Harvard Institute for Applied Computational Science

Weiwei Pan: What Are Useful Uncertainties in Deep Learning and How Do We Get Them? | IACS Seminar

Yasaman Bahri: Theoretical Building Blocks From The Study of Wide Networks | IACS Seminar

Josh Bloom: Physics-Informed Machine Learning in Astronomy | IACS Seminar

Aaron Hertzmann: Can Computers Create Art? | IACS Seminar

Cengiz Pehlevan: A Function Approximation of Perspective on Sensory Representations | IACS Seminar

Jessica Stauth: It’s Not Just Good Leadership Advice, It’s Good Data Science Practice | IACS Seminar

Chris Tanner: Hard NLP Tasks: Determining who is who and what is what | IACS Seminar

Caroline Uhler: Autoencoders & causality in the Light of Drug Repurposing for COVID19 | IACS Seminar

Siddhartha Mishra: Deep Learning and Computations of high-dimensional PDEs | IACS Seminar

Emma Pierson: Data science for social equality | IACS Seminar

Trevor David Rhone: Quantum Materials Design Using Artificial Intelligence | IACS Seminar

Laure Zanna: The future of climate modeling in the age of artificial intelligence | IACS Seminar

2019 Women in Data Science Conference (Cambridge MA)

AC 297r: Computational Science and Engineering Capstone Project

Alex Liu: Data Science Ecosystems with AI to Improve Social Research | IACS Seminar

CS 109b: Data Science II: Advanced Topics in Data Science