Abstract: Theory-internal work on opacity in phonology has been focused on the challenges these interactions present for one theory (rules, constraints) versus another. But there has also been interest in studying the formal, invariant properties of opaque and other process interactions (Chandlee et al. 2018; Bakovic and Blumenfeld 2024), though these works crucially differ in their underlying assumptions. In this talk I will recontextualize Chandlee et al. (2018)'s result that opaque maps are ISL in light of Bakovic and Blumenfeld (2024)'s recent formal typology of process interactions, and this recontextualization will provide an answer to an open question about the k-value of an interaction map. I will then discuss the implications of this collective formal understanding of opacity for a recent model of lexicon and phonological grammar learning (i.e., Hua and Jardine 2021, Chandlee and Jardine to appear).


Speaker: Prof. Jane Chandlee, Associate Professor in the Department of Linguistics at Haverford College

Location: IACS Seminar room.
The International Neuroethics Society (INS) Speaker Series on AI & Consciousness

Abstract: Colln Allen and I noted in our 2008 book Moral Machines: Teaching Robots Right From Wrong, that consciousness, a theory of mind, sociability, situational awareness and embodiment are all supra-rational (beyond reason) capabilities that contribute to making ethical decision Whether any of these can be fully instantiated in machines remains an open question. Nevertheless, moral decision making in the digital age will require an evolution in and refinement of specific skills for both humans and for AI. I call one of these evolutions in moral decision making capabilities tradeoff ethics and another a silent ethics. Aspects of this social, and not just technological evolution, will require research by neuroscientists.

Speaker Bio: Wendell Wallach has an international reputation as an expert on the ethics and governance of emerging technologies, particularly artificial intelligence and biotechnologies. He is also senior advisor to The Hastings Center and a scholar at the Yale University Interdisciplinary Center for Bioethics where he chaired Technology and Ethics studies for eleven years. Wallach's latest book, a primer on emerging technologies, is entitled, A Dangerous Master: How to keep technology from slipping beyond our control. He co-authored (with Colin Allen) Moral Machines: Teaching Robots Right From Wrong. Wallach has been referred to as, a Godfather of AI Ethics.

Pre-register here (required): https://umaryland.zoom.us/meeting/register/sPpiR_drR4-9JYDhI2NhJg
Join us as we celebrate this year's Brook & Beyond Challenge finalists.
The Office for Research and Innovation invites you to hear about the two-month journey in which the Brook & Beyond team supported eight cohorts in bringing their bold ideas from the lab to the marketplace. It's an energizing evening that highlights the collaboration, creativity, and entrepreneurial spirit driving discovery across the University.
Meet this year's award recipients, hear pitches from the emerging founders, and applaud their achievements.
Connect, celebrate, and be part of the momentum shaping the future of innovation at
Stony Brook University.
Refreshments will be served. Registration is required.
Register Here.

Join us for an engaging panel discussion featuring researchers who participated in our inaugural AI JAM session on February 26th. Our panelists will share their firsthand experiences using large language models to tackle complex scientific problems, with a special focus on prompt engineering strategies, discussing both breakthroughs and challenges encountered during this collaborative initiative. Learn how these cutting-edge AI tools are being applied to real-world research questions and discover insights that could inform your own scientific endeavors. Attendees are encouraged to come prepared with questions about prompt engineering for the panel discussion.

Moderator: Adolfy Hoisie, Deputy Director, Computing and Data Sciences

Kevin Yager, Group Leader, AI-Accelerated Nanoscience, Center for Functional Nanomaterials
Lingda Li, Associate Computational Scientist, Systems, Architecture and Computing Technologies, Computing and Data Sciences
Liguo Wang, Director of Scientific Operations, Laboratory for BioMolecular Structure (LBMS), National Synchrotron Light Source II
Weiguo Yin, Physicist, Condensed Matter Theory, Condensed Matter Physics and Materials Science Department

Location: CDS, Bldg. 725, Training Room

Join ZoomGov Meeting: https://bnl.zoomgov.com/j/1606837837?pwd=Tc0mwQqLXpDfYOIaoaurmpLD2mMlzS.1 (Meeting ID)

Passcode: 822553

The overall purpose of this seminar is to bring together people with interests in Computer Vision theory and techniques and to examine current research issues. This course will be appropriate for people who already took a Computer Vision graduate course or already had research experience in Computer Vision. To enroll in this course, you must either: (1) be in the PhD program or (2) receive permission from the instructors. Each seminar will consist of multiple short talks (around 15 minutes) by multiple students. Students can register for 1 credit for CSE656. Registered students must attend and present a minimum of 2 talks. Everyone else is welcome to attend. Fill in https://forms.gle/q6UG9ygauLp2a8Po8 to subscribe to our mailing list for further announcement.
Prof. Eugene A. Feinberg, from the Department of Applied Mathematics and Statistics, presents, Recent Developments in Markov Decision Processes Relevant to AI on April 4 at 4p. The talk discusses recent developments in Markov Decision Processes potentially relevant to artificial intelligence. These developments include complexity estimations for exact and approximate algorithms, decision making with incomplete information and multiple criteria, and continuity properties of optimal values and expectations. Dr. Eugene A. Feinberg is currently Distinguished Professor in the Department of Applied Mathematics and Statistics at Stony Brook University. He is an expert on applied probability, stochastic models of operations research, Markov decision processes, and on industrial applications of operations research and statistics. He has published more than 150 papers and edited the Handbook of Markov Decision Processes. His research has been supported by NSF, DOE, DOD, NYSTAR (New York State Office of Science, Technology, and Academic Research), NYSERDA (New York State Energy Research and Development Authority) and by industry. He is a Fellow of INFORMS (The Institute for Operations Research and Management Sciences) and has received several awards including 2012 IEEE Charles Hirsh Award for developing and implementing smart grid technologies, 2012 IBM Faculty Award, and 2000 Industrial Associates Award from Northrop Grumman. Dr. Feinberg is an Associate Editor for Mathematics of Operations Research and for Applied Mathematics Letters. He is an Area Editor for Operations Research Letters. Refreshments will be provided
The Future Histories Studio welcomes Moontae Lee, LG AI Research.


Generative AI is transforming how we understand, create, and interact with information. Large Language Models (LLMS) comprehend contexts, answer non-trivial questions, and spark creative ideas. This talk introduces the evolution of these models, highlighting the most recent advancements in planning, reasoning, and evaluation. The talk also touches on the criticalconsiderations for both model developers and users, carefully addressing limitations of LLMs as well as ethical and societal implications. Finally, the talk provides ongoing directions in researchand production: from the rise of personalized AI agents to the future frontiers of AI.

Moontae Lee is the Director of the Superintelligence Lab at LG AI Research and an Assistant Professor of Information and Decision Sciences at the University of Illinois Chicago. His journey with Large Language Models began as a visiting scholar at Microsoft Research in 2019, continuously consulting the Deep Learning Group at Redmond until joining LG. He holds a PhD in Computer Science from Cornell, an MS from Stanford, and BS degrees in Computer Science, Mathematics, and Psychology from Sogang University. He has been an area chair for major AI conferences and earned recognition in Operations Research and Computational Social Science, including awards from INFORMS and Amazon.

His research interests include:
● Computational Creativity, Algorithmic Awareness
● Retrieval-Augmented Generation and Evaluation
● Code Generation, Reasoning, Planning
● Fine-grained Alignment from Human/AI Feedback in Generative AI
● Large Time-series Models, Diffusion/Consistency
● Machine Unlearning
● Ranking Monopoly, Voting Fairness
● AI Safety, Ethics, and Market Impacts

Join us in person @ Future Histories Studio Staller Center for the Arts, 4222

The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning.

ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics.

ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.


For more information and registration, visit the official website.
Abstract: In this talk, we take a step back and argue that many varied and seemingly unrelated attacks on the web are actually symptoms of one deeper problem that has existed since the web's inception. Whether it is attacks due to expired domain names, cloaking done by malicious websites, malvertising, or even our growing distrust of the news can be largely attributed back to the issue of stateless linking. Stateless linking refers to the absence of any integrity guarantees between the time that a link for a remote resource was created, to a future time when this link is resolved by web clients. We draw on 10+ years of research to demonstrate how stateless linking and the resulting lack of content integrity is the true culprit for many of our past, current, and likely future web problems. Successfully tackling this one really challenging problem, has the potential of solving many of our web woes.

Bio: Nick Nikiforakis is affiliated with the National Security Institute. He received his PhD in Computer Science from KU Leuven in Belgium. He received his MSc, in Parallel and Distributed Systems and BSc in Computer Science from the University of Crete, Greece. His research focuses on web security and privacy, software security, and intrusion detection.

Location: NCS 120