Jessica Gronsbell

Jesse Gronsbell is primarily interested in the development of statistical and machine learning methods for electronic health records and mobile health data. Before joining U of T, shereceived a BA in Applied Mathematics at UC Berkeley and a PhD in Biostatistics under the direction of Tianxi Cai at Harvard University. She did postdoctoral work with Lu Tian in the Department of Biomedical Data Science at the Stanford School of Medicine. She then spent a couple of years as a data scientist in the Mental Health Research and Development group at Alphabet's Verily Life Sciences.

Junwei Lu

Junwei Lu is an assistant professor in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. His research aims to develop a new generation of inference methods and theory for modern statistics and machine learning, especially focusing on combinatorial functionals, complex data structures and complicated algorithms. With the problems above, he is interested in studying the uncertainty assessment methodology, probabilistic universality phenomenon, and information-theoretical lower bound theory. His research finds its main applications in computational neuroscience.

Kung H-Sing Yu

Kung H-Sing Yu received his PhD in Biomedical Informatics and PhD Minor in Computer Science from Stanford University, and he obtained his MD from National Taiwan University, Taiwan. His research focuses on the integration of quantitative histopathology image patterns with multi-omics (genomics, epigenomics, transcriptomics, and proteomics) profiles to advance cancer research and clinical practice. His team has developed fully-automated algorithms to analyze whole-slide histopathology images at scale, discovered the molecular mechanisms underpinning the microscopic phenotypes of tumor cells, and identified novel cellular morphologies for patient prognosis. His research interests include quantitative pathology, machine learning, and translational bioinformatics.

Peter Potash

Peter Potash is a Senior Researcher at Microsoft in the Turing Montreal team, focusing on language understanding and generation. He is originally from San Anselmo, California and attended undergraduate studies at the University of California at Santa Barbara where he received Bachelors degrees in Mathematics and Slavic Languages & Literature and a Minor in English in 2010. After graduation, he spent some time tutoring Math and then working at an online advertising network, LookSmart, in San Francisco before beginning a Masters program in Mathematics at University of Massachusetts Lowell in Fall 2011. Peter finished the degree in Spring 2013 and continued graduate studies as a PhD student in the Computer Science department, advised by professor Anna Rumshisky. Peter joined Microsoft in 2017 after completing the PhD program, with his dissertation titled “Neural Argumentation: Structure and Persuasion

© 2018- CELEHS, Harvard University