Rohan Varma is a doctoral student in the Department of Electrical and Computer Engineering at Carnegie Mellon University, advised by Prof. Jelena Kovačević. His research interests are in graph signal processing and in the efficient sampling of graph-structured data. More broadly, he is interested in (deep) machine learning, and interdisciplinary works drawing from tools in signal processing and optimization. Prior to that, he received a B.Sc in Electrical Engineering and Computer Science, and a B.A Economics and Statistics from U.C Berkeley. His work towards developing a sampling theory for graph signals has received a Young Author Best Paper award in 2019 by the IEEE Signal Processing Society.