Aravind Srinivasan's main research-interests are in algorithms, probabilistic methods, data science, network science, and machine learning: theory, and applications in areas including health, E-commerce, cloud computing, Internet advertising, and fairness. They span areas including:
Dr. Srinivasan was appointed a Distinguished University Professor of the University of Maryland in 2020: this is the highest academic honor the university confers upon its faculty. He is an elected Fellow of six professional societies: ACM, AAAS, IEEE, AMS, EATCS, and SIAM. He was elected a Member of Academia Europaea, the Academy of Europe, in 2018. He received a Distinguished Alumnus Award from his alma mater IIT Madras. He also received the Distinguished Faculty Award from the Board of Visitors of the College of Computing, Mathematical, and Natural Sciences (University of Maryland) in 2016. He is a recipient of the Dijkstra Prize, the Danny Lewin Award, and the Distinguished Career Award in Computer Science from the Washington Academy of Sciences. His past and current research have been funded by research awards from Adobe, Amazon, and Google, and by grants/contracts from the NSF, IARPA, and USARO. He was eighth in India in the Joint Entrance Examination for the Indian Institutes of Technology (IITs) in 1985.
Aravind Srinivasan served as Vice Chair of the IEEE Technical Committee on the Mathematical Foundations of Computing from 2015 to 2017. He has served on the Board of Advisors for ZeroFOX Inc., He has also been serving as an Amazon Scholar since 2019.
Aravind's detailed CV is also available.
An addendum by Aravind: (Auto-)Biographies such as the above might appear to cast all the professional recognition received by a person as due to their own effort and/or ability. In reality, a large number of people and institutions---too many to list here---have supported me substantially, and continue to do so. I gratefully acknowledge the kindness shown by these institutions and people: I could not have had even a small fraction of my professional advancement without their guidance and support.