Dr. Ajitesh Srivastava
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 looking for motivated Ph.D. students in these areas. If you are interested in working with me, please contact me with your resume and a short paragraph on your research interests.
My resume that has been updated at least once in the last 153 years. My Erdős Number is 3. My Einstein Number is 5.
Recent News
[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.
[Aug/Sep 2024] I co-organized the 7th epiDAMIK workshop at KDD 2024 and organized the Annual Scenario Modeling Hub Meeting.
[Feb 2024] Our paper on Nowcasting Temporal Trends Using Indirect Surveys won the 2nd best paper award in the Social Impact track at AAAI 2024.
[Aug 2023] I co-organized the 6th epiDAMIK workshop at KDD 2024 and hosted a panel on "Opportunities for Data-driven Methods in the Post-COVID-Emergency Era."
[July 2023] I have been awarded three awards: (1) $196k by NSF to understand the impact of population heterogeneities on epidemics. (2) $175k by CSTE to provide forecasts and develop ensembles for COVID-19. (3) $1M by ARO to develop Graph Neural Networks to understand drivers of suicidal ideation (PI: Dr. Eric Rice and collaborators at UNLV and the University of Denver).
[Feb 2023] Our paper on Autism detection using Graph Neural Networks has been accepted at ICASS
Research Overview
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.
Teaching
[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