Recent Workshops in Biostatistics: Fall 2022

DATE INVESTIGATOR PRESENTATION TITLE

9/29

 

Ajit Johnson Nirmal

The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution

Abstract and suggested readings

PDF Flier

10/6

Roxana Daneshjou

Precision health for all: developing inclusive datasets and algorithms

Abstract and suggested readings

PDF Flier

10/13

 

Lynn Petukhova

Leveraging Information in the Human Genome to Improve Skin Health and to Advance the Practice of Dermatology

Abstract and suggested readings

PDF Flier

10/20

DBDS SEMINAR
 Lee Hood

Data-Driven Science of Wellness and Prevention: A 2nd Human Genome Project

Abstract and suggested readings

PDF Flier

10/27

 

Adrian Buganza Tepole  Data-driven skin biophysics  

Abstract and suggested readings

PDF Flier

11/3

 

David Van Valen

Everything as Code

Abstract

PDF Flier

11/10

 

Liana Lareau

Revealing patterns of alternative splicing in single cells

Abstract

PDF Flier

11/17

Lorin Crawford


Machine Learning for Human Genetics: A Multi-Scale View on Complex Traits and Disease

Abstract

PDF Flier

12/1



Marina Sirota


Leveraging Molecular and Clinical Data to Improve Women’s Health in the Era of Precision Medicine

Abstract

PDF Flier

12/8

Lior Pachter

Fireside chat with Lior Pachter, moderated by Barbara Engelhardt

More info

Recent Workshops in Biostatistics: Spring 2022

DATE INVESTIGATOR PRESENTATION TITLE

3/31

 

Matthew Jones, Bioinformatics PhD candidate at UC San Francisco and UC Berkeley, advised by Jonathan Weissman and Nir Yosef

Algorithmic tools for single-cell lineage tracing to illuminate the phylodynamics, plasticity, and transcriptional paths of tumor evolution

Abstract & Suggested Readings (PDF)

4/7

Virtual Access Only 

Dianbo Liu, PhD, Postdoc fellow and leader of humanitarian AI team, Prof. Yoshua Bengio Group, Mila -Quebec AI institute, Canada, and Research affiliate, The Broad Institute of MIT and Harvard, USA 

 

Improve accessibility and fairness in healthcare using generalizable artificial intelligence

Abstract & Suggested Readings (PDF)

4/14

 

 

Jennifer Listgarten, PhD, Professor, UC Berkeley Department of Electrical Engineering and Computer Science and Center for Computational Biology

Machine Learning-Based Protein Engineering

Abstract (PDF)

4/21

 

DBDS Seminar Series

Collin M. Stultz
, MD, PhD, Nina T. and Robert H. Rubin Professor in Medical Engineering and Science, Professor of Electrical Engineering and Computer Sciecne, Harvard-MIT, Division of Health Science and Technology, MIT, Division of Cardiovascular Medicine, Massachusetts General Hospital

Artificial Intelligence in Clinical Medicine: Challenges, Obstables, and Opportunities

Abstract & Suggested Readings(PDF)

4/28

 

Serena Wang, PhD student in Computer Science, UC Berkeley, advised by Rediet Abebe and Michael I. Jordan

Out of Scope, Out of Mind: Expanding Frontiers for Fair ML in Social Decision Making

Abstract & Suggested Readings(PDF)

5/5

 

Aaron Newman, PhD, Assistant Professor of Biomedical Data Science, Stanford 

Decoding stem cell hierarchies and cellular ecosystems in cancer

Abstract & Suggested Readings(PDF)

5/12

 

James Zou, PhD, Assitant Professor of Biomedical Data Science and, by courtesy, of Comupter Science and Electrical Engineering, Stanford 

AI for clinical trials and clinical trials for AI

Abstract & Suggested Readings(PDF)

5/19

 

Steven E. Brenner, PhD, Professor at the Department of Plant and Microbial Biology, University of California Berkeley

Prediction potential and pitfalls in pervasive population personal genomics: Interpreting newborn genomes with Notes on privacy timebombs in functional genomics data.

Abstract & Suggested Readings(PDF)

5/26

 

Elizabeth Stuart, PhDAssociate Dean for Education, and Professor of Mental Health, of Biostatistics, and of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health

Study designs to estimate policy effects using large-scale data: Applications to COVID-19 and opioid policies.

Abstract & Suggested Readings(PDF)

Winter 2022

Abstracts, when available, are included in the drop-down

Autumn 2021

Abstracts, when available, are included in the drop-down

Spring 2021

Abstracts, when available, are included in the drop-down

Winter 2021

Abstracts, when available, are included in the drop-down

Fall 2020

Abstracts, when available, are included in the drop-down

Spring 2020

Abstracts, when available, are included in the drop-down

Winter 2020

Abstracts, when available, are included in the drop-down

Fall 2019

Abstracts, when available, are included in the drop-down

Spring 2019

Abstracts, when available, are included in the drop-down

Winter 2019

Abstracts, when available, are included in the drop-down

DBDS on Diversity

We are committed to our historical and ongoing mission to use biomedical data science to improve human health. A cornerstone of this mission is diversity, reflected in embracing a breadth of complementary research interests, research styles, and a diverse and inclusive community. DBDS recognizes that we have significant work to do in shaping our future as we work towards achieving justice, equity, diversity and inclusion throughout our work and operations, our research and activities, and our professional relationships and partnerships.


Stanford's Land Acknowledgment Statement

Stanford sits on the ancestral land of the Muwekma Ohlone Tribe. This land was and continues to be of great importance to the Ohlone people. Consistent with our values of community and inclusion, we have a responsibility to acknowledge, honor, and make visible the University’s relationship to Native peoples.

This acknowledgment has been developed in collaboration with the Muwekma Ohlone Tribe.