BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//VA Women in HPC - ECPv6.1.0.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:VA Women in HPC
X-ORIGINAL-URL:https://va-whpc.org
X-WR-CALDESC:Events for VA Women in HPC
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260318T130000
DTEND;TZID=America/New_York:20260318T140000
DTSTAMP:20260909T015230
CREATED:20260305T200634Z
LAST-MODIFIED:20260319T183449Z
UID:7128-1773838800-1773842400@va-whpc.org
SUMMARY:Save the Date: AI in HPC Panel
DESCRIPTION:Topic: VA-WHPC Panel: AI in HPC \nThank you for those who joined us for our March 2026 speaker panel where three researchers shared their experiences and thoughts on artificial intelligence (AI) in High-Performance Computing (HPC). Each speaker gave a 10-minute presentation on how AI is used in HPC environments\, their experiences and views on AI in research computing\, how HPC infrastructure can support AI workloads\, and the practical lessons\, opportunities\, and challenges they have encountered. After the presentation\, there was time for questions and discussion.  \n			\n						Watch the Recording\n					 \nPresenters: \n• Dr. Vijeta Sharma is a High Performance Computing and Artificial Intelligence (HPC-AI) scientist with over 15+ years of R&D experience in both industry and academia. She holds a master’s degree in Data Science and a PhD in the convergence of Artificial Intelligence and High-Performance Computing (HPC). She is actively engaged in Research\, Teaching\, and the mentorship. She is deeply involved in international collaborations for research\, workshops\, conferences\, and knowledge dissemination. Her core research interests span Artificial Intelligence\, Computer Vision (image & video processing)\, Human Action Recognition\, Deep Learning\, Large Vision Models (LVM)\, High-Performance Computing (HPC)\, Embodied AI\, and Robotics. Specifically\, in AI on HPC\, her passion lies in AI model parallelisation across accelerators such as CPU\, GPU\, and TPU – a central theme of her research work. She has delivered 40+ invited talks on international platforms\, including as a keynote speaker. She is an active member of Women in HPC (WHPC). Beyond technology\, she is also recognised as a woman leader and recipient of the Global Women Leadership 2022 award\, honouring her inspiring contributions to women in science and leadership. \n\nDr. Bruce Rushing is a Research Scientist within the Data Analytics Center (DAC). The DAC provides machine learning (ML) and artificial intelligence (AI) analytics to UVA researchers as a core part of its mission. Dr. Rushing has expertise in ML and AI\, with an emphasis on generative probabilistic modeling\, deep learning with neural networks\, and large language models (LLMs). His previous work at the DAC includes probabilistic models for glaucoma patient trajectories\, next-image segmentation and generation with time-series MRI data\, and LLM fine-tuning for modeling semantic shifts in scientific descriptions of American wildlife. Previously\, he conducted foundational research on ML\, statistics\, LLMs\, and causal discovery as a Postdoc at Purdue University’s Virtual Reality and Artificial Intelligence lab. He is a trained computational philosopher and statistician\, and he has a PhD in Philosophy and MA in Mathematical Behavioral Sciences from the University of California\, Irvine\, where his dissertation focused on the decision-theoretic foundations for Bayesian and causal inference. His research interests focus on the foundations of statistics and causal modeling and scientific theorizing that emphasize building algorithms for reliable induction.• Dr. Jie Ren is an Assistant Professor of Computer Science at William & Mary. She received her Ph.D. from the University of California\, Merced\, from PASA Lab and received her B.S. degree from the Beijing Institute of Technology. Her research interests span operating systems\, computer architecture\, and their intersection with machine learning and high-performance computing. Her research aims to improve the performance and resource efficiency of heterogeneous computing systems while making it easier for users to deploy and manage their applications. Her publications appear in top conferences such as SC\, PPoPP\, HPCA\, FAST\, and NeurIPS. 
URL:https://va-whpc.org/event/save-the-date-ai-in-hpc-panel/
LOCATION:Virtual Event
END:VEVENT
END:VCALENDAR