Weiwei Pan

What I Do: I’m a Research Associate at the Institute for Computational Sciences at Harvard University. I’m a machine learning researcher focusing on health care applications. I work with clinicians to build machine learning models that have desirable properties for specific real-life downstream tasks. The model properties that I often concentrate on are: human interpretability and useful predictive uncertainties. What I Love About Data Science:I love that recent developments in data science is beginning to allow us to combine insights from data and domain knowledge from human experts in meaningful ways! What Else:I’ve been organizing this workshop since 2017 and I am thrilled to be doing it again this year!

Anastasiya Belyaeva

What I Do: I am a PhD student at MIT in the Institute for Data, Systems, and Society. As a PhD student I work on developing and applying new machine learning models for applications in biology. In particular, I’m interested in building models that capitalize on different types of data. What Else:My research focuses on developing and applying machine learning methods such as deep learning, representation learning, causal inference, and network analysis to large-scale data sets, with a special interest in biology & health.

Arushi Jain

What I Do:I'm a Data & Applied Scientist at Microsoft NERD Center in Cambridge. I am in Microsoft's AI rotation program where we work with different partner teams in Microsoft on different paradigms of AI. What I Love About Data Science:I love that data science allows us to make informed decisions – and to stop guessing. What Else:I am really passionate about teaching and empowering women into this field and this the first I am organizing this workshop, really excited to be here!!