About us
The University of San Francisco Data Science & Artificial Intelligence Speaker Series is produced by the Data Institute. This group brings researchers and practitioners together with students in the MS in Data Science and Artificial Intelligence graduate program, faculty, and interested members of the public to discuss topics of interest in analytics and data science.
Talks take place in person on Fridays from 12:30–2:00 pm at the USF Downtown San Francisco campus, located at 101 Howard Street in the East Cut neighborhood, at the heart of San Francisco’s downtown innovation corridor. We encourage attendees to bring their lunch and join us for these mid-day conversations.
Talk recordings are made available subject to speaker permission. You can find the recorded talks at https://www.youtube.com/channel/UCN0kf0sI01-FXPZdWAA-uMA
Upcoming events
2
Foundations of Distributed Training: How Modern AI Systems Are Built
101 Howard St, University of San Francisco - Downtown Campus, San Francisco, CA 94105, San Francisco, Ca, USWe are excited to welcome Suman Debnath, Technical Lead in Machine Learning at Anyscale, for a practical and intuitive introduction to distributed training.
Talk Description:
As modern AI models continue to grow, single-GPU training is no longer enough. Distributed training has become essential, but scaling models introduces challenges that require understanding communication patterns, system bottlenecks, and key trade-offs.
In this session, we will break down distributed training from first principles. We will explore why single-GPU training hits limits, how transformer models manage memory, and what techniques like gradient accumulation, checkpointing, and data parallelism actually do.
We will also demystify communication primitives, walk through ZeRO-1, ZeRO-2, ZeRO-3 and FSDP, and show how compute and communication can be overlapped for better efficiency. Finally, we will connect these concepts to real-world tooling used in frameworks like Ray and PyTorch. Attendees will gain a clear, grounded understanding of how distributed training works and when to apply different strategies.Bio:
Suman Debnath is a Technical Lead in Machine Learning at Anyscale, where he works on large-scale distributed training, fine-tuning, and inference optimization in the cloud. His expertise spans Natural Language Processing, Large Language Models, and Retrieval-Augmented Generation.
He has also spoken at more than one hundred global conferences and events, including PyCon, PyData, and ODSC, and has previously built performance benchmarking tools for distributed storage systems.We look forward to seeing you!
#DataScience #MachineLearning #DistributedTraining #Ray #PyTorch #LLM #RAG #DeepLearning #USFCA #USFMSDSAI #DataInstitute #AIEngineering #TechTalk
54 attendees
Finding Leverage with AI: Building More with Fewer People
101 Howard St, University of San Francisco - Downtown Campus, San Francisco, CA 94105, San Francisco, Ca, USWe are excited to welcome Punn Kamolyabutr for an upcoming Data Science Speaker Series talk.
Punn is the CTO and co-founder of Conduit (Y Combinator W24), a platform for building conversational AI automations. Previously, he worked on AI at Google, built systems at a crypto lending protocol, and worked as a trader at a private wealth fund.
While many AI talks focus on technology, this session focuses on what AI enables: massive leverage for small teams. Punn will share how a small engineering team supports a platform sending millions of messages and hundreds of thousands of calls each week, how AI is reshaping team structures across engineering and non-engineering roles, and why leading companies are hiring fewer but sharper people.
This talk is especially relevant for students interested in startups, early-stage teams, and understanding how the technical job market is evolving.
Join us and be part of the discussion.
#USFCA #USFMSDSAI #DataInstitute #DataScience #ArtificialIntelligence #Startups #AIEngineering #TechTalk #StartupCareers #EarlyStageStartups
21 attendees
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