Venkata Gandikota (GV)

Address: CST 4-206B,  Syracuse University, Syracuse, NY 13210
E-mail:  <lastname>[dot]<firstname>[at]gmail[dot]com
Research overview: My research aims to identify the algorithmic limits of various data analysis tasks. In particular, we leverage the combinatorial properties of error-correcting codes to design efficient and robust algorithms for various machine learning tasks such as distributed learning and sparse recovery. We exploit the key idea of introducing "structured redundancy" that facilitates the design of computationally efficient noise-resilient algorithms for many computational tasks. 

Research Interests: 

Biography: 

I am an Assistant Professor in the Department of Electrical Engineering and Computer Science at Syracuse University.  I am also an affiliate faculty at EnCore: Institute for Emerging CORE Methods in Data Science, and an IEEE senior member.  My research interests include coding theory, lattices, and their applications to foundational machine learning tasks. A part of my research is supported by the CUSE and SOURCE RA grants. Before joining SU, I was a postdoctoral researcher at the University of Massachusetts at Amherst, and Johns Hopkins University I received my Ph.D. in Computer Science from Purdue University I completed my undergraduate Mathematics (MSc) & Computer Science (BE) from Birla Institute of Technology & Science, Goa, India.