sigchi dissertation award

ACM Special Interest Group on Computer-Human Interaction

Outstanding Dissertation Award | ACM SIGCHI

Sigchi outstanding dissertation award.

We are excited to announce the SIGCHI Outstanding Dissertation Award, which will recognize the most outstanding research contributions from recently graduated PhD students within the HCI community, showcasing the quality and impact of HCI research.

Important Dates

Submission Deadline:  December 15, 2022 Awards Announced: February 14, 2023

Eligibility

• Eligible dissertations must have been successfully completed between September 1, 2021 and August 31, 2022 . An award date that is appropriate to the candidate’s institution is acceptable, for example graduation date, examination date, or final thesis acceptance date. 
• Candidates will only be eligible to submit once for this award.
• The candidate must be a SIGCHI member.
• Only dissertations written in English will be considered. If a dissertation originally was written in another language, a translation into English is acceptable and can be considered.
• The candidate must have published at least one paper in a “paper venue” (e.g., a full paper or a note) of any length (but not an abstract to support a workshop or other non-paper venue) at a SIGCHI Sponsored or Co-Sponsored conference (see https://new.sigchi.org/conferences/upcoming-conferences/ ) or an ACM-sponsored HCI journal.
• Each nominated dissertation must be on a topic relevant to HCI. The determination of whether a dissertation is within scope for the award will be made by the SIGCHI Outstanding Dissertation Award Committee. A dissertation can be nominated for both the SIGCHI Outstanding Dissertation Award and the ACM Doctoral Dissertation Award.
• Only one nomination may be submitted per department.

Preparing and Submitting

All nomination materials must be submitted by the submission deadline to this online form . Submissions must be submitted in English. PDF format is preferred for textual materials. Supplementary materials must be multi-platform. Late submissions will not be considered.

Nomination for the award must include:

• English language copy of dissertation.
• Statement from an advisor limited to 2 pages addressing why the candidate’s dissertation should receive this award. This should address the significance of the dissertation, not simply repeat the information in the abstract. Nomination must come from the advisor; self-nomination is not allowed.
• One letter of support limited to 2 pages. The supporting letter should be from an expert 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.) If a letter-writer is supporting more than one nomination, they may be asked to rank those nominations.
• List of publications contributing to the dissertation.
• SIGCHI membership number for candidate.
• Suggested citation if the candidate is selected. This should be a concise statement (maximum of 50 words) describing the key technical contribution for which the candidate merits this award. Note that the final wording for awardees will be at the discretion of the SIGCHI Outstanding Dissertation Award Committee.

Doctoral Award Review Process

Each submission will be reviewed by a panel of experts selected by the SIGCHI Executive Committee to evaluate the quality, contribution, and impact as demonstrated by the submitted thesis and supplementary materials.  

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Karan Ahuja Wins ACM SIGCHI Outstanding Dissertation Award

The dissertation advances the state of the art in high-fidelity user tracking and digitization and opens new paradigms in augmented and virtual reality, health sensing, and natural user interfaces.

Northwestern Engineering’s Karan Ahuja earned a 2024 Association for Computing Machinery (ACM) Special Interest Group on Computer-Human Interaction (SIGCHI) Outstanding Dissertation Award , which recognizes excellent dissertation research in human-computer interaction (HCI).

Evaluated on technical depth, significance of the research contribution, potential impact on the field, and quality of presentation, the SIGCHI Outstanding Dissertation Award is given annually to up to five recent doctorate recipients worldwide.

This August, Ahuja will join the Department of Computer Science as a Lisa Wissner-Slivka and Benjamin Slivka Assistant Professor in Computer Science and director of the Sensing, Perception and Interactive Computing Exploration (SPICE) Lab. He is currently a visiting faculty researcher at Google, leading efforts on Google XR.

Ahuja’s dissertation, titled “ Practical and Rich User Digitization ,” advances the state of the art in high-fidelity user tracking and digitization and opens new paradigms in augmented and virtual reality, health sensing, and natural user interfaces.

Ahuja’s research addresses the challenge of understanding and interpreting human behavior and actions in everyday environments.

“The existing spectrum of technology for this purpose is polarized: on one end, mobile and pervasive consumer devices estimate coarse metrics like step counts and sedentariness, but fall short in comprehensively understanding complex human behaviors,” Ahuja said. “On the other end, detailed professional digitization systems, such as motion capture suits and multi-camera rigs, are impractical for everyday use due to their high costs, privacy concerns, and need for specialized lab settings.”

Ahuja’s research transforms and democratizes this space by harnessing the diverse sensors in consumer devices like smartphones and smartwatches. He repurposed alternative minimally invasive and privacy-aware sensing approaches — including doppler, capacitive, lo-fi audio loudness sensors, and inertial measurement units — to enable full-body user digitization and estimate body pose, activities, and behavioral patterns.

“The eminently practical techniques promise a revolution in areas as diverse as wellness monitoring, rehabilitation, chronic condition management, clinical movement research, eldercare support, and embodied telepresence,” said the SIGCHI Awards Committee. “Expect to see these techniques on your devices soon.”

Many of Ahuja’s research projects have been open-sourced, deployed in-the-wild, licensed by tech companies, and shipped as a product feature. Notably, his activity recognition research has been licensed for commercialization by Fortune 500 companies. In addition, his work on classroom sensing with the EduSense team has been adopted in more than 45 classrooms across various universities, enhancing teaching productivity and contributing valuable pedagogical insights.

Ahuja’s studies on tracking arm motion to estimate hyperactivity as an ADHD biomarker have led to innovative approaches for early screening and diagnosis, including two research trials with the University of Pittsburgh Medical Center. Also in the healthcare sphere, Ahuja’s novel approach to human activity recognition, called Vid2Doppler, demonstrated potential application for safety and fall-detection in home healthcare settings.

More recently, Ahuja’s research focuses on end-to-end systems for human sensing and tracking, followed by long-term behavioral understanding, ultimately closing the loop towards solving human augmentation.

Ahuja earned a PhD in HCI from Carnegie Mellon University in 2023, co-advised by Chris Harrison and Mayank Goel.

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Department of Civil, Construction, and Environmental Engineering

Recent ccee graduate recognized with two dissertation awards.

Luo was also selected as the honorable mention for the Paul V. Roberts/Association of Environmental Engineering and Science Professors (AEESP) Outstanding Doctoral Dissertation Award for her dissertation, “Integration of power systems and air quality models to mitigate negative health and climate impacts of electricity generation.” This prestigious fully endowed award is given annually to recognize a rigorous and innovative doctoral thesis that advances the science and practice of water quality engineering for either engineered or natural systems and also recognizes research that supports underserved communities, environmental awareness, or sustainable solutions. She will be recognized during the annual AEESP Awards Presentation on June 18. 

Luo was advised by Associate Professors Jeremiah Johnson and Fernando Garcia Menendez and is currently a postdoctoral researcher at Princeton University. Her dissertation tackles the challenge of mitigating greenhouse gas emissions within the power sector, with a particular emphasis on air pollution, public health and justice implications associated with power plant emissions. Her current research involves developing and using energy system modeling tools to better understand how energy-related policies/regulations impact the energy system, human health, and climate.

“I felt very honored to receive these recognitions and also excited to know that I got both awards at the same time,” Luo said. “ I am extremely grateful to my advisors for providing me the opportunity to learn and explore this topic and supporting me from all perspectives.”

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Council of Graduate Schools (CGS)/ProQuest Distinguished Dissertation Award

The College of Arts and Sciences is seeking nominations for the  2024 Council of Graduate Schools (CGS)/ProQuest Distinguished Dissertation Award . Full details about the award can be found on the  CGS website . The fields for this year’s awards are:  1) Mathematics, Physical Sciences, and Engineering  and 2) Social Sciences . In each category, only one institutional nominee can be selected.  We will use the following timeline/process:

• Submit nomination materials electronically to Dr. Brian Orefice ( [email protected] ), Assistant Dean, Graduate Studies.
• ASC nominations will be competing with nominations from other colleges in each category, so the Graduate School will identify the institutional nominee. 
• Nominees must have had their doctoral degree awarded between July 1, 2022 and June 30, 2024.
• An abstract of the nominee’s dissertation (not to exceed 5 double-spaced pages).  Appendices containing other material, such as charts, tables, and/or references may be included as additional pages. All pages should be numbered, and each should bear the name of the nominee.
• Three letters of recommendation letter evaluating the significance and quality of the nominee’s dissertation work. One letter is to be from the nominee’s dissertation supervisor, another from a member of the nominee’s dissertation committee, and the third from a person of the nominee’s choice.
• The nominee’s curriculum vitae (not to exceed five pages).
• Monday, June 24 – Nominations due from College of Arts and Sciences to the Graduate School
• Wednesday, July 3 – Graduate School submits materials to CGS

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This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

This project has investigated long-term disaster recovery following Hurricane Katrina on the Mississippi Gulf Coast in order to better understand how survivors define the ultimate success of recovery efforts in their communities.  The study examined recovery in two ways: qualitatively and quantitatively.  Ninety-seven survivors diverse in their age, gender, race, ethnicity, occupation, and income level participated in interviews after the hurricane.  Thirty-four of these participants also documented recovery activities in their communities through photography and/or mapping.  These data were analyzed for similarities and differences among and between demographic groups.  A survivor’s view of success is of interest to local governments, urban planners, emergency managers, and disaster scholars who monitor the rebound of communities after a disaster and often use construction and population statistics as measures for defining success.  It is important to determine how effectively these statistics can approximate recovery progress and success as defined by affected residents themselves.  Hence, this study also compared spatial patterns in these metrics against survivors’ maps of community recovery.

Hurricane Katrina’s recovery presented a rare opportunity to derive new conceptual knowledge on long-term place recovery by observing the process underway eight to nine years after the large-scale catastrophe.  This study applied the geographic concept of place in three distinct ways to study disaster recovery: first, as a space that forms identity and shapes the community fabric, second, as a built environment that serves functional needs, and third, as an areal unit for statistical aggregation and comparison. In doing so, this research answered the National Research Council’s (2006) call to examine the complex recovery processes that occur across social groups and geographic scales following disaster, further advancing our scientific understanding of these processes.

The study found that recovery held six distinct meanings for affected residents: commemoration, betterment, sensory experience, materiality, adjustments to activity space, and changing functions of spaces.  These meanings varied in their importance and in their opposition with one other over the recovery period.  During the early stages of recovery, commemoration activities centered on replacing lost infrastructure exactly as it was pre-disaster, while in the long-term, the recovery of the pre-disaster sense of place became the primary focus.  Such long-term commemoration activities were found to oppose solutions aimed at sustainable development from the ground up.  Tensions between these two meanings tangibly altered the resilience of the rebuilt community infrastructure against future disasters.  They also influenced citizen satisfaction (or dissatisfaction) toward local governments’ recovery efforts.

Results showed more commonalities than differences between residents’ recovery meanings across socio-demographic groups (e.g., gender, race, and ethnicity).  Instead, differences emerged based on levels of place attachment, life stage, degree of mobility (both physical and social), and international immigration experience.  Recovery landmarks identified through mapping strongly mirrored each resident’s mobility patterns.  This link between residents’ perceptions of community recovery and mobility is absent from current recovery theory.  Spatial patterns of recovery identified in residents’ maps matched spatial patterns of home reconstruction, population return, and home repair, lending validity to the use of these metrics by local and state governments to assess recovery progress at a sub-county level.

The centrality of restoring function to...

Please report errors in award information by writing to: [email protected] .