Two PhD graduates from the University of Washington’s Paul G. Allen School of Computer Science & Engineering have had their dissertations recognized with prestigious Association for Computing Machinery (ACM) Doctoral Dissertation Awards.
The honors went to award winner Ashish Sharma, now a senior applied scientist at Microsoft, and honorable mention recipient Sewon Min, a research scientist at Seattle’s Allen Institute for AI (Ai2) and incoming faculty member at the University of California, Berkeley. Both students, working on advances in artificial intelligence, earned their doctoral degrees in 2024.
“This is an extremely rare situation,” Allen School Director Magdalena Balazinska told GeekWire. “For a university to have one of their students win this award is a once-in-a-decade type of event. Having two students recognized in the same year is truly outstanding. And both are AI-related, so very timely.”
ACM’s yearly awards recognize the best PhD dissertations in computer science. Longtime UW professor Ed Lazowska said there is usually a winner and one or two honorable mentions, and that in the U.S. alone there are more than 2,000 computer science PhD dissertations annually.
“We’ve had winners three times in the past, and honorable mentions four times,” Lazowska said. “That’s a superb record. But to have two in one year — the winner and one of two honorable mentions — is unprecedented. And both are in AI/ML/NLP, showing our leadership in that area.”
For his dissertation titled “Human-AI Collaboration to Support Mental Health and Well-Being,” Sharma devised ways to address a fundamental challenge in health care by leveraging AI to make high-quality mental health support available to more people.
“Augmenting mental health interventions with AI and NLP-based methods has the potential to provide scaffolding that could make quality mental health care accessible to all,” Sharma said in an Allen School blog post. “By carefully designing human-AI collaboration that is grounded in psychology expertise to truly understand the complexities of mental health, human behavior and user needs, and is rigorously tested for safety and effectiveness, we can empower both those seeking help and those providing it.”
Sharma worked with professor Tim Althoff in the Allen School’s Behavioral Data Science Group.
He previously received one of two William Chan Memorial Dissertation Awards, recognizing dissertations of exceptional merit, as well as a JP Morgan AI Ph.D. Fellowship.
In her dissertation titled “Rethinking Data Use in Large Language Models,” Min addressed fundamental challenges in natural language processing by developing a new class of language models and alternative approaches for how such models are trained.
“My research established the foundations of nonparametric models, and also opened up new avenues for responsible data use, such as enabling data opt-out and credit assignment to data creators,” said Min, who worked in the UW NLP Group with professors Hanna Hajishirzi (a senior director at Ai2) and Luke Zettlemoyer (a research director at Meta).
Prior to the ACM honor, Min also earned a William Chan Memorial Dissertation Award from the Allen School, as well as the 2024 Western Association of Graduate Schools (WAGS) ProQuest Innovation in Technology Award, which recognizes research that introduces innovative technology as a creative solution to a major problem. During her time at the Allen School, Min received a JP Morgan Ph.D. Fellowship in AI and was also named a 2022 EECS Rising Star.
The other ACM honorable mention award went to Alexander (Zander) Kelley for his dissertation “Explicit Pseudorandom Distributions for Restricted Models of Computation” toward a PhD earned at the University of Illinois Urbana-Champaign.
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