Practicing Trustworthy Machine Learning

About the Authors

Yada Pruksachatkun is a machine learning scientist at Infinitus, a conversational AI startup that automates calls in the healthcare system. She has worked on trustworthy natural language processing as an applied scientist at Amazon, and she led the first healthcare NLP initiative within midsized startup ASAPP. She did research in transfer learning in NLP in graduate school at New York University where she was advised by Professor Sam Bowman.

Matthew McAteer works on machine learning at Formic Labs, a startup focused on in silico cell simulation. He is also the creator of 5cube Labs, an ML consultancy that has worked with over 100 companies in industries ranging from architecture to medicine to agriculture. Matthew previously worked with the TensorFlow team at Google on probabilistic programming, and with the general-purpose AI research company Generally Intelligent. Before he was an ML engineer, Matthew worked in biomedical research labs at MIT, Harvard Medical School, and Brown University.

Subhabrata (Subho) Majumdar is a machine learning scientist at Twitch, where he leads applied science efforts in responsible ML. He is also the founder of AI Vulnerability Database, a knowledge base of ML failures, and cofounder of Bias Buccaneers, a nonprofit dedicated to algorithmic bias bounties. Previously, Subho led research and development in ethical AI at AT&T, and was a senior scientist in the security ML team of Splunk. Subho holds a PhD and masters in statistics ...