Come learn of the exciting research being done across so many fields using AI! The recipients of AI3's seed awards will present their work in our showcase on November 17, 2025 and we would love to see you there!

The schedule is listed below.

Location: New Computer Science Room 120

Session 1 - 10:30 AM to 11:45

Kevin Reed, PI, Introducing the AI Techniques in Assessing the Future Changes of Extreme Precipitation and Associated Flood Risks
Co-PIs: Tangnyu Song, Ishrat Dollan
Consultant: Jayesh Rathi

Ruwen Qin, PI, AI-Assisted Analysis of Materials in Recycling Streams
Consultant: Vismay Vora

Giuseppe Gazzola, PI, Using AI to Investigate National Literatures: Italy, France, Spain 1733- 1794
Consultant: Jayesh Rathi

Joseph Lemelin, PI, IAE2^3: AI Ecologies
Co-PIs: Katherine Johnston, Aruna Balasubramanian, Matthew Salzano

Niranjan Balasubramanian, Co-PI, Molecular Foundations for Sustainability: Data Analytics for Sustainable Cellulose Scaffolding Modifications to Remediate Diverse Water Contamination Challenges
PI: Benjamin Hsiao, Co-PI: I. V. Ramakrishnan

Owen Rambow, PI,Achieving Common Ground Through Language and Vision in Mixed-Initiative Human-Machine Communication Via zoom
Co-PI Susan Brennan

Session 2 - 12:30 PM to 1:45

Jack McSweeney, PI, Developing Machine Learning Approaches to Classify Internal Waves
Consultant: Vismay Vora

Eric Josephs, PI, Learning Design Rules to Personalize Precision CRISPR Gene Therapies with Interpretable AI
Consultant: Deboparna Banerjee

Shyam Sharma, PI, Fostering Writing-to-Learn Skills through Critical AI Literacy: A Faculty Development and Student Support Program
Co-PIs: Rose Tirotta-Esposito, Christine Fena

Ritwik Banerjee, PI, A Pragmatic Approach to AI for Digital Media Integrity: Combating Complex Misinformation Through Fallacies and Propaganda
Co-PI: Ruobing Li

Ziyu Shu, Co-PI, Novel Clinical Applications of Deep Image Prior-based CT Image Reconstruction
PI: Xin Qian, Co-PIs: Tiezhi Zhang, Zhaozheng Yin

Prateek Prasanna, Co-PI, An Artificial Intelligence-Driven Clinical Decision Support Tool for the Management of Abdominal Aortic Aneurysm
PI: Apostolos Tassiopoulos, Co-PI's: Mary Saltz, Janos Hajagos, Tahsin Kurc



Presenters will give a 5-minute talk with 2 minutes for Q & A.

Abstract: As intelligent systems become more integrated into human environments, fostering trustworthy human-AI collaboration presents a pressing challenge. In this talk, I examine the interplay between an agent's performance and social dynamics in shaping trust in human-AI interactions. My approach combines testbed development, behavioral prototyping, and user study design to create controlled experimental setups that capture real-world interaction complexities, such as ambiguity, multi-agent dynamics, and conflicting goals.

I illustrate this with a recent VR study on multi-user interaction with an autonomous vehicle (AV). Moving beyond dyadic interactions, the study probes human perspectives from the roles of a pedestrian, driver, and AV passenger, all interacting with the AV simultaneously at an ambiguous all-way stop sign intersection. We compare interactions with efficient and prosocial AV behavior strategies, revealing diverging trust perceptions and preferences across user roles. These insights inform a broader research trajectory focused on balancing performance with social considerations in designing trustworthy human-AI collaborations.

Bio: JiHyun Jeong is a postdoctoral researcher at Cornell University working on human-computer interaction and human-robot interaction. Her research develops prototypes and methods to explore performance and social factors that influence collaboration and trust between humans and artificial agents. She holds a Ph.D. and MPS in Information Science from Cornell University, and a BSc in Computer Science and Engineering from Korea University. She is a recipient of an honorable mention for best paper at DIS.

Zoom: https://stonybrook.zoom.us/j/98738234619?pwd=djJFQXBWbkpmblZDT25zNlVMYWpCQT09

Meeting ID: 987 3823 4619
Passcode: 474618

The Pittsburgh Supercomputing Center is pleased to present a Machine Learning and Big Data workshop.

This workshop will focus on topics including big data analytics and machine learning with Spark, as well as deep learning.

This will be an IN PERSON event hosted by various satellite sites, there WILL NOT be a direct to desktop option for this event. SBU's Institute for Advanced Computational Science (IACS) is one of those satellite sites!

Location: IACS Conference Room #2

Interested applicants must first have an ACCESS ID. If you don't have the ID, please visit this page to create one: ACCESS USER REGISTRATION.


Once you have an ACCESS ID, please login (see top right here) then register here.
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



Matthew Salzano (Stony Brook), AI and DEIA: Getting at the Roots

Link to the talk (no pre-registration required this time): https://stonybrook.zoom.us/j/96209347479?pwd=Cs8fEfFdbXrGTC5cQgyHRb8Msh5vp8.1Meeting ID: 962 0934 7479 Passcode: 272489

Abstract: Conversations about AI and DEIA (Diversity, Equity, Inclusion, and Access) often unwittingly assume that social problems can and should have technical fixes. Left unaddressed, scholars, advocates, and technologists inevitably miss important consequences in our proposed solutions, and focus on surface-level problems rather than addressing the root causes of inequity. Drawing from scholarship in communication, rhetoric, and critical digital studies, this talk explains how we are often trimming branches when we need to pull out roots -- and introduces new terms and questions that can help reorient our conversations about AI and DEIA.

Speaker Bio: Matthew Salzano, Ph.D., is a communication scholar researching new media technologies, user practices, and cultural trends that threaten to limit possibilities for diverse engagement in public argument, debate, and protest. His scholarship has appeared in journals like The Quarterly Journal of Speech, Critical Studies in Media Communication, and Women's Studies in Communication, and his research on DEIA, AI, and advocacy communications has been funded by the Waterhouse Family Institute at Villanova University. He is currently an Inclusion, Diversity, Equity, and Access fellow in Ethical AI at Stony Brook University's School of Communication and Journalism and Alan Alda Center for Communicating Science.

Join us for the New York State Innovation Summit on October 28-29, 2024 in Syracuse, NY. This multi-day is event for NYS organizations that want to showcase and discover new and emerging technologies that support innovation and drive business growth. The event serves as an opportunity to foster collaboration; introduce industry to experts that can assist growth, strengthen our statewide innovation ecosystem and showcase promising early stage companies. Whether you're a startup, an economic developer, or an established manufacturer, the NYS Innovation Summit is for you. The 2024 New York State Innovation Summit will showcase companies and researchers at the forefront of emerging technologies and new advancements in production capabilities. This event celebrates New York State leadership in technology-led economic growth with experts in biotechnology, new materials, energy innovation, and artificial intelligence that will explore current technology convergence opportunities, ways to accelerate commercialization, and issues of manufacturing sustainability.

You are cordially invited to attend the biweekly Brookhaven AI Mixer (BAM). BAM includes one short talk 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.

Abstract: This presentation will begin by outlining key challenges facing the modern power grid and summarizing our group's research efforts to address them. It will then discuss how AI and machine learning are reshaping the grid modernization. The major focus of the talk will highlight a range of AI/ML applications we have developed in recent years to enhance grid operation, planning, control, and security.

Biography: Meng Yue is currently leading the Grid Modernization and Security Group in the Interdisciplinary Science Department at Brookhaven National Laboratory (BNL). He received his Ph. D. from Michigan State University in electrical engineering. His major research interests include power system modeling, simulation, and control, and applications of AI/ML- and quantum machine learning and quantum computing in operation, planning, and security of the future grid.

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.

Location: CDS, Bldg. 725, Training Room

Join ZoomGov Meeting: https://bnl.zoomgov.com/j/1604383624?pwd=ffQ5cUPNxTI7nzClKQO6cnsNbhF9Vf.1

Meeting ID: 160 438 3624
Passcode: 558449

How Language Makes us Smart (without Big Data) presented by Charles Yang

Abstract: Language provides the glue that combines simpler concepts into complex ones. To study how language guides conceptual development, we need precise accounts of how rules are learned from the child's linguistic experience, which is extremely limited in comparison to the amount of data available to current machine learning methods. In this talk, I discuss a mathematical model of inductive generalization, which enables language learning with very small amount of data. Such a view of learning has strong implications for the cross-cultural/linguistic variation of development. As a case study, I show that Hong Kong children learning Cantonese, which has a relatively simpler formal counting system, develop understanding of symbolic numbers a full year ahead of English-learning children in the United States, which is precisely predictable from the learning model. The new conception of learning adds another wrinkle to the eternal question of how language and thought are related to each other.

Bio: Charles Yang studied at the MIT AI lab and now teaches linguistics, computer science and psychology and directs the Program in Cognitive Science at the University of Pennsylvania. He is the author of several books: The Price of Linguistic Productivity (2016 MIT Press) won the Leonard Bloomfield Award from the Linguistic Society of America. His honors include a Guggenheim fellowship.