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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Mar12
EVENT DETAILS
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Speaker: David KrasowskaTitle: Architecting Task-Based Execution Across GPU Clusters and PIM Architectures
Abstract: Writing parallel and distributed programs is notoriously difficult. This talk explores how task-based programming frameworks can reduce this burden across increasingly heterogeneous and distributed hardware. First, I present cuNumeric.jl and Legate.jl, which transparently scale idiomatic Julia array workloads across CPUs and GPUs. Second, I shift focus to extending task-based programming models to emerging Processing-in-Memory (PIM) architectures. I introduce libvectordpu, a high-performance tasking model for direct DPU programming, and Legion-PIM, which integrates DPUs into the core Legion programming system. Ultimately, moving computation near memory requires more than just a new backend– it fundamentally reshapes our assumptions about task granularity, data partitioning, and locality.
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What is CSPAC?
We are the CS PhD Advisory Council. We are a PhD student-led organization, and our mandate is to interface between PhD students and faculty on academic issues. We want to advocate for PhD students in the department, so if there is some way we can support you, please come talk to us. We welcome PhD students to our weekly meetings on Tuesdays, 4:00-5:00pm in Mudd 3501 and on zoom. We also welcome anonymous concerns/feedback at any time via this form. Anyone in the community can reach us at cspac@u.northwestern.edu.TIME Thursday, March 12, 2026 at 12:00 PM - 1:00 PM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT CSPAC cspac@u.northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Apr6
EVENT DETAILS
lessFrom Data to Design: Rethinking
Engineering Design With Next-Gen AIBIO
Faez Ahmed is an Associate Professor of Mechanical Engineering at MIT, where he leads the DeCoDE Lab. His research focuses on AI for engineering design, including deep generative models, multimodal representations, and human–AI collaboration. His work has been recognized with the NSF CAREER Award, ASME DAC and DTM Young Investigator Awards, the Google Research Scholar Award, and the Amazon Research Award. He serves as an Associate Editor for Computer-Aided Design and Design Science.
ABSTRACT
Generative AI is transforming how we create, customize, and accelerate digital content. Yet applying these tools to engineering design introduces unique challenges, from maintaining precision under evolving requirements to working effectively in data-scarce environments and interpreting designer intent. In this talk, I will discuss these challenges and show how emerging engineering-focused foundation models are beginning to address them, reshaping workflows in areas such as vehicle design, CAD automation, and design optimization. I will highlight new opportunities enabled by generative AI that integrates multimodal data with engineering analysis and optimization, and present examples of AI-driven design co-pilots for engineering tasks. The talk will conclude with a perspective on how AI enables us to broaden design democratization, accelerate innovation cycles, and fundamentally reshape the role of engineers.
TIME Monday, April 6, 2026 at 3:00 PM - 4:00 PM
LOCATION 1-350, Ford Motor Company Engineering Design Center map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)
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Apr13
EVENT DETAILS
lessMonday / CS Seminar
April 13 / 12:00 PM
Hybrid / Mudd 3514Speaker
Arindam BanerjeeTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Monday, April 13, 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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Apr22
EVENT DETAILS
lessWednesday / CS Seminar
April 22 / 12:00 PM
Hybrid / Mudd 3514Speaker
Lev Reyzin, University of Illinois ChicagoTalk Title
On the Hardness of Learning Regular ExpressionsAbstract
"Despite the theoretical significance and wide practical use of regular expressions, the computational complexity of learning them has been largely unexplored. We study the computational hardness of improperly learning regular expressions in the PAC model and with membership queries. We show that PAC learning is hard even under the uniform distribution on the hypercube, and also prove hardness of distribution-free learning with membership queries. Furthermore, if regular expressions are extended with complement or intersection, we establish hardness of learning with membership queries even under the uniform distribution. We emphasize that these results do not follow from existing hardness results for learning DFAs or NFAs, since the descriptive complexity of regular languages can differ exponentially between DFAs, NFAs, and regular expressions.
This work is joint with Idan Attias, Nati Srebro, and Gal Vardi"
Biography
Lev Reyzin is a Professor of Mathematics, Statistics, and Computer Science at the University of Illinois Chicago and Co-Director of the IDEAL Institute. He works on the theory of machine learning, data science, and artificial intelligence. Prior to UIC, Reyzin was a Simons Postdoctoral Fellow at Georgia Tech and an NSF Computing Innovation Fellow at Yahoo! Research. Reyzin received his Ph.D. on an NSF doctoral fellowship from Yale under Dana Angluin and his bachelor’s degree from Princeton. He is currently the Chair of the Steering Committee for the ALT conference and the Editor-in-Chief of Mathematics of Data, Learning, and Intelligence. He has also served as a General Chair for FOCS 2024, the Program Chair for ISAIM 2020, and a Program Chair for ALT 2017. His work has earned awards at ICML, COLT, and AISTATS and has received extensive funding.Research Areas/Interests: theory of machine learning, data science, and artificial intelligence
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Zoom Link
Panopto LinkTIME Wednesday, April 22, 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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Apr27
EVENT DETAILS
lessMonday / CS Seminar
April 27 / 12:00 PM
Hybrid / Mudd 3514Speaker
Tushar ChandraTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Monday, April 27, 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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Apr29
EVENT DETAILS
lessWednesday / CS Seminar
April 29 / 12:00 PM
Hybrid / Mudd 3514Speaker
Bill FeffermanTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Wednesday, April 29, 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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May4
EVENT DETAILS
lessMonday / CS Seminar
May 4 / 12:00 PM
Hybrid / Mudd 3514Speaker
Moon DuchinTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Monday, May 4, 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)