Ph.D., Cornell University (Statistics and Data Science) (expected 2027)
M.S., Cornell University (Statistics and Data Science) (2025)
J.D., Columbia Law School (2024)
B.S., Yale College (Applied Mathematics) (2019)
Anti-Discrimination Law, Evidence, Employment Law, Torts
Daniel Kipnis is an Academic Fellow and Lecturer in Law at Columbia Law School. He is a
scholar of law and statistics. His scholarship uses and develops methodologies in statistics
and probability theory and draws upon formal epistemology to conceptualize and solve
doctrinal problems in evidence, anti-discrimination law, and tort law.
Kipnis earned his JD from Columbia Law School in 2024, where he was a member of the
Academic Scholars Program. He has worked as a litigation associate at Cravath, Swaine &
Moore and as a judicial intern and extern for the Honorable Valerie Caproni of the United
States District Court for the Southern District of New York. He is currently a doctoral
candidate in Statistics and Data Science at Cornell University.