Program Schedule
The conference will take place at the Multi-Purpose Room at the International Center unless otherwise noted in the schedule below.
Friday, April 28, 2023
9:00AM-9:30AM Breakfast
9:30AM-9:45AM Introduction
- Alexander Aue Chair, Department of Statistics
9:45AM-11:45AM Technical Session I: Biomedical Imaging and Statistics
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Chair: Xiucai Ding, Assistant Professor, UC Davis
- Hau-Tieng Wu, Professor, Departments of Mathematics, Duke University
- Jean Feng, Assistant Professor, Department of Epidemiology and Biostatistics, UC San Francisco
- Danielle Jenine Harvey, Professor, Department of Public Health Sciences, UC Davis
Keynote:
Title: "From Raw Data to Actionable Insights: Biorhythm Analysis with Modern Signal Processing Techniques for Clinical Use"
Speakers:
Title: "Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions"
Title: "Clinical Trials in Alzheimer’s Disease: How Data Science Can Help"
11:45AM-1:30PM Lunch
1:30PM-3:00PM Technical Session II: Computational Biology and Genomics
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Chair: Debashis Paul, Professor, UC Davis
- Hongyu Zhao, Professor of Biostatistics, Professor of Genetics, Statistics and Data Science, Yale School of Public Health
- Gerald Quon, Assistant Professor, Department of Molecular and Cellular Biology, UC Davis
Keynote:
Title: "Statistical methods for estimating cell-type-specific gene co-expressions using single cell and bulk RNA-seq data"
Speakers:
Title: "Integration of high dimensional, multimodal datasets to characterize the genetic basis of schizophrenia"
3:00PM-3:30PM Coffee Break
3:30PM-5:15PM Technical Session III: Causal inference
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Chair: Ruoqi Yu, Department of Statistics, UC Davis
- Michael Baiocchi, Associate Professor, Epidemiology and Population Health Department, Stanford University
- Erin Hartman, Assistant Professor, Department of Political Science, UC Berkeley
- Bulat Gafarov, Assistant Professor, Department of Agriculture and Resource Ecpnomics, UC Davis
Speakers:
Title: "How to tell the difference between machine learning and traditional (bio)statistics"
Title: "Kpop: A kernel balancing approach for reducing specification assumptions in survey weighting"
Title: "On Model Selection Criteria for Climate Change Impact Studies"
5:15PM-6:30PM Poster Session/Reception
6:30PM-8:30PM Banquet at Multi-Purpose Room and Patio at the International Center.
Saturday, April 29, 2023
9:00AM-9:30AM Breakfast
9:30AM-11:30AM Technical Session IV: Public Health and Disease Dynamics
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Chair: Shizhe Chen, Department of Statistics, UC Davis
- Bhramar Mukherjee, Professor, Departments of Biostatistics, Epidemiology, and Global Public Health, University of Michigan
- Yong Chen, Professor, Departments of Biostatistics, University of Pennsylvania
- James Zou, Assistant Professor, Departments of Biomedical Data Science, Stanford University
Keynote:
Title: "Analysis of Big Real-World Health Care Data: Promises and Perils"
Speakers:
Title: " Distributed statistical inference and its role in the era of networked real-world data"
Title: "Using generative AI for (data) science"
11:30AM-1:00PM Lunch
1:00PM-3:00PM Technical Session V: Statistical Learning and Networks
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Chair: Mina Karzand, Department of Statistics, UC Davis
- Giles Hooker, Professor, Department of Statistics, UC Berkeley
- H. Michael Zhang, Professor, Department of Civil and Environmental Engineering, UC Davis
- Iman Soltani, Assistant Professor, Department of Mechanical and Aerospace Engineering, UC Davis
Keynote:
Title: "V-Statistics and Variance Estimation: Inference for Random Forests and Other Ensembles"
Speakers:
Title: "Should California increase the speed limits of its highways?"
Title: "data-efficient learning in automation and industrial diagnosis"
3:00PM-3:30PM Coffee Break
3:30PM-5:10PM Alumni and Postdoc
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Chair: Jairo Fúquene-Patiño, Assistant Professor, UC Davis
- Minjie Fan, Machine Learning Engineer and Tech Lead at the Google
Shopping Ads team
- Chao Shen, Applied Scientist at Amazon Sponsored Brands
- Xiongtao Dai, Assistant Professor in the Division of Biostatistics, School of Public Health, UC Berkeley
- Seung Yong Hwang, Senior Biostatistician, GRAIL
Speakers:
Title: " Machine Learning in Recommendation Systems – a case study of Google Shopping Ads"
Title: "Machine learning in Amazon Advertising"
Title: "Tukey's Depth for Non-Euclidean Objects"
Title: "Diffusion-Weighted MRI: Exploring White Matter Fiber Tracts in the Brain"