April 2026 - talks - lists.cs.princeton.edu

Alan Zhang will present his MSE talk "Detection-based Attention Steering System for Vision Language Models" on Friday, Apr 24th, 2026 in CS 105 at 2pm in CS 105.
by Gradinfo 15 Apr '26

15 Apr '26

Alan Zhang will present his MSE talk "Detection-based Attention Steering System for Vision Language Models" on Friday, Apr 24th, 2026 in CS 105 at 2pm in CS 105. All are welcome to attend. Presenter: Alan Zhang (az0686) Advisor: Ravi Netravali Reader: Wyatt Lloyd Abstract: Modern Vision Language Models (VLMs) have demonstrated remarkable versatility in a wide variety of applications involving multimodal reasoning, captioning, and analysis. However, VLMs still struggle with the fundamental tasks of object detection and localization, especially when compared to traditional Convolutional Neural Network (CNN) models. Contemporary VLMs tend to allocate very scarce attention to non-textual inputs such as image tokens and lack the visual inductive biases present in CNNs, making it difficult for them to identify challenging objects in complex scenes. To address these limitations, we propose a detection-based dynamic attention steering system that utilizes the locality insight from convolutions to efficiently steer a VLM's attention toward more relevant sections of an image outlined by bounding boxes from a CNN-based detector model. The steering intensity during each inference is dynamically scaled according to the confidence of the bounding boxes. Extensive evaluations across multiple state-of-the-art VLMs demonstrate substantial improvements on object localization-oriented benchmarks, achieving up to a 4% accuracy gain. Results show the effectiveness of combining different model architectures to harness their respective strengths for advancing VLM capabilities.

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Ziyu Xiong will present her General Exam "Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra" on Friday, April 17, 2026 at 3:00 PM in Friend 202 and via zoom.
by CS Grad Department 14 Apr '26

14 Apr '26

Ziyu Xiong will present her General Exam "Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra" on Friday, April 17, 2026 at 3:00 PM in Friend 202 and via zoom. Zoom link: https://princeton.zoom.us/j/95476730233 Committee Members: Ellen Zhong (advisor), Zhuang Liu, Ryan Adams Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is a cornerstone technique for determining the structures of small molecules and is especially critical in the discovery of novel natural products and clinical therapeutics. Yet, interpreting NMR spectra remains a time-consuming, manual process requiring extensive domain expertise. We introduce ChefNMR (CHemical Elucidation From NMR), an end-to-end framework that directly predicts an unknown molecule's structure solely from its 1D NMR spectra and chemical formula. We frame structure elucidation as conditional generation from an atomic diffusion model built on a non-equivariant transformer architecture. To model the complex chemical groups found in natural products, we curated a dataset of simulated 1D NMR spectra for over 111,000 natural products. ChefNMR predicts the structures of challenging natural product compounds with an unsurpassed accuracy of over 65% on simulated benchmarks, but generalizing to real experimental NMR spectra remains a key challenge. To bridge this synthetic-to-real gap, we propose further improvements, including a more robust peak-based spectral encoder, a flow matching generative framework, a multimodal transformer architecture, and expanded training data. This work takes a significant step toward solving the grand challenge of automating small-molecule structure elucidation and highlights the potential of deep learning in accelerating molecular discovery. Reading List: https://docs.google.com/document/d/1OLM7gak0-XaH8To0Al_zOrEIwyvezDM4bAxvUyO… Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.

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Jens Tuyls will present his FPO "From Expert Imitation to Autonomous Discovery in Intelligent Agents" on Tuesday, April 21, 2026 at 2 PM in CS 105.
by CS Grad Department 14 Apr '26

14 Apr '26

Jens Tuyls will present his FPO "From Expert Imitation to Autonomous Discovery in Intelligent Agents" on Tuesday, April 21, 2026 at 2 PM in CS 105. The members of Jens’ committee are as follows: Examiners: Karthik Narasimhan (Adviser), Benjamin Eysenbach, Tom Silver Readers: Danqi Chen, Chi Jin A copy of his thesis is available upon request. Please email gradinfo(a)cs.princeton.edu if you would like a copy of the thesis. Everyone is invited to attend his talk. Abstract follows below: Learning from demonstrations and learning from experience are two learning paradigms that lie at the heart of today’s most capable AI systems. This thesis focuses on questions related to both of these paradigms: (1) how to recover expert behavior from demonstration data, (2) how to explore an environment without access to demonstration data, and (3) how to leverage expert knowledge to guide exploration. Chapter 1 focuses on learning from expert demonstrations and asks the following question: What role do model and data size play in recovering the expert’s performance when training policies with behavioral cloning? We demonstrate that the same empirical scaling laws used in language modeling accurately describe the loss and return functions in behavioral cloning on single-agent games, allowing practitioners to predict the compute-optimal model and data size to reach a certain level of performance. Chapters 2 and 3 introduce two novel reinforcement learning-based methods for exploring an environment without access to expert demonstrations. The first method uses explicitly disentangled exploration and exploitation phases combined with curiosity-based intrinsic rewards to explore the state space, setting a new state-of-the-art in challenging text game environments. The second method learns a large set of policies (or “skills”) through mutual information skill learning that, taken together, cover the state space of the MDP. In continuous control tasks, the method is competitive with current state-of-the-art skill-learning methods. Finally, Chapter 4 studies the interplay between learning from expert data and autonomous exploration by asking the following question: Can the knowledge in language model representations, which is mostly obtained from expert data, help drive exploration toward learning novel behaviors? Our empirical results suggest deliberate exploration with reinforcement learning on top of pre-trained language models can be a promising path for learning novel behaviors beyond those of human experts. Taken together, this thesis provides foundational empirical insight for learning from expert data as well as novel empirical methods for learning from experience through exploration.

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Jane Castleman will present her MSE thesis "Measuring Validity in Resume Screening Systems" on Tuesday, April 14th, 2026 in Sherrerd Hall 306 at 4:30pm.
by Gradinfo 13 Apr '26

13 Apr '26

Jane Castleman will present her MSE thesis "Measuring Validity in Resume Screening Systems" on Tuesday, April 14th, 2026 in Sherrerd Hall 306 at 4:30pm. Advisor: Aleksandra Korolova Reader: Lydia T. Liu All are welcome to attend. Abstract: Resume screening is perceived as a particularly suitable task for LLMs given their ability to analyze natural language; thus many entities rely on general purpose LLMs without further adapting them to the task. While researchers have shown that some LLMs are biased in their selection rates of different demographics, studies measuring the validity of LLM decisions are limited. One of the difficulties in externally measuring validity stems from lack of access to a large corpus of resumes for whom the ground truth in their ranking is known and that has not already been used for LLM training. In this work, we overcome this challenge by systematically constructing a large dataset of resumes tailored to particular jobs that are directly comparable, with a known ground truth of superiority. We then use the constructed dataset to measure the validity of ranking decisions made by various LLMs, finding that many models are unable to consistently select the resumes describing more qualified candidates. Furthermore, when measuring the validity of decisions, we find that models do not reliably abstain when ranking equally-qualified candidates, and select candidates from different demographic groups at different rates. Our proposed framework provides a principled approach to audit LLM resume screeners in the absence of ground truth, offering a crucial tool to independent auditors and developers to ensure the validity of these systems as they are deployed.

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Peter Zoller presents a public lecture on quantum computing on April 14 at 5 pm
by Emily C. Lawrence 09 Apr '26

09 Apr '26

PCTS Public Lecture Tuesday, April 14, 2026 5:00 PM, McDonnell Hall, Room A-02 Speaker: Professor Peter Zoller Title: When Atoms Compute Subtitle: Quantum computing, simulation, and sensing with atoms, ions, and light Abstract: Quantum mechanics governs nature at its smallest scales—but today we can engineer that quantum world by creating and controlling entanglement, the unique fingerprint of quantum physics. Using laser-controlled atoms and ions, researchers can build programmable quantum devices that compute beyond classical limits, emulate complex quantum matter, and approach fundamental quantum limits. This talk gives a non-technical overview of leading platforms, from trapped-ion processors to quantum simulators based on ultracold atoms. We illustrate the ideas with snapshots from current research: string-breaking dynamics inspired by high-energy physics, using simulators to guide materials design, methods to validate what quantum devices are doing when classical calculation is no longer feasible, and an outlook toward programmable quantum sensors. There is no registration requirement for the public lecture.

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CoE Seminar - Prof. David Sholl, 4/23 at 10:00 am in Maeder Hall
by Emily C. Lawrence 09 Apr '26

09 Apr '26

CoE Seminar Thursday, April 23 at 10:00am in Maeder Hall Auditorium David Sholl, Rice University Title: When Do I Get My Flying Car? Assessing the Potential of AI to Revolutionize Separations Science Abstract: Artificial intelligence and machine learning have been suggested as tools that will revolutionize many areas of science and society. I will discuss the potential and pitfalls for these methods in a key field within chemical engineering, namely separations science. Examples will include scanning collections of thousands of porous materials for adsorption-based separations of complex molecular mixtures, searching for high performance materials for Direct Air Capture of carbon dioxide, and developing mixed matrix membranes for gas separations.

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Yann LeCun's talk at ORFE
by Kai Li 07 Apr '26

07 Apr '26

From: "Ariana M Reyes" <ar8562(a)princeton.edu> To: "Bartolomeo Stellato" <bstellato(a)princeton.edu>, "Kai Li" <li(a)cs.princeton.edu> Cc: "Connie A. Brown" <connieb(a)princeton.edu> Sent: Tuesday, April 7, 2026 12:40:28 PM Subject: RE: Meeting with Yann LeCun Dear Kai, We are glad that you were able to sign up for an individual meeting and to attend dinner. Below is the announcement that we sent out if you can please circulate it to CS students and faculty as suggested. Thank you! ……………………………………………………………………………………………………………………… Today’s ORFE Department Colloquia Date & Time: Tuesday, April 7, 2026 at 4:30 PM Location: 101 - Friend Center Speaker: [ https://orfe.princeton.edu/events/2026/yann-lecun-new-york-university | Yann LeCun, New York University ] Bio: Yann LeCun is the Executive Chairman of AMI Labs and the Jacob T. Schwartz Professor at NYU affiliated with the Courant Institute - School of Mathematics, Computer Science, and Data Science. He was the Chief AI Scientist at Meta (2018-2025), the founding Director of Meta-FAIR (2013-2017), and of the NYU Center for Data Science (2011-2014). He received an Engineering Diploma from ESIEE (Paris) and a PhD from Sorbonne Université (1987). After a postdoc in Toronto he joined AT&T Bell Labs in 1988, and AT&T Labs in 1996 as Head of Image Processing Research. He joined NYU as a professor in 2003 and Meta/Facebook in 2013. His interests include AI, machine learning, computer perception, robotics, and computational neuroscience. He is the recipient of the 2018 ACM Turing Award (with Geoffrey Hinton and Yoshua Bengio) for "conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing", a member of the National Academy of Sciences, the National Academy of Engineering, the French Académie des Sciences. ………………………………………………………………………………………………………………………….. Ariana Reyes Administrative Assistant & Events Operations Research and Financial Engineering (ORFE) Princeton University Sherrerd Hall, Room 119, Princeton NJ 08544 609-258-9076 ar8562(a)princeton.edu From: Bartolomeo Stellato <bstellato(a)princeton.edu> Sent: Saturday, April 4, 2026 10:36 AM To: Kai Li <li(a)cs.princeton.edu> Cc: Ariana M Reyes <ar8562(a)princeton.edu>; Connie A. Brown <connieb(a)princeton.edu> Subject: Re: Meeting with Yann LeCun Dear Kai, Glad you were able to sign up for a meeting and dinner! Sherrerd 117 is the visitor room assigned to Yann, so it's the most convenient one for meetings. That should work well for your 1:30pm slot. Let us know if you have any questions. Best, Bartolomeo On Sat, Apr 4, 2026 at 12:05 AM Kai Li < [ mailto:li@cs.princeton.edu | li(a)cs.princeton.edu ] > wrote: Dear Bartolomeo, I signed up for 1:30pm slot in Sherred 117. I saw Elad meets Yann there. Is it the room for me to meet him or should I meet him in my office in CS building? I also signed up for dinner. Thank you! Kai ----- On Apr 3, 2026, at 7:55 PM, Bartolomeo Stellato < [ mailto:bstellato@princeton.edu | bstellato(a)princeton.edu ] > wrote: BQ_BEGIN Dear Kai, Thanks for reaching out. We still have a couple of slots available on the schedule, and you are welcome to sign up for lunch or dinner as well. The sign-up sheet is here: [ https://princetonu-my.sharepoint.com/:x:/g/personal/orfe-onedrive_princeton… | https://princetonu-my.sharepoint.com/:x:/g/personal/orfe-onedrive_princeton… ] The talk page is here: [ https://orfe.princeton.edu/events/2026/yann-lecun-new-york-university | https://orfe.princeton.edu/events/2026/yann-lecun-new-york-university ] . We are still waiting for the final title and abstract, but we can let you know as soon as they are available. Happy to have you circulate it to CS, of course. Looking forward to meeting you on Tuesday. Best, Bartolomeo On Fri, Apr 3, 2026, 8:15 PM Kai Li < [ mailto:li@cs.princeton.edu | li(a)cs.princeton.edu ] > wrote: BQ_BEGIN Dear Ariana, Connie and Bartolomeo, This is Kai Li, a faculty member at Computer Science. Sean at NYU told me that Yann LeCun is giving a talk at ORFE and you mentioned to Sean that it would be nice for me to meet Yann. For some reason, I couldn't find any message about this in my email. I have known Yann for over 10 years and would be great to see him again. I am flexible to meet him on April 7th. Please let me know what time slots are available. If you would like me to circulate his talk to CS faculty and students, please send me info about his talk so that I can forward. Best wishes, Kai Kai Li Paul & Marcia Wythes Professor Department of Computer Science Princeton University [ https://www.google.com/maps/search/35+Olden+street+Princeton,+NJ+08544?entr… | 35 Olden street ] [ https://www.google.com/maps/search/35+Olden+street+Princeton,+NJ+08544?entr… | Princeton, NJ 08544 ] (609) 258-4637 BQ_END BQ_END

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Ilya Maier will present his MSE thesis “Induced Cycles of Many Lengths" on Tuesday, April 21, 2026 at 2:30pm in Fine Hall 224.
by Gradinfo 07 Apr '26

07 Apr '26

Ilya Maier will present his MSE thesis “Induced Cycles of Many Lengths" on Tuesday, April 21, 2026 at 2:30pm in Fine Hall 224. Adviser: Maria Chudnovsky, Reader: Pravesh Kothari. All are welcome to attend. Abstract: Let $G$ be a graph and let $\mathrm{cl}(G)$ be the number of distinct induced cycle lengths in $G$. We show that for $c,t\in \mathbb N$, every graph $G$ that does not contain an induced subgraph isomorphic to $K_{t+1}$ or $K_{t,t}$ and satisfies $\mathrm{cl}(G) \le c$ has bounded treewidth. As a consequence, we obtain a polynomial-time algorithm for deciding whether a graph $G$ contains induced cycles of at least three distinct lengths.

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Theresa Lim will present her MSE Thesis: "A Functional Introduction to Computer Science" on April 20, 2026 at 11am in CS 302.
by Gradinfo 07 Apr '26

07 Apr '26

Theresa Lim will present her MSE Thesis "A Functional Introduction to Computer Science" on April 20, 2026 at 11am in CS 302. Adviser: David Walker, Reader: Kevin Wayne All are welcome to attend. Abstract below: In recent years, there has been increased demand for computer science (CS) education at the primary and secondary level. Traditionally, introductory CS courses teach students about an imperative language, such as Java or Python, and students practice writing increasingly complex programs from scratch. However, with the rise of AI-generated code, it is more important than ever that students develop the skill of reasoning about unfamiliar code in a systematic and critical manner. Additionally, many researchers have identified discrete mathematics courses as a common difficulty for college computer science students due to students' unfamiliarity with writing proofs. This work presents a 20-hour introductory computer science curriculum that aims to address both of these problems. The course is tailored to high school students with little to no coding experience, and it teaches students to code in OCaml and reason about program correctness using equational reasoning and proof by induction. We incorporate modern pedagogical techniques, including backward design, differentiated instruction, and culturally-responsive pedagogy. This course not only prepares students for future work in computer science but also strengthens the logical reasoning skills that math and science disciplines require. This abridged course serves as a foundation for future proof-based introductory computer science curricula.

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Computational Math IDeAS Seminar
by Emily C. Lawrence 07 Apr '26

07 Apr '26

COMPUTATIONAL MATH – IDeAS SEMINAR Recurring weekly series · Thursdays, 2:00 – 3:00 PM This week's talk: Speaker: Daniel B. Szyld (Temple) Title: Convergence of Randomized and Greedy Block Gauss-Seidel methods, as well as Asynchronous Iterations Date: Thursday, April 9, 2026 Time: 2:00 PM – 3:00 PM Room: 224 Fine Hall Abstract: We extend results known for the randomized (point and block) Gauss-Seidel and the Gauss-Southwell methods for the case of a Hermitian and positive definite matrix to certain classes of non-Hermitian matrices. We consider cases with overlapping variables (as in Domain Decomposition). We obtain convergence results for a whole range of parameters describing the probabilities in the randomized method or the greedy choice strategy in the Gauss-Southwell-type methods. We identify those choices which make our convergence bounds best possible. One result is that the best convergence bounds that we obtain for the expected values in the randomized algorithm are as good as the best for the deterministic, but more costly algorithms of Gauss-Southwell type. We use these new results to show a provable convergence rate for asynchronous iterations. (Joint work with Andreas Frommer) About the speaker: Daniel B. Szyld is Professor of Mathematics at Temple University. Until recently he was the President of the International Linear Algebra Society (2020-2026). He was Vice-President (at large) of SIAM, the Society for Industrial and Applied Mathematics in 2014-2015. He was the editor-in-chief of the SIAM Journal on Matrix Analysis and Applications (2015-2020) and of the Electronic Transactions on Numerical Analysis (2005-2013). He is a SIAM Fellow, and an AMS Fellow. He has worked on many aspects of numerical linear algebra and matrix computations, including eigenvalue problems, sparse matrix techniques, Schwarz preconditioning and domain decomposition, Krylov subspace methods, and asynchronous iterative methods. His PhD is from the Courant Institute, New York University (1983), which he attended after undergraduate studies in his native Buenos Aires. Up next: Thursday, April 16 – Elad Romanov (Yale University). - Liza Rebrova, Marc Aurèle Gilles, and Jorge Garza Vargas.

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