NeurIPS 2020 - Thirty-fourth Conference on Neural Information Processing Systems - https://nips.cc/
Join us to share your thoughts about teaching, learning, and AI!
The landscape of higher education is rapidly evolving with the integration of Artificial Intelligence (AI). Through the Institute on AI, Pedagogy, and the Curriculum with AAC&U, we are exploring ways that we can better address AI in teaching and learning. We want to hear your experiences, your concerns, and your ideas.
This is an open discussion for all faculty and staff to share their perspectives on the opportunities and challenges AI presents in our academic environment.
We'll be exploring critical questions like:
In the age of AI, what are the opportunities you see for enriching the classroom and curriculum? How can it enhance student learning or your professional practice?
What are the most significant challenges and concerns that AI raises for you regarding academics, student integrity, or your workload?
What resources (tools, training, technical support, policy guidance, etc.) do you need to feel confident and successful in the age of AI?
Dates/Times:
Tuesday, 2/3 at 2pm
Friday, 2/6 at 9:30am
Please register in advance for the Zoom link.
Can't Make It? Share Your Feedback!
We understand schedules are tight. If you cannot attend the live discussion, you can still share your thoughts! Join our AI Zoom Room to share your thoughts via video recording or email rose.tirotta-esposito@stonybrook.edu with your comments and ideas.
Videos will not be shared publicly and comments will only be shared in aggregate.
Your input is vital. From pedagogy to assessment, your insights will be critical. We look forward to a thoughtful and productive conversation!
Dr. Rose Tirotta-Esposito (Assistant Provost; Director of CELT)
Dr. Elizabeth Hewitt (Associate Professor in the Department of Technology and Society (DTS) in the College of Engineering and Applied Sciences)
Chris Kretz (Associate Librarian and Head of Academic Engagement at SBU Libraries)
Prof. Rajiv Lajmi (Assistant Professor in the School of Health Professions and Chair of Applied Health Informatics)
Dr. Matthew Salzano (Assistant Professor in the Department of Communication in the School of Communication and Journalism)
AI3, SBU Libraries and IACS present
at International Love Data Week
sponsored by The Office of the Provost and
Educational and Institutional Effectiveness (EIE)
Special Talk and Panel Discussion
How I Learned to Stop Worrying and Love AI (For Now)
with Paul Fain from The Job and Work Shift
A reporter's take on what we know--and what we don't know--about AI's emerging impacts on the labor market. The discussion will include the latest research from economists and the AI labs themselves about how workers are using AI, and current thinking among experts on how the tech's rapid deployment will play out across job roles, industries, and regions.
Limited Seats!
Registration is required.
at International Love Data Week
sponsored by The Office of the Provost and
Educational and Institutional Effectiveness (EIE)
Special Talk and Panel Discussion
How I Learned to Stop Worrying and Love AI (For Now)
with Paul Fain from The Job and Work Shift
A reporter's take on what we know--and what we don't know--about AI's emerging impacts on the labor market. The discussion will include the latest research from economists and the AI labs themselves about how workers are using AI, and current thinking among experts on how the tech's rapid deployment will play out across job roles, industries, and regions.
Panel discussion to follow with:
- Lav Varshney, Della Pietra Infinity Professor and inaugural director of the AI Innovation Institute
- Nicholas Johnson, Director of AI, SBU Libraries
- Marianna Savoca, Associate Vice President for Career Readiness and Experiential Education
Limited Seats!
Registration is required.
How do you get the most out of generative AI? Stop by the library Galleria outside of the Central Reading Room to learn more! Librarians Chris Kretz and Ahmad Pratama, along with David Ecker of DoIT, will be demonstrating tools and tips for writing prompts that make the most of what AI can do. And they'll be hosting Explore AI demos this Monday - Wednesday (March 3rd-5th) 12:30 - 1:30. Whether you're new to AI or a current user, they'd love to talk to you about it.
Location: Melville Library Galleria
Location: Melville Library Galleria
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/
Meeting ID: 160 105 2863
Passcode: 442980
Abstract: In this talk, we will discuss what a CS PhD entails and the traits and habits that are important for success in PhD programs and future careers. While the talk is targeted to first-year PhD students, PhD students at all levels should derive from it.
Bio: Samir Das is a professor in the Department of Computer Science at Stony Brook
University. He is currently serving as the department chair. He is well recognized in the
community for his research in wireless networks and systems.
Location: NCS120
Bio: Samir Das is a professor in the Department of Computer Science at Stony Brook
University. He is currently serving as the department chair. He is well recognized in the
community for his research in wireless networks and systems.
Location: NCS120
NLP Reading Group | Fall 2025
The Natural Language Processing Reading Group at Stony Brook University meets weekly to discuss recent research papers in NLP and related fields.
Join the Google Group here.
The Natural Language Processing Reading Group at Stony Brook University meets weekly to discuss recent research papers in NLP and related fields.
Join the Google Group here.
Virtual Talk: Contextual Modeling for Natural Language Understanding, Generation and Grounding by Rui Zhang
Zoom link to come.
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 PhD 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 and CoNLL. During his PhD, 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.
Zoom link to come.
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 PhD 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 and CoNLL. During his PhD, 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.
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.
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.
Experiencing Machine Learning in Collider-Accelerator Control System
Abstract: The Relativistic Heavy Ion Collider (RHIC) at Collider-Accelerator Department (C-AD) of BNL provides the world's only high-energy polarized proton beam. It is in the unique position to study where nuclei obtain their spin. During 25 years of operation at RHIC, the C-AD controls group has developed its own control system to tune the accelerator performance, which contains millions of control points. The successful operation of this system will highly affect the machine performance. RHIC's successor, the Electron-Ion Collider (EIC), will be one of the most complex scientific instruments ever built, with the capability of colliding polarized proton and electron beams. The increasing complexity of instruments will require new, sophisticated control methods/tools to tune and optimize the accelerator performance. In this talk, I will summarize some projects developed in recent years that utilize machine learning in the C-AD controls group.
Biography: Dr. Yuan Gao is an assistant scientist at the Collider-Accelerator Department (C-AD) at Brookhaven, primarily working on developing new machine learning schemes in the control group to enhance system performance. His research interests include game theory, algorithm design, anomaly detection, and simulation modeling.
Location: CDS, Bldg. 725, Training Room
Join ZoomGov Meeting: https://bnl.zoomgov.com/j/1604302440?pwd=0x2I95PIvbkkzIi6rA0MNnon5k2sux.1
Meeting ID: 160 430 2440
Passcode: 478223
The SUNY Office of Research, Innovation & Economic Development (ORIED) is hosting a webinar, Pathways to Innovation: Exclusive STEM Opportunities for Students at Premier Labs, with the Air Force Research Laboratory (AFRL), the Griffiss Institute and Brookhaven National Laboratory (BNL).
Please join us on October 30 from 12:30 - 2:00 pm to learn more about the labs and the wide variety of research, education, and workforce development programs they offer.
Register here: https://rfsuny.zoom.us/webinar/register/WN_fjWNU9l8Sr6WO_M3AoZ-Rw?mc_cid=50c2045945&mc_eid=357e15f9df#/registration
Please join us on October 30 from 12:30 - 2:00 pm to learn more about the labs and the wide variety of research, education, and workforce development programs they offer.
Register here: https://rfsuny.zoom.us/webinar/register/WN_fjWNU9l8Sr6WO_M3AoZ-Rw?mc_cid=50c2045945&mc_eid=357e15f9df#/registration