Network Systems Science and Advanced Computing

S.S. Ravi

  • Research Professor
S.S. Ravi headshot


S.S. Ravi is a research professor in the Network Systems and Advanced Computing division and a distinguished teaching professor in the Department of Computer Science at the University at Albany-SUNY.

  • Design and Analysis of Algorithms, Data Mining, Wireless Networks, Operations Research, Discrete Dynamical Systems, Fault-Tolerant Computing, Very Large-Scale Integration (VLSI)

  • University of Pittsburgh, Pittsburgh, Penn., Computer Science, Ph.D., 1984. Thesis Title: “Heuristics for PLA Folding: An Analytical Approach.” Thesis Advisor: Professor Errol L. Lloyd.
    University of Pittsburgh, Pittsburgh, Penn., Computer Science, M.S., 1981.
    Indian Institute of Science, Bangalore, India, Automation (Computer and Control Engineering), M.E., 1979.
    Indian Institute of Science, Bangalore, India. Electronics and Communication Engineering, B.E., 1977.
    Bangalore University, Bangalore, India, Physics, B.Sc. (Honors), 1974

Selected Publications
Social and Decision Analytics
Hu Z; Deng X; Goode BJ; Ramakrishnan N; Saraf P; Adiga A; Self N; Korkmaz G; Kuhlman CJ; Machi D; Marathe MV; Ravi SS; Ren Y; Cedeno-Mieles V; Ekanayake S . 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA. 2019; :169-180
Network Systems Science and Advanced Computing
Pal A; Kumar VSA; Ravi SS . IEEE Transactions on Power Systems. 2017; 32(1):552-561
Network Systems Science and Advanced Computing
Pal A; Mishra C; Kumar VSA; Ravi SS . IET Generation, Transmission & Distribution. 2017; 11(2):347-353
Network Systems Science and Advanced Computing
Adiga A; Kuhlman C; Marathe M; Ravi SS; Rosenkrantz D; Stearns R . Theoretical Computer Science. 2017; 679:126-144
In the News
Biocomplexity Institute News

What do hip-hop and hurricane evacuations have to do with network science? High school students learned the answers to that and more in an inaugural series of network science lectures, given by University of Virginia Biocomplexity Institute researchers Chris Kuhlman, Dustin Machi and S.S. Ravi at the annual Achievable Dream Summer Program.

Network Science

The University of Virginia’s Biocomplexity Institute was recently awarded a five-year $4 million collaborative grant from the U.S. National Science Foundation (NSF) to build a self-sustaining cyberinfrastructure (CINES – pronounced “science”) to serve as an open-source, web-based repository for developing, trading, analyzing, and sharing network science resources. 

Machine Learning

The use of artificial intelligence (AI) is everywhere. From making diagnoses in the medical profession to determining sentencing in court cases, we are increasingly relying on AI and machine learning algorithms to make decisions that can have a profound impact on people’s lives. As the use of AI becomes even more prevalent, how do we know that the algorithms and models used to make these critical decisions are correct, unbiased, and reliable?