Put AI to Work
April 15-18, 2019
New York, NY
Kush Varshney

Kush Varshney
Principal Research Staff Member and Manager, IBM Research

Website

Kush R. Varshney is a research staff member and manager at IBM Research AI at the T. J. Watson Research Center, where he leads the Learning and Decision Making Group. He’s the founding codirector of the IBM Science for Social Good initiative. His research applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to recognitions such as the 2013 Gerstner Award for Client Excellence for contributions to the WellPoint team and the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation. He also conducts academic research on the theory and methods of statistical signal processing and machine learning. His work has been recognized through best paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences. He holds a PhD and SM in electrical engineering and computer science from MIT, where he was a National Science Foundation Graduate Research Fellow, and a BS (magna cum laude) in electrical and computer engineering with honors from Cornell University.

Sessions

9:00am12:30pm Tuesday, April 16, 2019
Implementing AI
Location: Petit Trianon
Secondary topics:  Deep Learning and Machine Learning tools, Ethics, Privacy, and Security
Rachel Bellamy (IBM Research), Kush Varshney (IBM Research), KARTHIKEYAN NATESAN RAMAMURTHY (IBM Research), Michael Hind (IBM Research AI)
Rachel Bellamy, Kush Varshney, Karthikeyan Natesan Ramamurthy, and Michael Hind explain how to use and contribute to AI Fairness 360—a comprehensive Python toolkit that provides metrics to check for unwanted bias in datasets and machine learning models and state-of-the-art algorithms to mitigate such bias. Read more.