News & EventsDepartment Events & Announcements
Events
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Apr27
EVENT DETAILS
lessMonday / / CS Distinguished Lecture
April 27 / 12:00 PM
Hybrid / Mudd 3514Speaker
Tushar ChandraTalk Title
From Research to Reality: The Applied AI PlaybookAbstract
Winning an AI benchmark is a feat; serving billions of users across multiple different surfaces is an entirely different challenge. This talk explores the Applied AI frontier at Google, focusing on the rigorous engineering required to bridge the gap between theoretical research and global-scale production. We will dissect the "Well-Lit Path" to production, addressing ease of use, compute efficiency, and non-AGI machine learning, all of which are important to imbue products with AI.Biography
I lead the Applied ML team at Google, where our mission is to enable the best AI across Google's product ecosystem. My team develops end-to-end solutions for teams applying AI to their products, focusing on model selection, prompt engineering, supervised fine-tuning/LoRA, distillation, model upgrades, etc.
Before this role, I led the onboard software team at Waymo, working to realize the mission of making it safe and easy to move people and things through autonomous driving technology.
My earlier tenure at Google spanned 15 years, most recently as a Distinguished Engineer. During that time, I co-founded Sibyl, a general-purpose, large-scale machine learning and data analysis system. My career also includes more than a decade of research at IBM, split between the Almaden and T.J. Watson Research Centers.
I received my B.Tech. in Computer Science from the Indian Institute of Technology, Kanpur—where I first met Professor Khuller—and earned my Ph.D. in Computer Science from Cornell University. In 2010, I was a co-recipient of the Dijkstra Prize (alongside Sam Toueg and Vassos Hadzilacos) for the research conducted in my Ph.D. thesis.
TIME 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 Fefferman, University of ChicagoTalk Title
Have we seen a demonstration of experimental quantum advantage?Abstract
"A major goal for the field of quantum computation is “quantum advantage" -- the first experimental demonstration of a quantum computation that is beyond the capabilities of any classical computer. While we have now seen many quantum advantage claims made by experimental groups around the world, many of these claims have been disproven.In this talk we'll discuss the status quo regarding the latest experimental quantum advantage claims and the evidence for their classical hardness. We’ll then discuss the classical verification problem, and propose a new quantum advantage proposal that uses ideas from quantum error correction to enable a large gap between classical verification and simulation."
Biography
"Bill Fefferman is an Associate Professor in the Department of Computer Science at the University of Chicago. His research explores the power of quantum computers in both the near-term and the indefinite future. He is the recipient of an NSF CAREER award (2020), a Young Investigator Award from the Air Force Office of Scientific Research (2018), and a Google Scholar Award (2022). Before coming to Chicago he held research positions at the University of Maryland/NIST and at the University of California at Berkeley. He received his Ph.D. in computer science in the Department of Computer and Mathematical Sciences and the Institute for Quantum Information and Matter at Caltech."Research Area/Interest: Quantum computing, theory
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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)
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May4
EVENT DETAILS
lessThis dissertation develops and applies computational methods to three problems at the frontier of empirical economics, united by a common objective: to operationalize abstract economic concepts using modern machine learning tools, to uncover new empirical knowledge through those measurements, and to evaluate the conditions under which such tools can be trusted.
The first essay asks what makes a scientific paper novel, and whether novelty of different kinds matters differently for impact. Treating novelty as a multidimensional construct rather than a single attribute, the essay leverages Large Language Models (LLMs) and embedding models to measure novelty directly from the full text of scientific papers. It finds that specific dimensions of novelty, defined by a paper's distinctiveness from its intellectual neighbors versus its engagement with the current frontier, predict fundamentally different outcomes. This finding reveals a strategic tension in knowledge production that citation-based measures of impact cannot capture. The second essay asks why strategic behavior systematically departs from game-theoretic predictions in complex environments. Drawing on a massive dataset of hundreds of millions of chess games, it develops an interpretable measure of when a position is genuinely difficult for a boundedly rational agent, and uncovers a new stylized fact: complexity arises endogenously more often among higher-skilled players. A structural model reveals that this pattern reflects experts' ability to sustain complexity, rather than a preference for risk, a finding with broader implications for understanding how people create and exploit strategic complexity. The third essay asks how much we should trust a predictive model when it is applied outside the context in which it was estimated. It formalizes this out-of-domain prediction problem, derives coverage-guaranteed forecast intervals for transfer error, and finds suggestive evidence that the in-domain superiority of black-box algorithms does not reliably generalize across domains, a cautionary note with direct relevance for the use of machine learning in situations requiring generalizability.
Together, these essays argue that the value of computational tools in economics lies not only in their raw predictive power, but more importantly in their capacity, when disciplined by economic theory, to render previously unobservable quantities measurable and to rigorously evaluate the limits of predictive models.
TIME Monday, May 4, 2026 at 1:30 PM - 3:30 PM
LOCATION Mudd 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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May5
EVENT DETAILS
lessSecure multi-party computation (MPC) enables multiple parties to jointly evaluate a function on their private inputs without revealing any information beyond the output. It is a foundational tool for privacy-preserving applications, including federated analytics, private machine learning, distributed credential issuance, and differentially private data release. Despite decades of progress, a persistent gap remains between the theoretical efficiency of MPC protocols and the performance and usability demands of real-world deployments.
My work is motivated by a core goal: to build secure computation frameworks that are \emph{provably efficient} while remaining \emph{practical for real-world developers}. I work across three areas: (1) generic MPC protocol design, (2) compiler frameworks for MPC, and (3) application-driven cryptographic systems, including differential privacy and thresholdizing standardized post-quantum signature schemes. I propose to build an efficient threshold version of the NIST-standardized FALCON signature scheme along two complementary directions: FALCON-specific algorithmic improvements, including a fixed-point analysis of the fast Fourier orthogonalization sampler to reduce the asymptotic signing complexity, and improved MPC primitives, including more efficient correlation generators applicable to both FALCON and ML-DSA.
TIME Tuesday, May 5, 2026 at 1:00 PM - 2:30 PM
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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May6
EVENT DETAILS
lessWednesday / Student Seminar
May 6 / 12:00 PM
Mudd 3514Speaker:
Title: TBA
Abstract: TBA
Bio: TBA
TIME Wednesday, May 6, 2026 at 12:00 PM - 1:00 PM
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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May13
EVENT DETAILS
lessWednesday / CS Seminar
May 13 / 12:00 PM
Mudd 3514Speaker:
Title: TBA
Abstract: TBA
Bio: TBA
TIME Wednesday, May 13, 2026 at 12:00 PM - 1:00 PM
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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May14
EVENT DETAILS
lessWednesday / CS Distinguished Lecture
May 14 / 4:00 PM
Hybrid / Ford ITW 1350Speaker
Prabhakar RaghavanTalk Title:
Can AI assist in Mathematics and Computer Science research?Abstract:
We share our experience using LLMs to obtain new results in mathematics and computer science. We begin with an illustrative example from load-balancing in planet-scale cloud systems, outlining the abilities and limitations of LLMs. Next, we describe our experience with AlphaEvolve, an evolutionary language model from Google DeepMind, to establish new results in the approximability of the Traveling Salesman Problem (TSP), and MAX-CUT problem. We also derive new bounds for several Ramsey numbers. Our methodology entails evolving fleets of Python programs that generate proof chunks to yield these results, and to accelerate proof verification by up to 10,000x. We suggest that our results on inapproximability and Ramsey theory could not have been discovered by hand, and conclude with reflections on the state and promise of AI in mathematics and CS research.Biography:
Prabhakar Raghavan is the Chief Technologist at Google, where he has held several senior roles since joining in 2012, including Senior Vice President with oversight of Search, Maps, Advertising, Gemini and Payments, and before that, responsibility for Gmail, Google Drive, Calendar and Google Docs. Previously, he led Yahoo! Labs and served as CTO at Verity, Inc following over a decade at IBM Research. He co-authored the textbooks Randomized Algorithms and Introduction to Information Retrieval. Raghavan received a PhD from Berkeley and a Dottore ad honorem from the University of Bologna, and is a member of the National Academy of Engineering.---
ZoomTIME Thursday, May 14, 2026 at 4:00 PM - 5:00 PM
LOCATION ITW 1350, Ford Motor Company Engineering Design Center map it
CONTACT Jensen Smith jensen.smith@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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May18
EVENT DETAILS
lessMonday / Student Seminar
May 18 / 12:00 PM
Mudd 3514Speaker: TBA
Title: TBA
Abstract: TBA
Bio: TBA
TIME Monday, May 18, 2026 at 12:00 PM - 1:00 PM
CONTACT Wynante R Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)
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May20
EVENT DETAILS
lessWednesday / CS Distinguished Lecture
May 20 / 12:00 PM
Hybrid / Mudd 3514Speaker
Julio OttinoTalk Title
TBAAbstract
TBABiography
TBA---
Zoom: TBA
Panopto: TBATIME Wednesday, May 20, 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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May27
EVENT DETAILS
lessCome celebrate with us at the annual end of year department awards on Wednesday May 27th. Details to come.
TIME Wednesday, May 27, 2026 at 3:00 PM - 5:00 PM
LOCATION TGS Commons, 2122 Sheridan Road map it
CONTACT Wynante Charles wynante.charles@northwestern.edu EMAIL
CALENDAR Department of Computer Science (CS)