Please join us for the Women in Big Data at Michigan symposium at the Michigan League. This day-long symposium will highlight women data science researchers at U-M, and provide resources and support for women pursuing careers in data science.

Keynote Speaker

Xihong Lin
Henry Pickering Walcott Professor of Biostatistics
Harvard T.H. Chan School of Public Health

Dr. Lin’s research focuses on the development and application of statistical and computational methods to analyze high-throughput genetic and genomic data in epidemiological, environmental and clinical studies, and to analyze complex exposure and phenotype data in observational studies.

Title: Analysis of Massive Data from Genome, Exposome and Phenome: Challenges and Opportunities

Abstract: Massive data from genome, exposome, and phenome are becoming available at an increasing rate with no apparent end in sight. Examples include Whole Genome Sequencing data, smartphone data, wearable devices, Electronic Medical Records and biobanks. The emerging field of Health Data Science presents statisticians and quantitative scientists with many exciting research and training opportunities and challenges. Success in health data science requires scalable statistical inference integrated with computational science, information science and domain science.  In this talk, I discuss some of such challenges and opportunities, and emphasize the importance of incorporating domain knowledge in health data science method development and application. I illustrate the key points using several use cases, including analysis of data from Whole Genome Sequencing (WGS) association studies, integrative analysis of different types and sources of data using causal mediation analysis, analysis of multiple phenotypes (pleiotropy) using biobanks and Electronic Medical Records (EMRs), reproducible and replicable research, and cloud computing.

U-M Speakers

Presenters Panel Participants
Veronica Berrocal, Biostatistics Moderator: Liza Levina, Statistics
Danai Koutra, Computer Science & Engineering Amy Cohn, Industrial & Operations Engineering
Heather Mayes, Chemical Engineering Xihong Lin, Biostatistics, Harvard University
Snigdha Panigrahi, Statistics Jennifer Linderman, Chemical Engineering
Maureen Sartor, Computational Medicine & Bioinformatics Rada Mihalcea, Computer Science & Engineering
Jenna Wiens, Computer Science & Engineering Bhramar Mukherjee, Biostatistics
Rocio Titiunik, Political Science

Schedule

8:30 a.m.: Registration & Breakfast

9:15 a.m.: Welcome

9:30 a.m.: Keynote Address, Xihong Lin

11 a.m.: Research lightning talks, U-M faculty members

Noon: Lunch with roundtable discussions on academia and industry

1:30 p.m.: Poster Session

2:00 p.m.: Presentation on U-M Data Science Resources: CSCAR, ARC-TS, ADVANCE

3 p.m.: Panel Discussion: In conversation with senior women data scientists

Thank you to our generous sponsors