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Assistant Professor, Computer Science, Ashoka University
Ph.D. University of Illinois Chicago
Rochana Chaturvedi is an Assistant Professor at the Department of Computer Science at Ashoka University. Her research is at the intersection of natural language processing, large language models, and graph machine learning, with an emphasis on temporal and causal grounding. She develops methods to recover latent structure from longitudinal text for applications such as health risk prediction, studying social media polarization, and investigating fairness in AI-driven hiring. She also develops methods to examine and improve LLM reliability and robustness. Her research has been published in leading computer science venues such as ACL, EMNLP, TACL, and the ACM Web Conference, as well as interdisciplinary venues such as Political Analysis.
Before joining Ashoka, she was a Postdoctoral Fellow at Kellogg School of Management at Northwestern University and the Mathematics and Computer Science Division at Argonne National Laboratory. She earned her Ph.D. and M.S. in Computer Science from the University of Illinois Chicago. Prior to her doctoral studies, she was an Assistant Professor of Computer Science at Keshav Mahavidyalaya, University of Delhi.
SCORE: Specificity, Context Utilization, Robustness, and Relevance for Reference-Free LLM Evaluation
Homaira Huda Shomee, Rochana Chaturvedi, Yangxinyu Xie, and Tanwi Mallick. EMNLP 2026. Forthcoming. [LLM evaluation, RAG, robustness]
Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processing
Rochana Chaturvedi, Yue Zhou, Andrew Boyd, Brian T. Layden, Mudassir Rashid, Lu Cheng, Ali Cinar, and Barbara Di Eugenio. Transactions of the Association for Computational Linguistics (TACL), 2026, 14, pages 1711–1733. [Clinical NLP, representation learning, graph machine learning]
Temporal Relation Extraction in Clinical Texts: A Span-Based Graph Transformer Approach
Rochana Chaturvedi, Peyman Baghershahi, Sourav Medya, and Barbara Di Eugenio. ACL 2025, pages 25765-25788. [Information extraction, graph machine learning]
Bridging or Breaking: Impact of Intergroup Interactions on Religious Polarization
Rochana Chaturvedi, Sugat Chaturvedi, and Elena Zheleva. ACM Web Conference 2024, pages 2672-2683. [NLP, Computational social science]
Sequential Representation of Sparse Heterogeneous Data for Diabetes Risk Prediction
Rochana Chaturvedi, Mudassir Rashid, Brian T. Layden, Andrew Boyd, Ali Cinar, and Barbara Di Eugenio. IEEE BIBM, 2023. [Healthcare AI, representation learning, risk prediction]
It’s all in the name: A character-based approach to infer religion.
Rochana Chaturvedi and Sugat Chaturvedi. Political Analysis 32.1 (2024), pages 34-49. [NLP, computational social science]
Enhancing Cause-of-Death Ascertainment in India through NLP-Enabled Verbal Autopsy in the MINErVA Network. Breakthrough Research Grant, Gupta-Klinsky India Institute, Johns Hopkins University. Co-Principal Investigator. USD 80,000. 2026
NSF Student Travel Awards: ACM Web Conference 2024 and IEEE BIBM 2023; UIC Graduate Student Council Travel Award, 2023
Junior Research Fellowship (JRF), University Grants Commission–National Eligibility Test, 2018
Courses Taught at the University of Delhi 2011-2021 (partial list):
Data Structures
Design and Analysis of Algorithms
Advanced Algorithms
Discrete Structures
Linear Algebra
Introduction to Data Science
Data mining
Introduction to Python Programming
Computer System Architecture
