News & EventsDepartment Events & Announcements
Events
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Feb23
EVENT DETAILS
lessMonday / CS Seminar
February 23 / 12:00 PM
Hybrid / Mudd 3514Speaker
Xiaorui Sun, UICTalk Title
Toward Faster Algebraic Computation: An Isomorphism PerspectiveAbstract
"Over the past few decades, linear-algebraic techniques played a central role in the design of faster algorithms, with notable successes in many graph algorithms such as maximum flow and shortest paths. However, for many problems that are not yet known to admit polynomial-time algorithms—such as integer factoring and various isomorphism problems—linear methods alone are often insufficient. In these settings, more general nonlinear algebraic structures, including groups, rings, and modules, naturally arise. Achieving further algorithmic progress requires a deeper understanding of these algebraic objects.
In this talk, I will discuss how algebraic representations have become essential to recent advances in isomorphism problems. I will highlight connections among several central isomorphism problems and survey the techniques that have led to more efficient algorithms. I will conclude by discussing open challenges and outlining promising directions for future research."
Biography
Xiaorui Sun is an Associate Professor of Computer Science at the University of Illinois Chicago. His research interests lie in theoretical computer science, with an emphasis on the intersection of algorithms and algebraic computation. After earning his PhD from Columbia University, he worked at Simons Institute for the Theory of Computing and Microsoft Research. He is a recipient of the NSF CAREER Award, and his work have been featured in Communications of the ACM and Quanta Magazine.Research Interests: theoretical computer science, algorithms, and algebraic computation
TIME Monday, February 23, 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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Feb25
EVENT DETAILS
lessWednesday / CS Seminar
February 25 / 12:00 PM
Hybrid / Mudd 3514Speaker
Austin Mordahl, UICTalk Title
Challenges of Modern Static Analysis: Configuration, Flakiness and TestingAbstract
"Static analysis tools are essential for catching bugs early in software development, yet decades of research have failed to overcome fundamental barriers to their adoption: complicated configuration, high false positive rates, and failure to detect real bugs. Despite the proliferation of sophisticated tools for determining program properties and advances in underlying techniques, these challenges continue to hinder widespread adoption and effective use in practice. In this talk, we will explore solutions to three persistent problems that plague modern static analysis: configuration complexity, flakiness, and testing. First, we'll examine approaches to reducing the steep learning curves around tool configuration, making it easier for developers to deploy static analyzers in their projects. Second, we'll investigate techniques for addressing flakiness: when analysis tools produce different results on identical code, undermining developer trust in their results. Finally, we'll discuss methods for testing static analysis tools themselves: validating that tools correctly determine the program properties they claim to compute.
Throughout the talk, we'll also examine how large language models are reshaping approaches to each of these challenges and consider their potential to fundamentally transform static analysis workflows. Attendees will gain practical insights into emerging solutions to long-standing problems and new research directions in making static analysis tools more reliable and accessible."Biography
Austin Mordahl has been an Assistant Professor at the University of Illinois Chicago since November 2024. Prior to this, he was a Ph.D. student at the University of Texas at Dallas. Dr. Mordahl’s research concerns automatic bug detection and static analysis, and he is especially interested in understanding and improving the performance of real-world static analysis tools. As a Ph.D. student, he was a recipient of the prestigious NSF Graduate Research Fellowship as well as the winner of the 2019 ACM Student Research Competition at ICSE.Research Interests: Program analysis, software testing, software engineering
TIME Wednesday, February 25, 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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Feb26
EVENT DETAILS
lessCS Community! Join us for our monthly free bagels and coffee while mingling with fellow faculty and students.
This month we will also be celebrating Black History Month! Visit the "Words That Carry Us" and "Community Reflection" stations while you snack on baked goods from a local Black-owned bakery.
TIME Thursday, February 26, 2026 at 9:00 AM - 11:00 AM
LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Bella Barrios marbella.barrios@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Feb26
EVENT DETAILS
lessHosted By CSPAC
Title: When AI Agents Stop Listening: Measuring Reasoning Drift in LLM Agent Reinforcement Learning with RAGEN
Abstract: Foundation-model agents are increasingly trained in the loop: they act, receive feedback, and update based on the consequences of their own behavior. This closed-loop paradigm offers a direct path toward stronger long-horizon capability, but it also introduces reliability challenges that are less visible in static supervised learning. In the RAGEN line of work, closed-loop agent training is treated as a systems-and-learning problem: how to make training measurable, how to keep it stable under interaction, and how to ensure the resulting behaviors remain correctable and input-grounded.
This talk will cover a unified perspective across several RAGEN results. First, we will introduce diagnostics that probe multi-turn failure modes—settings where agents remain fluent and confident while weakening their dependence on the specific input, or where training appears to improve aggregate reward while degrading instance-level grounding. Second, we will summarize mechanism views for why these failures emerge in reinforcement learning, emphasizing low-signal updates, the variance structure of feedback, and template-like attractors induced by repeated rollouts. Finally, we will outline lightweight stabilization strategies that improve grounding and training robustness across tasks and modalities, without requiring heavy architectural changes.---
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, February 26, 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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Mar2
EVENT DETAILS
lessMonday / CS Seminar
March 2 / 12:00 PM
Hybrid / Mudd 3514Speaker
Rana Hanocka, University of ChicagoTalk Title
Data-Driven Neural Mesh Editing – without 3D DataAbstract
Much of the current success of deep learning has been driven by massive amounts of curated data, whether annotated or unannotated. Compared to image datasets, developing large-scale 3D datasets is either prohibitively expensive or impractical. In this talk, I will present several works that harness the power of data-driven deep learning for tasks in shape editing and processing, without any 3D datasets. I will discuss works that learn to synthesize and analyze 3D geometry using large image datasets.Biography
Rana Hanocka is an Assistant Professor at the University of Chicago and holds a courtesy appointment at the Toyota Technological Institute at Chicago (TTIC). She founded and directs the 3DL (Threedle) research collective, comprised of enthusiastic researchers passionate about 3D, machine learning, and visual computing. Her research interests span computer graphics, computer vision, and machine learning. She completed her Ph.D. at Tel Aviv University under the supervision of Daniel Cohen-Or and Raja Giryes. Her Ph.D. research focused on building neural networks for irregular 3D data and applying them to problems in geometry processing.---
Zoom: TBA
Panopto: TBATIME Monday, March 2, 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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Mar5
EVENT DETAILS
lessHosted By CSPAC
Title: TBA
Abstract: TBA
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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 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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Mar11
EVENT DETAILS
lessWednesday / CS Seminar
March 11 / 12:00 PM
Hybrid / Mudd 3514Speaker
Li "Harry" Zhang, Drexel UniversityTalk Title
Auto-Formalization for Trustworthy PlanningAbstract
Despite the rapid advancement of AI, most systems in high-stakes applications remain primarily limited to rule-based interactions and cannot reliably plan or execute complex user tasks. Despite recent efforts in using large language models (LLMs) to plan as agents, their hallucinations and lack of verifiability undermine executability and trust, preventing real-world deployment. This proposal advances an alternative paradigm: LLM-as-formalizer. Instead of relying on LLMs to generate plans directly, we use them as a code generator to translate a user’s environment and goal into formal languages (such as PDDL) that can be deterministically solved by off-the-shelf solvers. This neurosymbolic approach combines the flexibility of LLMs with the reliability of symbolic systems, offering a pathway toward trustworthy, generalizable planning. In this talk, I will discuss a few advances in 2025 including a comprehensive evaluation of LLM's auto-formalization ability under a unified methodological framework, and also ongoing work on iterative and multi-agent planning in partially observable environments.Biography
Li "Harry" Zhang is an assistant professor at Drexel University, focusing on Natural Language Processing (NLP) and artificial intelligence (AI). He obtained his PhD degree from the University of Pennsylvania in 2024, advised by Prof. Chris Callison-Burch and chaired by Prof. Dan Roth. He was a year-long intern in 2023 at the Allen Institute for Artificial Intelligence. He obtained his Bachelor's degree from the University of Michigan in 2018, mentored by Prof. Rada Mihalcea and Prof. Dragomir Radev. His research agenda use large language models (LLMs) as auto-formalizers for trustworthy problem-solving, accepted to the AAAI 2026 New Faculty Highlights program. He has published more than 30 peer-reviewed papers in NLP and AI conferences, such as ACL, EMNLP, and NAACL, that have been cited more than 3,000 times. He also consistently serves as Area Chair, Session Chair, and reviewer in those venues. Outside academia, he is a sponsored musician, producer, and content creator having over 60,000 subscribers across streaming platforms.Research Interests: NLP, planning, reasoniong, code generation
TIME Wednesday, March 11, 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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Mar12
EVENT DETAILS
lessHosted By CSPAC
Title: TBA
Abstract: TBA
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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
lessMonday / CS Joint Seminar
April 6 / 3:00 PM
Ford Motor ITWA joint seminar presented by Mechanical Engineering, Computer Science, and the Center for Human–Computer Interaction + Design
Speaker
Faez Ahmed, Massachusetts Institute of TechnologyTalk Title
From Data to Design: Rethinking Engineering Design With Next-Gen AIAbstract
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.Biography
Faez Ahmed is an Associate Professor of Mechanical Engineering at MIT, where heleads 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.TIME Monday, April 6, 2026 at 12:00 PM - 1:00 PM
LOCATION ITW 1350, Ford Motor Company Engineering Design Center map it
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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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)