AI + Music Seminar - The meeting will consist of introductions and organizational discussions, aimed at understanding participants' interests. We'll discuss what the seminars can focus on going forward.
The Renaissance School Of Medicine Department of Scientific Affairs and its Single Cell Genomics facility are excited to host a special seminar and discussion on AI and single cell genomics analysis:

With the decreasing cost of sequencing, many biobanks and large research cohorts have moved to whole genome sequencing (WGS) and single-cell RNA-seq. However, making use of this deluge of data remains a challenge. I will discuss statistical and deep learning approaches that we are exploring to address the challenge of noncoding variant interpretation, including our work as part of the Alzheimer's disease sequencing project.

Speaker: David A. Knowles, PhD. Asst. Professor of Computer Science, Interdisciplinary Appointee in Systems Biology, Columbia University Core Faculty Member, New York Genome Center

Join us in person: Health Science Tower Level 3, Lecture Hall 5

OVERVIEW


This workshop, Expanding Horizons in AI with HPC, aims to explore the dynamic intersection of AI and HPC, focusing on how advanced computing can accelerate AI research and applications. As AI models become more complex and data-intensive, traditional computing systems struggle to meet the demand for scalability, efficiency, and speed. HPC offers a solution by providing the necessary infrastructure for training large-scale models, enhancing AI algorithms, and enabling breakthroughs in fields such as deep learning, natural language processing, and autonomous systems.

Through a combination of expert presentations and panel discussions, participants will gain insights into the latest developments in AI-HPC integration. Attendees will also engage in discussions on the future trends, challenges, and ethical considerations surrounding the use of HPC in AI.

The workshop is designed for AI researchers, data scientists, engineers, and HPC professionals seeking to enhance their understanding of how high-performance computing can drive innovation and expand the potential of AI in solving complex, real-world problems.

The workshop will be held at the Wang Center at Stony Brook University.

https://you.stonybrook.edu/hpcai/

PROGRAM

The program features sessions on HPC Architectures for AI, AI Applications in HPC, LLM's in HPC, and AI in HPC Workflows, and open student presentations. The tentative program and list of confirmed speakers is available at https://you.stonybrook.edu/hpcai/program/.

CALL FOR STUDENT PRESENTATIONS & PARTICIPATION

We are excited to offer students the opportunity to present their work in the area of high-performance scientific computing and artificial intelligence at the workshop. We are calling for students to submit their talk proposals (Name + Title) by April 15 to hpc_ai_workshop@stonybrook.edu. The committee will select the best submission to be presented at the workshop. Accepted speakers will be notified by April 22, 2025.

All students, regardless of whether they are presenting, may reach out to hpc_ai_workshop@stonybrook.edu for financial support to cover travel and lodging costs.

REGISTRATION

Registration is available at https://www.eventbrite.com/e/expanding-horizons-in-ai-with-hpc-tickets-1256469978529?aff=oddtdtcreator until May 2nd. The registration fee covers the workshop participation and the social event in the evening of May 9.

Regular registration: $200
Student registration: $100


IMPORTANT NOTE

The registration fee was meant to cover the room rent, catering, and dinner. Thanks to an RF seed grant, we are able to drop the registration fees for SBU students and staff/faculty. We still ask for an informal registration via email to hpc_ai_workshop@stonybrook.edu until April 27, so we can plan for catering and dinner.
Please get in touch with us if you have already registered as an SBU student/faculty/staff member for the workshop so we can handle any reimbursement.

The program is now online at https://you.stonybrook.edu/hpcai/program/.
Mind Brain Lecture: Constructing the World of Taste in Your Head You fork the morsel into your mouth and say yum...chocolate cake. The appreciation of your dessert's taste seems to follow directly, quickly and simply from the placement of the food on your tongue. The truth, however, is far more interesting and complex: your brain actually begins determining whether you will enjoy a bite of food even before the fork approaches your mouth and continues to work the problem well after. Information about your food's color, smell, texture and taste activates multiple parts of your brain, where that information collides with your pre-mouthful beliefs about how it should taste. The coming-together and shuffling of that information around the brain takes time, as networks of neurons work together to help you decide whether the morsel in your mouth is worth swallowing. Referring to work from psychology, biology and computational neuroscience, Professor Katz will de-mystify and reveal the beauty of these complexities of the neuroscience of taste. Donald Katz, Professor of Psychology, Departments of Neuroscience, Psychology, and the Volen National Center for Complex Systems, Brandeis University Free presentation intended for a general audience. Reception to follow. https://www.stonybrook.edu/commcms/mind/

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.
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 Stony Brook Computing Society presents an exciting event featuring experts from Google (Danny Rosen - Technical Program Manager) and NVIDIA (Veer Mehta - Senior Solutions Architect), diving into the latest developments in generative AI. Learn how these industry leaders are shaping the future of technology and explore new ideas in a relaxed, engaging setting.

📍 Location: Frey 102
📅 Date: Monday, Nov 11
⏰ Time: 12 PM - 1:50 PM

Scan the QR code or register in the link.
Moderated by Katherine Lucente, BS in Nursing Candidate at Stony Brook University
  • Lav Varshney, PhD, MS, BS - Director of the AI Institute at Stony Brook University
  • Meghan Reading Turchioe, PhD, MPH, RN, FAHA - Nurse Scientist at Columbia University
  • Briana Shiri Last, PhD - Department of Psychology at Stony Brook University

This event is proudly sponsored by the Stony Brook University School of Nursing, the Stony Brook University Hospital Division of Nursing, and the Sigma Theta Tau Kappa Gamma Chapter.
Abstract: In today's digital era, language functions not only as a medium of information transmission but also as a mechanism of persuasion, framing, and control. The proliferation of online platforms has amplified this dual role: while enabling unprecedented access to knowledge, it has also exacerbated challenges such as misinformation, rhetorical manipulation, and cultural or linguistic disparities in information access. As a result, pragmatic language understanding and information integrity have emerged as central concerns for both computational linguistics and society at large. This research follows how claims are produced, reframed, and contested online through three interconnected threads. First, it models pragmatic deflection in discourse by investigating whataboutism, a rhetorical device that deflects criticism by redirecting discourse, and introduced novel datasets from Twitter (now X) and YouTube. This work underscores how subtle pragmatic maneuvers can erode discourse integrity without relying on outright falsehoods. Second, it advances retrieval and alignment for information integrity in health and news communication. These systems trace claims and narratives across genres (e.g., social posts and news reports) and languages (Chinese and English), linking social posts with journalistic reporting and aligning Chinese news with English biomedical evidence. By accounting for cultural context, assertions can be linked to reliable evidence and organized for systematic comparison. This work surfaces the risks of missing sources, unverifiable claims, and framing disparities in global health discourse, and demonstrates computational solutions that enhance both the credibility and accessibility of information. Third, the methodological centerpiece is Class Distillation (ClaD), a geometry-aware training paradigm for distilling a small, well-defined target class from a large, heterogeneous background. ClaD couples a distribution-aware contrastive loss (instantiated here in a Mahalanobis form when its assumptions fit the data) with an interpretable decision algorithm tuned for class separation. Evaluated on sarcasm, metaphor, and sexism detection, ClaD delivers strong efficiency and robustness, matching or surpassing larger models while using fewer computational resources, making these pipelines practical by learning reliably from small, sharply defined classes. In sum, this research presents an integrated account of language understanding in the digital age. It exposes how integrity falters through pragmatic deflection, cross-genre drift, and cross-lingual misalignment, and translates these insights to move pragmatic language understanding to systems for evidence retrieval, alignment, and verification; and it sheds light on where and how integrity is threatened, and delivers methods that leverage pragmatic language use.

Speaker: Chenlu Wang

Location: (Old) Computer Science Building, Room 2311