Industrial Affiliates Annual Conference

This highlight event is regularly attended by IA Program Members alongside Statistics Department faculty and graduate students. Affiliates have an opportunity to meet the students and faculty, as well as giving short presentations: each one is a 25-minute informal talk introducing the speaker and their company, offering a discussion of the role of statistics within that company, or even posing a statistical problem of particular interest to that company or industry. We also feature many of the department's upper-cohort graduate students presenting their research.

Visit the Conference Series page to see our past events

Thursday, 6 November

9am to 4pm: On campus at our new Computing and Data Science Center, Room E160, 389 Jane Stanford Way

Draft Agenda

Time	Speaker
Session I — Jacqueline Meulman
9:05a	Tong Geng & Qing Zhang, Google: "Ad measurement and long-term effect of ads"
	Meeyoung Park & Chanhwa Lee, Google: “Lifetime-aware VM allocation”
	Henry Pascoe, Google: “Prediction-powered inference for measuring the prevalence of rare classes"
9:55a	Ivy Zhang: "Predicting data value before outcome collection"
10:20a	Morning Break
Session II — Guenther Walther
10:45a	Wenlong Ji: "Multi-armed bandits with machine learning-generated surrogate rewards"
11:10a	Yuanyuan Li, Munich Re: “Beyond accuracy: Quantifying error correlations in AI models”
11:35a	Rahul Kanekar: "Power properties and applications of graph-based two-sample tests"
12n	Lunch
Session III — Art Owen
1p	Maxime Cauchois, Two Sigma: “Forecasting financial returns with machine learning”
1:25p	Amber Hu: "Fast, reliable, and interpretable inference of latent dynamical systems"
1:50p	James Johndrow, Citadel: “Applications of ML in finance”
2:15p	Afternoon Break
Session IV — John Chambers
2:40p	Sophia Lu: "Efficient likelihood-free adaptive Bayesian inference"
3:05p	Pierre Demartines, BlackRock: “Alpha research in BlackRock Systematic”
3:30p	Yash Nair: "Diversifying conformal selections"
3:55p	Closing Remarks