2026
CAM PHD DISSERTATION DEFENSE: YIFAN PENG
4:00–5:00 pm Jones 111
Wednesday, April 22 2026, at 4:00 PM (Central Daylight Time), Location: Jones 111, 5747 S. Ellis Ave.
Dissertation Presentation and Defense
YIFAN PENG, Computational and Applied Mathematics, University of Chicago
“FAST NUMERICAL LINEAR ALGEBRA FOR GENERATIVE MODELING”
Topics
CAM & Stats Student Seminar: Anna Asch
12:30–1:30 pm DSI 103
Wednesday, April 22, 2026, at 12:30 PM (Central Daylight Time), Data Science Institute, 5460 S University Ave, Room 103
ANNA ASCH, Computational and Applied Mathematics, University of Chicago
“Improving the calibration of probabilistic weather forecasts with conformal prediction”
Topics
CAM Colloquium: Qiang Du
4:00–5:00 pm Jones 303
THURSDAY, APRIL 16, 2026, at 4:00 PM, in Jones 303, 5747 South Ellis Avenue
QIANG DU, Applied Physics and Applied Mathematics, and Data Science Institute, Columbia University
“Integral equation models with nonlocal operators: applications and recent developments”
Topics
CAM PHD DISSERTATION DEFENSE: SUZANNA PARKINSON
9:00–10:00 am Data Science Institute, Room 105 (Also via Zoom)
Thursday, April 16, 2026, at 9:00 AM (Central Daylight Time), Data Science Institute at 5460 S University Ave Room 105 (Also via Zoom)
Dissertation Presentation and Defense
SUZANNA PARKINSON, Computational and Applied Mathematics, University of Chicago
“On the Role of Depth in Deep Learning”
Topics
CAM & Stats Student Seminar: Jacob Linden
12:30–1:30 pm DSI 103
Wednesday, April 15, 2026, at 12:30 PM (Central Daylight Time), Data Science Institute, 5460 S University Ave, Room 103
JACOB LINDEN, Computational and Applied Mathematics, University of Chicago
“Acoustic Boundary Layers: A Boundary Integral Formulation”
Topics
CAM PHD DISSERTATION DEFENSE: NATHAN WANIOREK
12:00–2:00 pm Jones 111
Wednesday, April 15, 2026, at 12:00 PM (Central Daylight Time), Location: Jones 111, 5747 S. Ellis Ave.
Dissertation Presentation and Defense
NATHAN WANIOREK, Computational and Applied Mathematics, University of Chicago
“High-Dimensional Analysis of Ensemble Kalman Filters and Hierarchical Bayesian Inverse Problems”
Topics
CAM PHD DISSERTATION DEFENSE: ADELA DEPAVIA
1:00–3:00 pm Data Science Institute, 5460 S University Ave, Room 105
Monday, April 13, 2026, at 1:00 PM (Central Daylight Time), Location: Data Science Institute, 5460 S University Ave, Room 105
Dissertation Presentation and Defense
ADELA DEPAVIA, Computational and Applied Mathematics, University of Chicago
“Leveraging Structure for Learning and Optimization”
Topics
CAM PHD DISSERTATION DEFENSE: RUITING LIANG
3:00–5:00 pm Jones 111
Friday, April 10, 2026, at 3:00 PM (Central Daylight Time), Location: Jones 111, 5747 S. Ellis Ave.
Dissertation Presentation and Defense
RUITING LIANG, Computational and Applied Mathematics, University of Chicago
“Assumption-lean uncertainty quantification through exchangeability and algorithmic stability”
Topics
Distinguished Speaker Series: Jon Kleinberg
12:00–1:30 pm Data Science Institute
The University of Chicago Data Science Institute, Department of Statistics, Department of Computer Science, and Committee on Computational and Applied Mathematics are proud to announce our 2025-26 Distinguished Speaker Series. Join us for stimulating talks from leading data science and AI researchers exploring and expanding the fundamental methods and applications that transform large and complex datasets into knowledge and action.
Title: Formal Models of Language Generation
Abstract: The emergence of large language models has prompted a surge of interest into theoretical models that might give us insight into both their successes and their shortcomings. We’ll give an overview of recent work in this direction, focusing on a surprising line of positive results that shows it is possible to give guarantees for language-generation algorithms even in the absence of any probabilistic assumptions, in a framework known as “language generation in the limit”. These results suggest interesting notions of “breadth” in language generation, attempting to formalize the idea that different algorithms for this problem might all meet the specification but differ significantly in their expressiveness — in how “richly” they can generate from the underlying language. We also discuss strong contrasts with classical results on language identification, showing a strong sense in which language generation and language learning are fundamentally different as computational problems. The talk will be based on joint work with Sendhil Mullainathan and Fan Wei.
Bio: Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on the interaction of algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. He is a member of the National Academy of Sciences, the National Academy of Engineering, the American Academy of Arts and Sciences, and the American Philosophical Society, and he has served on advisory groups including the National AI Advisory Committee (NAIAC) and the National Research Council’s Computer Science and Telecommunications Board (CSTB) and Committee on Science, Technology, and Law (CSTL). He has received MacArthur, Packard, Simons, Sloan, and Vannevar Bush research fellowships, as well as awards including the the Nevanlinna Prize, the World Laureates Association Prize, the ACM/AAAI Allen Newell Award, and the ACM Prize in Computing.
Topics
Statistics, DSI, CAM
CAM PHD DISSERTATION DEFENSE: RONG JIANG
9:30–11:30 am Jones 111
Friday, April 10, 2026, at 9:30 AM (Central Daylight Time), Location: Jones 111, 5747 S. Ellis Ave.
Dissertation Presentation and Defense
RONG JIANG, Computational and Applied Mathematics, University of Chicago
“Nonparametric Statistics Meets Sequential Decision-Making: Minimax Optimality And Adaptivity”