News & EventsDepartment Events & Announcements
Events
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Feb18
EVENT DETAILSmore info
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From generating text and images to understanding problems and making decisions, artificial intelligence has prompted a wave of experimentation at work. Join us for an insightful conversation with Dr. Eric Horvitz, Chief Scientific Officer of Microsoft and Dr. David Autor, Rubinfeld Professor of Economics at MIT, contributing authors to the National Academies Report on Artificial Intelligence and the Future of Work. This timely discussion will delve into the evolving landscape of work, addressing critical issues such as creating new forms of valuable work and augmenting workers to changing workplace dynamics and labor. The public will gain valuable strategies for navigating workforce changes. Researchers will gain critical insights into AI development and work. And policymakers will understand the need for flexible responses. Don’t miss this chance to engage with thought leaders shaping the future of work and gain actionable insight to stay ahead in our rapidly changing world.
TIME Tuesday, February 18, 2025 at 1:00 PM - 2:00 PM
CONTACT Madison Deyo madison.deyo@northwestern.edu EMAIL
CALENDAR Center for Human-Computer Interaction + Design (HCI+D)
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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, reasoning, 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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Mar11
EVENT DETAILS
lessSpeaker: Zeyu Liu, Yale University
Title: Recent Advancements in Single-Server Oblivious Message Retrieval
Abstract: Anonymous message delivery systems, such as private messaging services and privacy-preserving blockchains, require mechanisms that allow recipients to retrieve messages addressed to them without leaking metadata or enabling message linkage. A simple approach is for recipients to download all posted messages and locally scan for those addressed to them, but this becomes prohibitively expensive in terms of communication and computation at scale.
We show how untrusted servers can detect messages on behalf of recipients and aggregate them into a compact encrypted digest that recipients can efficiently decrypt, via the cryptographic primitive Oblivious Message Retrieval. These servers operate obliviously and learn nothing about which messages are addressed to which recipients. Privacy, soundness, and completeness are guaranteed even if all parties except the recipient are adversarial and colluding. Moreover, our model and constructions generalize naturally to group messaging or mailing lists, where senders can generate messages that are efficiently detectable by multiple designated recipients.
In this talk, we begin with an asymptotically efficient construction based on Fully Homomorphic Encryption and homomorphically encoded Sparse Random Linear Codes. We then discuss recent advancements that lead to concretely efficient instantiations of this paradigm. Finally, we address additional security considerations, including resilience to denial-of-service attacks.
Bio: Zeyu Liu is a PhD student at Yale University, advised by Ben Fisch. He received his MS from Columbia University, where he was advised by Tal Malkin and Eran Tromer. His research focuses on cryptography, including fully homomorphic encryption, metadata privacy, and lattice-based cryptography.
TIME Wednesday, March 11, 2026 at 12:00 PM - 1:00 PM
LOCATION 3001, Mudd Hall ( formerly Seeley G. Mudd Library) map it
CONTACT Xiao Wang wangxiao@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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Mar12
EVENT DETAILS
lessHosted By CSPAC
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
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 3:00 PM - 4:00 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)
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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)