pre-Medical Students, and was awarded a Community Engagement micro-credential and gathering 500+ volunteer hours.

With dual roles as dance coach and social media coordinator for the Pakistani Student Association, she fosters a network of communities to embrace diversity and celebrate traditions.

A native of Martville, New York, Kyle is a University Honors College Scholar who graduates with a Bachelor of Science degree in biochemistry with minors in both physics and public health.

She has been a Student Association, Recreation Department, Student Engagement and TASS Center employee. She also is the current president of UB Rotaract, a volunteering club on campus.

Kyle is also a student researcher in the  Department of Microbiology and Immunology ,  Elizabeth A. Wohlfert, PhD , associate professor of microbiology and immunology, focusing on the effects of chronic inflammation on muscle function due to chronic infection..

Renzoni, of East Amherst, New York, graduates with a Bachelor of Science degree in biochemistry. He is a University Honors College Presidential Scholar and Honors College Ambassador.

A BioXFEL Scholar, he has received multiple research internship positions and worked in two different laboratories, contributing to work on the development of novel organic and organometallic compounds with applications as cancer therapies.

Renzoni has also served as a co-chair of the G14 Leadership Summit, president and executive adviser of UB ChemClub, and both assistant music director and music director of The Enchords, UB’s all-gender a cappella group.

Sanyu, an international student from Uganda, graduates with a bachelor’s degree in pharmacology and toxicology.

She is an Honors College Scholar who conducted oncology research within the lab of Wendy Huss, PhD, at Roswell Park Comprehensive Cancer Center and at Johnson & Johnson, where she earned the 2023 Inspire Spotlight Award.

Sanyu has also worked as a student assistant in the Office of Interprofessional Education and an honors peer mentor. 

She is a founder of a health care app and is involved with the community through her work with Suubi Cancer Relief and Hillside Family of Agencies.

Sanyu also loves to dance and was a member of the UBMystique and 8-Count dance teams.

Undergraduate Outstanding Senior Awards

The following awards honor high academic performance and involvement in the campus community and external organizations:

Biochemistry Sarah Bukhari

Biomedical Sciences Alexis Krayevsky

Biotechnology Tanvi Dixit

Medical Technology Eva Wisniewski

Neuroscience Leah Heiler

Nuclear Medicine Technology Kelly Mahan

Pharmacology and Toxicology Rachel Esther Sanyu

Commencement speaker Styliani-Anna (Stella) E. Tsirka, PhD, tells the graduates to never lose sight of the wonder and awe that first drew them to the biomedical sciences.

Keynote Theme One of Compassion, Resilience

Commencement speaker Styliani-Anna (Stella) E. Tsirka, PhD, the Miriam and David Donoho Distinguished Professor of pharmacological sciences and vice dean for faculty affairs at the Renaissance School of Medicine at Stony Brook University, spoke about empathy and persistence.

“Beyond the technical skills and academic achievements that you have earned and will continue to earn, what will set you apart is your capacity for empathy, for compassion, your ethical responsibility,” she said.

“In the pursuit of scientific advancement, try not to lose sight of the human element and the living organisms whose lives may be impacted by our work.”

Tsirka noted that biomedical scientists have a serious duty to use their expertise to make society better, alleviate suffering and to promote the health and well-being of all people, regardless of race, gender or socioeconomic status.

“If you decide to further pursue scientific inquiry, do remember that you will need persistence and resilience,” she said. “Experimental science is not for the faint of heart.”

She remarked that her lab members often talk about the fact that it is called “research” instead of just “search.”

“The majority of our experiments will not be successful, but the ones that provide that ‘eureka moment’ will last a lifetime,” Tsirka assured the graduates. “Remember that setbacks are valuable lessons that shape the way for future success.”

Tsirka encouraged the graduates to embrace the idea of lifelong learning.

“To remain at the forefront of your field, you must remain curious and receptive of new ideas,” she said.

“Importantly, science is also delicate. Continue to approach it with integrity and rigor.”

The UMass Amherst Department of Anthropology

Anthropology is the study of people and cultures of the past and present in their cultural, biological, and material contexts. From human evolution to endangered languages, cultural diversity to health disparities, we seek answers to some of today's most complex questions. Explore what the UMass Department of Anthropology has to offer.

Major in anthropology

Anthropology majors work closely with our nationally recognized faculty to explore cultural, linguistic, archaeological, and physical anthropology in all its intricacies while developing the ability to think critically and to develop research methods.

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Our graduate program offers both MA and PhD degrees in anthropology. Students can choose from a broad range of graduate-level courses in anthropology and pursue interdisciplinary approaches within related departments.

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CS&E Announces 2024-25 Doctoral Dissertation Fellowship (DDF) Award Winners

Seven Ph.D. students working with CS&E professors have been named Doctoral Dissertation Fellows for the 2024-25 school year. The Doctoral Dissertation Fellowship is a highly competitive fellowship that gives the University’s most accomplished Ph.D. candidates an opportunity to devote full-time effort to an outstanding research project by providing time to finalize and write a dissertation during the fellowship year. The award includes a stipend of $25,000, tuition for up to 14 thesis credits each semester, and subsidized health insurance through the Graduate Assistant Health Plan.

CS&E congratulates the following students on this outstanding accomplishment:

• Athanasios Bacharis (Advisor: Nikolaos Papanikolopoulos )
• Karin de Langis (Advisor:  Dongyeop Kang )
• Arshia Zernab Hassan (Advisors: Chad Myers )
• Xinyue Hu (Advisors: Zhi-Li Zhang )
• Lucas Kramer (Advisors: Eric Van Wyk )
• Yijun Lin (Advisors: Yao-Yi Chiang )
• Mingzhou Yang (Advisors: Shashi Shekhar )

Athanasios Bacharis

Bacharis’ work centers around the robot-vision area, focusing on making autonomous robots act on visual information. His research includes active vision approaches, namely, view planning and next-best-view, to tackle the problem of 3D reconstruction via different optimization frameworks. The acquisition of 3D information is crucial for automating tasks, and active vision methods obtain it via optimal inference. Areas of impact include agriculture and healthcare, where 3D models can lead to reduced use of fertilizers via phenotype analysis of crops and effective management of cancer treatments. Bacharis has a strong publication record, with two peer-reviewed conference papers and one journal paper already published. He also has one conference paper under review and two journal papers in the submission process. His publications are featured in prestigious robotic and automation venues, further demonstrating his expertise and the relevance of his research in the field.

Karin de Langis

Karin's thesis works at the intersection of Natural Language Processing (NLP) and cognitive science. Her work uses eye-tracking and other cognitive signals to improve NLP systems in their performance and cognitive interpretability, and to create NLP systems that process language more similarly to humans. Her human-centric approach to NLP is motivated by the possibility of addressing the shortcomings of current statistics-based NLP systems, which often become stuck on explainability and interpretability, resulting in potential biases. This work has most recently been accepted and presented at SIGNLL Conference on Computational Natural Language Learning (CoNLL) conference which has a special focus on theoretically, cognitively and scientifically motivated approaches to computational linguistics.

Arshia Zernab Hassan

Hassan's thesis work delves into developing computational methods for interpreting data from genome wide CRISPR/Cas9 screens. CRISPR/Cas9 is a new approach for genome editing that enables precise, large-scale editing of genomes and construction of mutants in human cells. These are powerful data for inferring functional relationships among genes essential for cancer growth. Moreover, chemical-genetic CRISPR screens, where population of mutant cells are grown in the presence of chemical compounds, help us understand the effect the chemicals have on cancer cells and formulate precise drug solutions. Given the novelty of these experimental technologies, computational methods to process and interpret the resulting data and accurately quantify the various genetic interactions are still quite limited, and this is where Hassan’s dissertation is focused on. Her research extends to developing deep-learning based methods that leverage CRISPR chemical-genetic and other genomic datasets to predict cancer sensitivity to candidate drugs. Her methods on improving information content in CRISPR screens was published in the Molecular Systems Biology journal, a highly visible journal in the computational biology field. 

Hu's Ph.D. dissertation is concentrated on how to effectively leverage the power of artificial intelligence and machine learning (AI/ML) – especially deep learning – to tackle challenging and important problems in the design and development of reliable, effective and secure (independent) physical infrastructure networks. More specifically, her research focuses on two critical infrastructures: power grids and communication networks, in particular, emerging 5G networks, both of which not only play a critical role in our daily life but are also vital to the nation’s economic well-being and security. Due to the enormous complexity, diversity, and scale of these two infrastructures, traditional approaches based on (simplified) theoretical models and heuristics-based optimization are no longer sufficient in overcoming many technical challenges in the design and operations of these infrastructures: data-driven machine learning approaches have become increasingly essential. The key question now is: how does one leverage the power of AI/ML without abandoning the rich theory and practical expertise that have accumulated over the years? Hu’s research has pioneered a new paradigm – (domain) knowledge-guided machine learning (KGML) – in tackling challenging and important problems in power grid and communications (e.g., 5G) network infrastructures.

Lucas Kramer

Kramer is now the driving force in designing tools and techniques for building extensible programming languages, with the Minnesota Extensible Language Tools (MELT) group. These are languages that start with a host language such as C or Java, but can then be extended with new syntax (notations) and new semantics (e.g. error-checking analyses or optimizations) over that new syntax and the original host language syntax. One extension that Kramer created was to embed the domain-specific language Halide in MELT's extensible specification of C, called ableC. This extension allows programmers to specify how code working on multi-dimensional matrices is transformed and optimized to make efficient use of hardware. Another embeds the logic-programming language Prolog into ableC; yet another provides a form of nondeterministic parallelism useful in some algorithms that search for a solution in a structured, but very large, search space. The goal of his research is to make building language extensions such as these more practical for non-expert developers.  To this end he has made many significant contributions to the MELT group's Silver meta-language, making it easier for extension developers to correctly specify complex language features with minimal boilerplate. Kramer is the lead author of one journal and four conference papers on his work at the University of Minnesota, winning the distinguished paper award for his 2020 paper at the Software Language Engineering conference, "Strategic Tree Rewriting in Attribute Grammars".

Lin’s doctoral dissertation focuses on a timely, important topic of spatiotemporal prediction and forecasting using multimodal and multiscale data. Spatiotemporal prediction and forecasting are important scientific problems applicable to diverse phenomena, such as air quality, ambient noise, traffic conditions, and meteorology. Her work also couples the resulting prediction and forecasting with multimodal (e.g., satellite imagery, street-view photos, census records, and human mobility data) and multiscale geographic information (e.g., census records focusing on small tracts vs. neighborhood surveys) to characterize the natural and built environment, facilitating our understanding of the interactions between and within human social systems and the ecosystem. Her work has a wide-reaching impact across multiple domains such as smart cities, urban planning, policymaking, and public health.

Mingzhou Yang

Yang is developing a thesis in the broad area of spatial data mining for problems in transportation. His thesis has both societal and theoretical significance. Societally, climate change is a grand challenge due to the increasing severity and frequency of climate-related disasters such as wildfires, floods, droughts, etc. Thus, many nations are aiming at carbon neutrality (also called net zero) by mid-century to avert the worst impacts of global warming. Improving energy efficiency and reducing toxic emissions in transportation is important because transportation accounts for the vast majority of U.S. petroleum consumption as well as over a third of GHG emissions and over a hundred thousand U.S. deaths annually via air pollution. To accurately quantify the expected environmental cost of vehicles during real-world driving, Yang's thesis explores ways to incorporate physics in the neural network architecture complementing other methods of integration: feature incorporation, and regularization. This approach imposes stringent physical constraints on the neural network model, guaranteeing that its outputs are consistently in accordance with established physical laws for vehicles. Extensive experiments including ablation studies demonstrated the efficacy of incorporating physics into the model. 

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