Summary
Robert Ness is a Senior Researcher and author of the book "Causal AI" with a decade of experience applying statistical and machine-learning methods to real-world problems at Microsoft, startups, and academia. He blends deep theoretical training—a PhD in Statistics and a master's in Mathematical Statistics from Purdue—with hands-on product and research roles, from founding Altdeep to driving ML research at Gamalon and Zymergen. As a Professor of Practice at Northeastern and an active researcher affiliated with PKU and Microsoft, he bridges teaching, published research, and industrial deployment of causal and language technologies. His background in finance, economics, and China studies gives him an unusual interdisciplinary lens for causal inference in socio-technical systems. He is comfortable moving between founding teams and large R&D organizations, translating complex statistical ideas into practical AI tools and curricula. Based in Bellevue, WA, he combines entrepreneurial grit with rigorous research, often focusing on interpretable, causality-driven solutions rather than black‑box models.
10 years of coding experience
14 years of employment as a software developer
Hopkins-Nanjing Center Program, China Studies, Hopkins-Nanjing Center Program, China Studies at Johns Hopkins SAIS
Master's degree, Mathematical Statistics and Probability, Master's degree, Mathematical Statistics and Probability at Purdue University
Bachelors, Finance, Economics, Bachelors, Finance, Economics at University of Pittsburgh
English, Chinese