The DSML Team
We are a unique mix of academics, industry professionals, data scientists and machine learning engineers.
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Alex Zai
Alex worked as a deep learning engineer for Amazon and Uber, where he contributed to their internal ML libraries such as MXNet, which were used to power their AI products, with a specialty in Computer Vision.
He's also the author of the book "Deep Reinforcement Learning in Action" by Manning Publications, which was the first book to emphasize the use of RL for common engineering problems.
He specializes in developing the program and assisting with DSML engineering endeavors.
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Jonathan Bechtel
Jonathan is a data scientist with an expertise in time series modeling and open source development. He has helped organize contributions to TensorflowJS and sktime, and enjoys evangelizing the spread of grassroots ML knowledge.
He has worked with organizations such as General Assembly, NYPD, Amber Capital and Advent International to assist them with their data science needs.
Jonathan has a particular passion for time series problems, since he believes they are the most practical way for companies to harness ML for business value.
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Gerard Torrats-Espinosa
Gerard is an assistant professor of Sociology at Columbia University and a member of their Institute for Data Science. His expertise is in the area of causal inference and experimental design.
His work has been published or is forthcoming in the American Sociological Review, Child Development, Demography, Housing Policy Debate, the Journal of Housing Economics, the Journal of Urban Economics, and the Proceedings of the National Academy of Sciences.
Gerard contributes to DSML Group's research endeavors.
Laura Zheng
Laura Zheng is currently a data scientist at Aetna working on experimental design to optimize outreaches to keep Aetna members healthy. She previously worked at CVS Health in the Retail Pharmacy division with experimental design for text message outreaches, especially those with video links.
Her first data scientist job was at the fintech startup Brigit where she used her data science and machine learning skills for credit risk modelling.
She has her B.S and M.Eng in Bioengineering from Cornell University and her Ph.D. in public health from Johns Hopkins University.
In her spare time, she likes to take too many pictures of her two cats, Reed and Nile, and try to bake the ultimate chocolate brownie.
Heather Harris
Heather has a PhD in statistics related to cognitive processes, and she has worked as a consulting data scientist and statistician for 4 years.
As a consultant, she’s led a multitude of diverse projects including predicting audiences for the first movie with a theatrical release following the pandemic, predicting and segmenting viewers for several television shows and networks, developing scoring algorithms for EdTech companies, and working with clients from several substantive areas to architect data ecosystems for advanced analytics.
She is passionate about teaching best statistical practices and communicating complex results to non-technical audiences. When she's not crunching numbers, you can find her exploring museums in DC and playing Euchre with friends.
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