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
4
The Industrialization of Search: Scaling Distributed Systems for a billion users
101 Howard St, University of San Francisco - Downtown Campus, San Francisco, CA 94105, San Francisco, Ca, USWe are happy to welcome Avirek Ghatia to the USF Data Science Speaker Series.
Everyone can build a search bar. The real challenge is building one that serves billions of users in less than a second.
At large scale, search is not only about algorithms. It is about building the infrastructure that makes those algorithms work reliably and efficiently. When systems operate at this level, even a one percent inefficiency can translate into millions of dollars in operational costs or noticeable delays that impact the user experience.
In this session, Avirek will share lessons from building search systems that operate at global scale. He will explain the concept of the multi-stage retrieval funnel, explore how modern search systems go beyond simple keyword matching, and discuss the trade-offs required to balance performance, cost, and user experience across different search use cases.
About the Speaker
Avirek Ghatia is a Staff Software Engineer at Slack, where he works on the infrastructure and distributed systems behind global enterprise search. He previously worked on search systems at TikTok, focusing on solving hyper-scale search challenges.
Avirek holds a Master of Science in Computer Science from New York University and brings more than a decade of experience building large-scale systems, from early Internet of Things platforms to modern semantic search infrastructure.We hope you can join us.
#DataScience #SearchSystems #DistributedSystems #MachineLearning #SoftwareEngineering #USFCA #USFMSDSAI #DataInstitute #TechTalk #BigData
28 attendees
Quantifying our confidence in neural networks and AI
101 Howard St, University of San Francisco - Downtown Campus, San Francisco, CA 94105, San Francisco, Ca, USWe’re thrilled to welcome back Josh Starmer back to the USF Data Science Speaker Series!
Description: Although Large Language Models and AI are known to generate false and misleading responses to prompts, relatively little effort has gone into understanding how we can quantify the confidence we should have in the output from these models. In this seminar, I will illustrate the problem using a simple neural network and then demonstrate two methods for quantifying our confidence in the model outputs. I will then show how these methods can be applied to Large Language Models and AI.
About the Speaker: Josh Starmer is the person behind the popular YouTube channel, “StatQuest with Josh Starmer.” Since 2016, Josh has used an innovative and unique visual style to clearly explain Statistics, Data Science and Machine Learning concepts and algorithms to curious people all over the world. Rather than dumb down the material, Josh brings people up with simple examples worked through, step-by-step, using pictures to make sure every main idea is easy to understand and remember. By breaking down even the most complicated algorithms into bite sized pieces, StatQuest has helped people, all over the world, win data science competitions, pass exams, graduate from school, and get jobs and promotions.
RSVP now to secure your spot!
#USFCA #USFMSDSAI #DataInstitute #DataScience #MachineLearning #ArtificialIntelligence #LLM #StatQuest #TechTalk
27 attendees
Building Systems That Matter: An Ethical Framework for Data & AI
101 Howard St, University of San Francisco - Downtown Campus, San Francisco, CA 94105, San Francisco, Ca, USWe are excited to welcome David Schoeller-Diaz, USF Class of 2006 alumnus and global program leader, for a special session on practical ethics in data science and artificial intelligence. This talk complements our cohort’s ethics module and the USF Data Science Speaker Series.
Talk Description: Most ethical decisions in data science are not dramatic dilemmas. Rather, they are embedded in everyday choices about how we formulate problems, what we include or exclude from our data, and who bears the consequences of our models. In this interactive session, David will share a practitioner's framework for ethical reasoning drawn from 20 years of building data-driven systems in complex, high-stakes environments, from cybersecurity operations protecting hospitals and NGOs to geospatial intelligence analysis and data systems that informed a national peace process. The session will explore how these experiences connect to the ethical challenges data scientists face today: AI governance and accountability, the concentration of power in the AI ecosystem, and the question of how to build technology that serves broad human flourishing. Rather than treating ethics as a constraint on technical work, this talk argues that ethical judgment is a dimension of professional craft, making data scientists more effective, more trusted, and more durable in their careers. Expect an interactive format with live polls, real-world scenarios, and open discussion throughout.
About the Speaker: David Schoeller-Diaz is a global program leader and systems builder with 20 years of experience leading data-driven operations across humanitarian, security, and technology sectors. His career spans intelligence analysis for U.S. Southern Command, humanitarian information management with iMMAP and the United Nations, cybersecurity partnerships at the CyberPeace Institute, academic research at the Harvard Humanitarian Initiative, and co-founding a social enterprise in Colombia. He holds a Master of Arts in Law and Diplomacy from The Fletcher School at Tufts University, an Executive Master in International Business from ESCP Business School, a PMP certification, an Executive Data Science Certificate from Johns Hopkins University, and a BA in Political Science from USF, where he was a McCarthy Fellow. David is based in the San Francisco Bay Area.
This talk is especially relevant for students interested in responsible artificial intelligence, trust and safety, policy, and governance.
We hope you can join us.
#DataScience #ResponsibleAI #AIEthics #AIGovernance #TrustAndSafety #USFCA #USFMSDSAI #DataInstitute #TechForGood #Cybersecurity #DataScienceSpeakerSeries16 attendees
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