Swanand Ravindra Kadhe is a Research Staff Member with IBM's Almaden Research Center in San Jose, CA. He is a member of the AI Platforms and AI Security and Privacy Solutions research groups. His current research is centered around building mathematical foundations of machine learning to address privacy, security, and scalability challenges, with a particular focus on federated learning and distributed machine learning. His research interests lie in the areas of machine learning in distributed and federated environments, distributed computing and storage systems, and blockchains.
Prior to joining IBM Research, he was a postdoctoral researcher at the EECS Department of University of California, Berkeley, where he was working with Prof. Kannan Ramchandran. During his postdoc, he designed and analyzed scalable algorithms for privacy-preserving and robust distributed machine learning and for enabling distributed computing on emerging platforms such as serverless systems and blockchains.
Prior to joining UC Berkeley, he completed his PhD from the ECE Department of Texas A&M University, where he was advised by Prof. Alex Sprintson. In his doctoral research, he developed coding-theoretic techniques for cloud storage systems to provide security against eavesdropping attacks and ensure high data availability for fast content download. He also designed efficient algorithms for private information retrieval that enable users to access records from a remote database while preserving the privacy of queries.
Before starting his PhD, he worked as an R&D Engineer at the Innovation Labs of TATA Consultancy Services (TCS), Bangalore. The theme of his work was “Signal Processing and Coding Techniques for Futuristic Communications and Storage”, with a focus on compressive sensing and network coding.
He obtained his master's degree from the Electrical Engineering Department of Indian Institute of Technology Kanpur in July 2009, with a thesis in wireless communications, advised by Prof. A. K. Chaturvedi.
For publications, please check his Google Scholar page.
For details on his research, please check his personal webpage.