Fall 2025, Mondays 2 to 3:20 pm, NCS 220 and Zoom link to be announced soon.

The seminar will be jointly taught by Prof. Dimitris Samaras samaras@cs.stonybrook.edu.

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 Ph.D. 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. Registered students must attend in person. Up to 3 absences will be excused. Everyone else is welcome to attend.
Department of Ecology and Evolution Colloquium Arthur Porto is Assistant Curator of Al for Biodiversity at the Florida Museum of Natural History. His research sits at the intersection of evolutionary biology, computer vision, and machine learning, with a focus on developing open, scalable methods for extracting biological information from images and natural- history collection objects. Life Sciences Building, Room 038

To truly understand human language, we must look at words in the context of the human generating the language. Factors such as demographics, personality, modes of communication, and emotional states have shown to play a crucial role in NLP models pre-LLMs era. Steps of mathematically defining the inclusion of human context in language modeling and more will be discussed with Nikita Soni, a PhD student at Stony Brook University co-advised by H. Andrew Schwartz and Niranjan Balasubramanian. She is the lead organizer of the workshop on human-centered large language modeling.

Please register for the STEM Speaker Series Zoom event here

Please RSVP for the STEM Speaker Series in-person event here
Title:Deep Contextual Modeling for Natural Language Understanding, Generation, and Grounding Zoom instructions: Join Zoom Meeting https://stonybrook.zoom.us/j/645050299?pwd=TVJVRkc3dlhxdDF5d00xWGlDQkovZz09 Meeting ID: 645 050 299 Password: 810247 One tap mobile +16468769923,,645050299#,,#,810247# US (New York) +13126266799,,645050299#,,#,810247# US (Chicago) Dial by your location +1 646 876 9923 US (New York) +1 312 626 6799 US (Chicago) +1 301 715 8592 US +1 346 248 7799 US (Houston) +1 408 638 0968 US (San Jose) +1 669 900 6833 US (San Jose) +1 253 215 8782 US Meeting ID: 645 050 299 Password: 810247 Find your local number: https://stonybrook.zoom.us/u/aemTiJMXu6 Abstract: Natural language is a fundamental form of information and communication. In both human-human and human-computer communication, people reason about the context of text and world state to understand language and produce language response. In this talk, I present several deep neural network based systems that first understand the meaning of language grounded in various contexts where the language is used, and then generate effective language responses in different forms for information access and human-computer communication. First, I will introduce Speaker Interaction RNNs for addressee and response selection in multi-party conversations based on explicit representations for different discourse participants. Then, I will present a text summarization approach for generating email subject lines by optimizing quality scores in a reinforcement learning framework. Finally, I will show an editing-based multi-turn SQL query generation system towards intelligent natural language interfaces to databases. Bio:Rui Zhang is a final year Ph.D. student at Yale University advised by Professor Dragomir Radev. His research interest lies in various natural language processing problems in understanding, generation, and grounding. He has been working on (1) End-to-End Neural Modeling for Entities, Sentences, Documents, and Multi-party Multi-turn Dialogues, (2) Text Summarization for Emails, News, and Scientific Articles, (3) Cross-lingual Information Retrieval for Low-Resource Languages, (4) Context-Dependent Text-to-SQL Semantic Parsing in Human-Computer Interaction. Rui Zhang has published papers and served as Program Committee members at top-tier NLP and AI conferences including ACL, NAACL, EMNLP, AAAI, CoNLL. During his Ph.D., He has done research internships at IBM Thomas J. Watson Research Center, Grammarly Research, and Google AI. He was a graduate student at the University of Michigan and got his bachelor's degrees at both the University of Michigan and Shanghai Jiao Tong University from the UM-SJTU Joint Institute.
ICB&DD 19th Annual Symposium

Iwao Ojima, Director, ICB&DD
Ivet Bahar Chair, Organizing Committee
Dima KozakovCo-Chair, OrganizingCommittee

There will be poster sessions on projects conducted in the ICB&DD member's laboratories aswell as other laboratories in the area. Awards will be given to the best three posters.

Please see the link for the registration and poster sessions in:
https://www.stonybrook.edu/commcms/icbdd/https://forms.gle/Wh4UzVx9U4HWStXb8

The AI Community at Stony Brook University is proud to announce Datathon 2026.

Dive into data analysis and AI/ML, and get ready to build something big. In this year's underwater-themed event, enjoy a weekend of data analysis, hacking, networking, fun activities, and minigames.

Whether you're a seasoned developer, data scientist, designer, or completely new to hacking, this event is your chance to collaborate, learn data science, and create something impactful with data and AI/ML.

What is Datathon?

AI Community's Datathon is the premier data science competition at Stony Brook University, bringing together students of all skill levels for a weekend of data exploration, analysis, and innovation. Just like a typical hackathon, you will be using your skills to build your dream project.

Unlike a regular hackathon, Datathon is focused on data science. You will be given a set of data to work with, analyze, and apply to your project. You can also find your own data to use. Your project will be presented to a panel of judges consisting of professors and industry professionals!

Who Can Participate

  • Students of all skill levels and majors are welcome.
  • Come with a team or find one at the event or on Discord.
  • This event is open to SBU and non-SBU students.

* Non-SBU Undergraduate Students are ineligible to receive prizes
* You must be 18+ or older (Excludes minors who are active SBU students)

Location: SAC Ballroom B

Register here.

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.

The AI Innovation Institute cordially invites you to the Summer Symposium this Friday, July 31st, from 10:00 AM to 12:00 PM in the Stony Brook Union Ballroom.



Poster Presentations: 10:00 - 11:30 am - Union Ballroom
Closing remarks: (11:25) Dr. Carl Lejuez, Executive Vice President & Provost
Group Photos (11:30-12)

Featuring undergraduate researchers/participants of the following:
  • AI Innovation & Diffusion Research Experience for Undergraduates (REU)
  • Explorations in STEM
  • Frances Velay Fellowship Program
  • Oncology Research and Clinical Learning Experience (ORACLE)
  • SUNY EOP
  • SUNY SOAR
  • URECA REACT/Research Entry Accelerator for College Transfers
  • URECA Summer

Join us in celebrating the hard work and accomplishments of our students.

Learn how SBU staff are using AI.

Over the past year, we've explored the AI tools and services available at Stony Brook. Now it's time to hear from colleagues who are putting these tools to work in their everyday roles. Join Tamara Gregorian, Herb Schramm, and Allie Seal moderated by David Ecker as they share how they use AI in their position, the tasks it helps them accomplish and the lessons they've learned along the way. This session is an opportunity to see practical examples, ask questions, and gather ideas that you can apply in your own work.

Register here.

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, November 26, 2024, 12:00 pm -- CDS, Bldg. 725, Training Room

Speakers

Hanfei Yan, NSLS-II

David Park, CDS, AI Dept

Xihaier Luo, CDS, AI Dept

Join Zoom Meeting

https://bnl.zoomgov.com/j/1601052863?pwd=eIX9qZKPGNtQ11uwbK8JP5hIdIxA3V.1

Meeting ID: 160 105 2863

Passcode: 442980