Research Assistant Professor
Ming Hsieh Department of Computer and Electrical Engineering
Associate Director, Center for AI in Society
University of Southern California,
EEB 226, 3740 McClintock Ave, Los Angeles, CA 90089-2562.
ajiteshs [AT] usc [DOT] edu
Research Interests: Machine Learning, Modeling, and Graph Algorithms applied to epidemics, social good, and social networks.
I am moving to Northeastern University (Charlotte campus) in Fall 2026 as an Associate Professor in AI and Health at Bouvé College of Health Sciences and the Network Science Institute.
My resume that has been updated at least once in the last 153 years. My Erdős Number is 3. My Einstein Number is 5.
[Sep 2025] Three papers accepted at NeurIPS 2025 Workshops
[Sep 2025] Cynthia wins the MHI Undergraduate Scholarship
[Dec 2024] Two papers accepted at AAAI 2025 on GNN-based spatio-temproal spread and building consensus from multiple time-series!
[Sep 2024] I have been funded by CFA as a part of the Atlantic Coast Center for Infectious Disease Dynamics and Analytics (ACCIDDA) to develop innovative modeling and analytic techniques to understand, predict, prepare for, and respond to infectious disease threats.
Here is a word cloud of the titles of my paper. For the full list of my publications, please see my Google Scholar page. To explore them interactively, check my Publication page.
My research interests include Machine Learning, Modeling, and Graph Algorithms applied to epidemics, social good, and social networks. Please check my Research Highlights for my recent work.
In the past, I have worked on information diffusion, parallel computing, FPGA acceleration, and smartgrids. If you are a student interested in working with me, please send me your resume and a half-page research proposal on what you would like to pursue.
[Fall 2023] EE155L: Introduction to Computer Programming for Electrical Engineers (co-instructor Prof. Sandeep Gupta)
[Spring 2023] EE 638: Applications of Machine Learning for Medical Data and Smart Systems [syllabus]
[Spring 2022] EE638: Applications of Machine Learning for Medical Data (co-instructor Prof. Cauligi Raghavendra)
[Fall 2021] EE155L: Introduction to Computer Programming for Electrical Engineers (co-instructor Prof. Sandeep Gupta)
For my standup comedy page, please visit: https://sites.google.com/view/ajcomedy/home