About Me

avatar
I am a Ph.D. candidate in the Department of Computer Science at the University of Illinois Chicago (UIC). I am working under the supervision of professor Elena Zheleva in the EDGES lab, a statistical relational learning and data science lab. My research interests lie at the intersection of Causal Inference, Knowledge Discovery, and Machine Learning. Currently, I am working on causal modeling and heterogeneous treatment effect estimation in network data.

I completed my Bachelor’s degree in Electronics and Communication Engineering from the Tribhuvan University (TU) in Fall 2014. Before joining UIC, I worked as a Software/Data Engineer on big data analytics, custom search engine, and web application development.

Publications

Shishir Adhikari, Sourav Medya, Elena Zheleva. Exposure Mapping Function Learning for Peer Effect Estimation. AAAI Workshop on Artificial Intelligence with Causal Techniques (AICT) 2025. Poster

Shishir Adhikari, Elena Zheleva. Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence. Machine Learning Journal 2025. Paper Code+Data

Shishir Adhikari, Elena Zheleva. Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence (Extended Abstract). IEEE Data Science and Advanced Analytics (DSAA) 2024.

Rishabh Singh Chauhan, Christoffer Riis, Shishir Adhikari, Sybil Derrible, Elena Zheleva, Charisma F Choudhury, Francisco Camara Pereira. Causality in Travel Mode Choice Modeling. Travel Behavior and Society 2024. Paper

Shishir Adhikari. Discovering heterogeneous causal effects in relational data. AAAI Doctoral Consortium 2024. Paper

Shishir Adhikari, Akshay Uppal, Robin Mermelstein, Tanya Berger-Wolf, Elena Zheleva. Understanding the Dynamics between Vaping and Cannabis Legalization Using Twitter Opinions. AAAI Conference on Web and Social Media (ICWSM) 2021. Paper Poster Code+Data

Preprints/Working papers/Technical reports

Shishir Adhikari, Sourav Medya, Elena Zheleva. Learning Exposure Mapping Functions for Inferring Heterogeneous Peer Effects. Arxiv preprint 2025. (Extended version of AAAI AICT 2025 paper, currently under review) Paper

Shishir Adhikari, Guido Muscioni, Mark Shapiro, Plamen Petrov, Elena Zheleva. Heterogeneous Causal Discovery of Repeated Undesirable Health Outcomes. Arxiv 2025 (Under Review). Paper

Shishir Adhikari. Causal Structure Learning when Data is not Independent and Identically Distributed (non-IID). A written critique as partial fulfillment of the requirements for Ph.D. qualifier examination 2020. PDF

Posters/Presentations

“Exposure Mapping Function Learning for Peer Effect Estimation” Poster at Midwest Machine Learning Symposium 2025 (MMLS'25) (June 23-24 2025).

“Inferring Causal Effects in Networks Under Heterogeneous Peer Influence” Student talk at IDEAL Annual meeting (June 09 2025).

“Inferring Causal Effects in Networks Under Heterogeneous Peer Influence” Invited talk at University of California Irvine (April 2025).

“Causal Inference under Interference” Guest Lecture for the Causal Inference and Learning course, taught by Dr. Elena Zheleva, at UIC, Chicago, IL (Fall 2024 and Fall 2023).

“Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence” Poster at the Foundations of Fairness, Privacy, and Causality in Graphs Workshop, Santa Cruz, CA (October 2023).

“Causal Inference under Heterogeneous Peer Influence” Presentation and Poster at KDD’23 PhD Consortium, Long Beach, CA (August 2023).

“Causal Inference for Policy Evaluation in Network Data” Presentation and Tutorial at Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) Workshop, Chicago, IL (Jun 2023).

“Quasi-Experimental Methods in Causal Inference” Guest Lecture for the Causal Inference and Learning course, taught by Dr. Elena Zheleva, at UIC, Chicago, IL (Fall 2022).

“Inferring Causal Effects in Network under Heterogeneous Peer Influence” Poster at the Midwest Machine Learning Symposium, Chicago, IL (May 2022).

Teaching

Teaching Assistant
Introduction to Data Science (CS418)
Spring 2020, Spring 2022

Teaching Assistant
Machine Organization (CS261)
Fall 2018, Spring 2019, Fall 2019

Services

Awards

Contact