Two Ph.D. Students Honored with Larry S. Davis Doctoral Dissertation Awards
The Department of Computer Science at the University of Maryland announced its winners of the Larry S. Davis Doctoral Dissertation Award for 2023-24, an annual honor distinguishing the department's two outstanding doctoral dissertations. This year's recipients are Marina Knittel, who plans to graduate this semester and begin a postdoctoral fellowship at UC San Diego in January, and Alexander Levine (Ph.D. '23, computer science), currently a postdoctoral fellow at the University of Texas at Austin.
The award highlights exceptional dissertations noted for their technical depth, significance, potential for impact and presentation quality.
"Whenever you are recognized with such an award, it signifies that others agree that your research is important, and it motivates you to work harder and achieve even greater things," Knittel said. "My goal is to conduct mathematically interesting work on graph algorithms that is always grounded by its practical implications in the real world, which I do in a few ways. First, I study fairness and partake in discussions regarding ethical methodologies to conduct fair algorithmic research. Second, I study scalable graph algorithms—as in, graph algorithms on systems that can efficiently handle massive inputs. This is necessary for algorithms to continue keeping pace with the continual growth of input datasets and user expectations."
Beyond the distinction of the award itself, recipients receive a cash prize of $500. The Department also traditionally nominates the selected dissertations for the ACM Doctoral Dissertation Award.
"Marina is exceptional. Not only is she a profound thinker, but she's also a skilled writer,” said Mohammad Hajiaghayi, the Jack and Rita G. Minker Professor of Computer Science and Knittel’s advisor. “She conducts her research with great independence, focusing on big data algorithms. Specifically, she delves into the significant areas of large data sets, emphasizing fair and diverse algorithms and clustering—a crucial topic in today's AI landscape."
The award motivates Levine to further his innovative research in ways that will continue to make a sizable impact.
"My dissertation work was mostly focused on developing machine learning techniques that are guaranteed to be robust to small changes in their inputs, even in the worst case of adversarially distorted inputs," Levine shared. "By providing robustness guarantees for machine learning systems, we can allow these systems to be used more confidently in safety-critical applications. I am honored that my work has been recognized by this award, and am deeply thankful for all of the support I received during my time at UMD from my advisor, my dissertation committee, and the rest of the UMD CS community."
Levine's advisor, Associate Professor Soheil Feizi, is confident in the future impact of his research.
"Alex's thesis addresses key challenges in provably robust learning, offering vital insights into AI model sensitivities against adversarial attacks and suggesting proven solutions,” Feizi said. “He's been outstanding in our department. His passion and sharp intellect stand out, and the depth and impact of his work, even among top Ph.D. students, is truly exceptional."
Named in honor of Computer Science Professor Emeritus Larry Davis, the award celebrates his significant contributions to computer science. Davis served as chair of the Department of Computer Science from 1999 to 2012. He also served as director of the University of Maryland Institute for Advanced Computer Studies from 1985 to 1994. An IEEE Fellow since 1997, Davis's research legacy includes groundbreaking work in computer vision and high-performance computing, with over 300 publications.
Story by Samuel Malede Zewdu, CS Communications
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