Please join us on Zoom for our next event in the Fall 2025 Stony Brook School of Nursing Research Seminar Series presented by our Office of Research and Innovation.

Topic: Responsible Artificial Intelligence: Promoting Health Equity for All

Speaker: Michael P. Cary, Jr., PhD, RN, FAAN.

Dr. Cary is a tenured Associate Professor at the Duke University School of Nursing. Dually trained as a health services researcher and applied health data scientist, Dr. Cary utilizes AI to investigate health disparities in aging populations, thereby promoting health equity and improving healthcare delivery. He co-directs HUMAINE™, an initiative dedicated to equipping nurses and healthcare professionals with the knowledge and skills necessary for the responsible use of AI in clinical practice.

Register: https://web.cvent.com/event/057978a5-a770-4de5-aca5-ad00287e4902/summary

You are cordially invited to attend the biweekly Brookhaven AI Mixer (BAM). BAM includes three short talks on AI research happening at BNL, followed by an open mixer over coffee and snacks for everyone to network and discuss all things AI. The first half hour will consist of presentations that will be available via ZOOM, and the second half hour will be for in person only networking.

Join us every other Tuesday at noon in CDSD's Training Room (building 725, 2nd floor) to learn about interesting AI methods and applications, engage with potential collaborators, prepare for pending FASST funding calls, and build a community of AI for Science at BNL.

Tuesday, January 7, 2025, 12:00 pm -- CDS, Bldg. 725, Training Room

Speakers

Chuntian Cao, CDS AID - Neural Network Potential (NNP) for Battery Electrolytes

Yeonju Go, NPP Physics - Generative AI for High-Energy Nuclear Physics

Gilchan Park, CDS AID - Graph RAG: Indexing, Retrieval and Generation

Join ZoomGov Meeting: https://bnl.zoomgov.com/j/1615289117?pwd=Hqkbj9itxWrFnkhZ8rQXHPInO2gxdF.1

Meeting ID: 161 528 9117
Passcode: 991382

The Antonija Prelec Memorial Committee in collaboration with Stony Brook University Libraries are very excited to bring you the 2019 Prelec Memorial Lecture! This year, we are pleased to announce our speaker is Patricia Flatley Brennan, RN, PhD, Director of the National Library of Medicine.

No registration required. Find more information here.
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 10 minutes) by multiple people. Students can register for 1 credit for CSE 656. Registered students must attend and present a minimum of 2 or 3 talks. Everyone else is welcome to attend. Fill in https://forms.gle/pCVXovgfMfQwGqG38 to subscribe to our mailing list for further announcement.
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

As part of a grant project funded by the AI3 Institute, a group of instructors participated in a faculty development program, Fostering Writing-to-Learn Skills with Critical AI Literacy: A Faculty Development and Student Support Program. This program was developed to support instructors across campus with navigating/integrating AI in their courses specifically around writing intensive/involved assignments. We would like to invite anyone interested to the culmination of this program, a mini-symposium, where the participants will share practical changes they made or are making around writing intensive/involved assignments and AI.

Location: Wang 201

A light lunch will be served. Please register by Friday, November 7th.

Abstract: Formalization of mathematics is the process by which pen-and-paper mathematics is translated into a strict chain of logical deductions down to the axioms of mathematics. The subject has seen renewed interest in the last decades thanks to the development of computer systems called proof assistants, which make this feasible in practice.
There have now been several examples of high-profile mathematical results which have been formalized. In principle, any mathematical domain is accessible. However, existing projects are skewed towards algebra instead of analysis. Notable exceptions are a project which formalized enough of Gromov's convex integration theory to deduce Smale's sphere eversion theorem and the ongoing project to formalize Carleson's convergence theorem for Fourier series.
This workshop will bring together formalization experts and interested mathematicians to give a new impulse to formalization of analysis (in a very broad sense), and to develop abstractions and tools to deduplicate effort.

Application Information: ICERM welcomes applications from faculty, postdocs, graduate students, industry scientists, and other researchers who wish to participate. Some funding may be available for travel and lodging. Graduate students who apply must have their advisor submit a statement of support in order to be considered.

The deadline to apply for this workshop is January 24, 2026.

https://icerm.brown.edu/program/topical_workshop/tw-26-ttfa