Data Science Institute

Data Science Grants @ Brown 2020

Predicting the Course of Chemical Reactions with Deep Reinforcement Learning

Brenda Rubenstein, Cancan Huang, Leonard Sprague, Gopal Iyer (Chemistry)

Deep Learning Segmentation of Liver Structures, Tumors, and Effects of Treatment from Medical Images

Ben Kimia, Ben Hsieh (Engineering)

An Introductory Workshop on Machine Learning Methods for Undergraduate Students in MCM and STS

Theo Lepage-Richter (Modern Culture and Media)

Topological Data Analysis of Dynamic Tumor Architecture

Ian Wong, Dhananjay Bhaskar (Engineering), Lorin Crawford (Biostatistics)

Predictive models for microbial response to antibiotic nanoparticles: a hybrid approach of machine learning and mechanistic models

Zhijin Wu, Nicola Neretti (Biostatistics), with Jingyi Chen and Yong Wang (U of Arkansas)

SHARE: Secure Healthcare and Administrative Records Environment 

Seny Kamara (Computer Science), David Yokum, Kevin Wilson (The Policy Lab)

Big Virtual Reality in the Brown YURT for Data Visualization

David Laidlaw (Computer Science)

Machine Learning for Small Data -omic Problems: Identifying the Immunosuppressive Proteomic Signature for Adipose-Derived Stem Cells

Adrienne Parsons (Biotechnology Graduate Program), Lorin Crawford (Biostatistics), Eric Darling (Molecular Pharmacology, Physiology, and Biotechnology)