News & EventsDepartment Events & Announcements
Events
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Oct15
EVENT DETAILS
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Wednesday / CS Seminar
October 15th / 12:00 PM
Hybrid / Mudd 3514Speaker
Jason Hartline, Northwestern UniversityTalk Title
Scoring Rules for a Theory of AIAbstract
Scoring rules are foundational in decision theory and, therefore, are foundational for a developing theory of artificial intelligence. Just as simple models from decision theory provide context for understanding the decisions of complex humans, so too can they for complex AI systems. Bayesian decision theory considers an agent receiving a signal that is correlated with the state, choosing an action, and obtaining a payoff that depends on both the state and action. With Bayesian updating and the revelation principle, the signal becomes a posterior belief and the decision problem becomes a scoring rule. Given a scoring rule, baseline performance is the optimal score under the prior; benchmark performance is the optimal score under the posterior; and the optimal scoring rule — framed as a mechanism design problem — maximizes the difference between them. The talk reviews this theory and applies it to evaluate the value of information, the losses from predictive models, and the accuracy of human and AI decision makers.Biography
"Prof. Hartline’s research introduces design and analysis methodologies from computer science to understand and improve outcomes of economic, legal, and AI systems. Optimal behavior and outcomes in complex environments are complex and, therefore, should not be expected; instead, the theory of approximation can show that simple and natural behaviors are approximately optimal in complex environments. This approach is applied to auction theory and mechanism design in his graduate textbook Mechanism Design and Approximation which is under preparation.
Prof. Hartline received his Ph.D. in 2003 from the University of Washington under the supervision of Anna Karlin. He was a postdoctoral fellow at Carnegie Mellon University under the supervision of Avrim Blum; and subsequently a researcher at Microsoft Research in Silicon Valley. He joined Northwestern University in 2008 where he is a professor of computer science. He was on sabbatical at Harvard University in the Economics Department during the 2014 calendar year and visiting Microsoft Research, New England for the Spring of 2015. He was on sabbatical at Stanford University for the 2023-2024 academic year.
Prof. Hartline is the director of Northwestern’s Online Markets Lab, he was a founding codirector of the Institute for Data, Econometrics, Algorithms, and Learning from 2019-2022, and is a cofounder of virtual conference organizing platform Virtual Chair."
TIME Wednesday, October 15, 2025 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov10
EVENT DETAILS
lessMonday / CS Seminar
November 10th / 12:00 PM
Hybrid / Mudd 3514Speaker
Aravindan Vijayaraghavan, Northwestern UniversityTalk Title
Toward a Modern Theory of Algorithms in the Machine Learning EraAbstract
The remarkable empirical successes of machine learning have revealed the power of computational techniques in several domains and scientific disciplines. Yet there is a striking disconnect in the algorithmic foundations of machine learning: many basic computational problems, ranging from classification and clustering to deep learning, reduce to non-convex optimization tasks that are computationally intractable in the worst case. Yet, in practice, heuristics often succeed in producing high-quality solutions, fueling the remarkable progress of modern AI. At the same time, the absence of rigorous guarantees raises the following question: when, and under what conditions, can we reliably use predictions of machine learning models?
In the first part of the talk, I will describe theoretical frameworks like smoothed analysis that go beyond worst-case analysis to better reason about algorithms on typical instances, and help obtain rigorous polynomial time guarantees for challenging algorithmic problems in ML and high-dimensional data analysis. In the second part of the talk, I will present recent principled approaches that treat machine learning models as powerful black boxes that are potentially unreliable or biased, and show how to design algorithms that can rigorously quantify and account for their uncertainty.
Biography
Aravindan Vijayaraghavan is an Associate Professor at Northwestern University in the department of Computer Science, and (by courtesy) Industrial Engineering and Management Sciences. He is also the co-director of the NSF Institute for Data, Econometrics, Algorithms and Learning (IDEAL). His research interests are broadly in algorithms and foundations of data science and machine learning.---
CSPAC Community Connections: Resumé Bias
Zoom Link
Panopto LinkTIME Monday, November 10, 2025 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov14
EVENT DETAILS
lessThis one-day workshop, which is part of the Fall 2025 IDEAL Special Program on High Dimensional and Complex Data Analysis, will explore the interplay between metric embeddings, high-dimensional geometry, and algorithmic problems in data science and theoretical computer science. Topics include geometric and probabilistic methods for understanding metric spaces, embeddings with low distortion, and the implications of high-dimensional phenomena for efficient computation and data representation. The workshop will bring together researchers from mathematics, computer science, and related areas to foster exchange across these connected fields.
TIME Friday, November 14, 2025
LOCATION Mudd Library, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Indira Munoz indira.munoz@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov17
EVENT DETAILS
lessMonday / CS Seminar
November 17th/ 12:00 PM
Hybrid / Mudd 3514Speaker
Shaddin Dughmi, USCTalk Title
A Combinatorial Lens on Supervised LearningAbstract
I will describe some recent joint results on the theory of supervised learning which follow from surprising connections to combinatorial optimization. Most notably, by connecting learning to bipartite matching on infinite graphs we derive several algorithmic and structural characterizations of learning which hold somewhat broadly.Biography
"Shaddin Dughmi is an Associate Professor in the Department of Computer Science at USC and the Neild visiting professor at Northwestern University. He received a B.S. in computer science, summa cum laude, from Cornell University in 2004, and a Ph.D. in computer science from Stanford University in 2011. He is a recipient of the NSF CAREER award, the Arthur L. Samuel best doctoral thesis award, and the ACM EC best student paper award.
Shaddin is broadly interested in questions that stimulate the development of new algorithmic techniques, and shed insight on the power and limitations of algorithms. Work in his group has investigated such questions in a variety of domains: game theory, mechanism design, multi-agent systems, persuasion and information design, delegation and contract theory, decision making subject to online or stochastic uncertainty, and the theory of machine learning."---
CSPAC Community Connections:
Zoom Link
Panopto LinkTIME Monday, November 17, 2025 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov19
EVENT DETAILS
lessWednesday / CS Seminar
November 19 / 12:00 PM
Hybrid / Mudd 3514Speaker
Robert Rand, University of ChicagoTalk Title
Quantum Programming in QunityAbstract
Qunity is a high-level functional language for writing quantum programs in the style of OCaml or Haskell. Qunity treats classical and quantum data equivalently, allowing us to run the same programs on classical data and quantum superpositions. It takes key concepts from classical programming, like pattern matching, try-catch blocks, and data duplication and lifts them to the quantum setting. In this talk, I will describe Qunity, along with recent extensions that enable easier classical and pure quantum programming, and its compiler to quantum circuits.Biography
Robert Rand is an Assistant Professor of Computer Science at the University of Chicago. His research focuses on programming languages and verification for quantum computing and his main projects include the Qunity quantum programming language, the BellKAT DSL for quantum networking, and VyZX, a verified ZX calculus library. He also works on a range of verification projects, from adding automation to the Rocq proof assistant to developing quantum program logics. Robert developed and maintains the INQWIRE QuantumLib, an open-source library for verified quantum computing in Rocq, which underlies many of his projects including his online textbook, Verified Quantum Computing.TIME Wednesday, November 19, 2025 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Nov20
EVENT DETAILS
lessCS Community! Join us for our monthly free bagels and coffee while mingling with fellow faculty and students.
TIME Thursday, November 20, 2025 at 9:00 AM - 11:00 AM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Dec13
EVENT DETAILS
lessThe ceremony will take place on Saturday, December 13 in Pick-Staiger Concert Hall, 50 Arts Circle Drive.
TIME Saturday, December 13, 2025 at 4:00 PM - 6:00 PM
LOCATION Pick-Staiger Concert Hall map it
CONTACT Andi Joppie andi.joppie@northwestern.edu EMAIL
CALENDAR McCormick School of Engineering and Applied Science
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Jan5
EVENT DETAILS
lessMonday / CS Seminar
January 5 / 12:00 PM
Hybrid / Mudd 3514Speaker
Ari HoltzmanTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Monday, January 5, 2026 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Jan12
EVENT DETAILS
lessMonday / CS Seminar
January 12 / 12:00 PM
Hybrid / Mudd 3514Speaker
Rana Hanocka, UChicagoTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Monday, January 12, 2026 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Jan28
EVENT DETAILS
lessTBA
TIME Wednesday, January 28, 2026 at 4:00 PM - 5:00 PM
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Jan29
EVENT DETAILS
lessCS Community! Join us for our monthly free bagels and coffee while mingling with fellow faculty and students.
TIME Thursday, January 29, 2026 at 9:00 AM - 11:00 AM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)