Vasudha Varadarajan

🧚🏽‍♀️

Vasudha

Postdoctoral Research Associate

I am Vasudha Varadarajan, a Postdoctoral Research Associate at Carnegie Mellon University, working with Maarten Sap and Mona Diab on social intelligence, safety, and improving evaluations of AI. I earned my PhD in Computer Science from Stony Brook University, advised by H. Andrew Schwartz in the State University of New York at Stony Brook. My research integrates NLP and computational psychology to build AI systems that account for complex ways people think, feel, and relate. Our work has received multiple recognitions: Outstanding Paper Awards at ACL 2023, and at COLING 2025 GenAIDetect Workshop, and 2022 DARPA Forward Riser. My goal to produce AI evaluations that are valid, trustworthy, and accountable to the people they serve.

If you have similar interests and would like to work together, please feel free to reach out!

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Interests

Natural Language Processing
Computational Social Science

Education

PhD in Computer Science
Stony Brook
MSc (Hons.) Physics
Birla Institute of Technology and Science (BITS) Pilani
BE (Hons.) Computer Science
Birla Institute of Technology and Science (BITS) Pilani

📚 My Research

I am a postdoc researcher broadly interested in using NLP and data science to study social/psychological phenomena through language use and improving conversational AI. I am always looking for opportunities to work with teams with similar interests. Please reach out to collaborate 😃

Featured Publications

Capturing Human Cognitive Styles with Language: Towards an Experimental Evaluation Paradigm

Discourse, Cognitive Styles, Dissonance, Decision Making

AI-generated text, while coherent and human-like, exhibits significantly less variation in psychological traits compared to human-authored content, consistently modeling an "average" human personality. This limitation makes AI text distinguishable from human writing through analysis of fundamental human traits, revealing current AI's inability to capture the full spectrum of human psychological diversity.

Jan 1, 2025

Language of Extremism, Radicalization, Social Media, Generalized Framework

Unifying the Extremes: Developing a Unified Model for Detecting and Predicting Extremist Traits and Radicalization

A novel framework using "The Extremist Eleven" factors successfully analyzes and predicts extremist behavior across different online communities by examining verbal behavioral signatures. The method demonstrates high predictive accuracy, identifying potential extremists up to 10 months before they join extremist communities, while showing that users maintain consistent extremist traits after joining these forums.

Jan 1, 2025

Mental Health, Assessments, Adaptive, Item Response Theory, Chatbot

ALBA: Adaptive Language-Based Assessments for Mental Health

This study introduces Adaptive Language-Based Assessment (ALBA) for mental health, using limited language responses to adaptively order questions and assess psychological traits. Two methods, ALIRT and Actor-Critic, outperformed non-adaptive baselines. ALIRT proved most effective, achieving high accuracy with fewer questions, demonstrating that adaptive assessments can maintain validity with smaller language samples and lower computational costs.

Jan 1, 2024

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Recent Publications

Adithya v Ganesan, Vasudha Varadarajan, Yash Kumar Lal, Veerle C Eijsbroek, Katarina Kjell, Oscar NE Kjell, Tanuja Dhanasekaran, Elizabeth C Stade, Johannes C Eichstaedt, Ryan L Boyd, Others (2026). Explaining GPTs' schema of depression: A machine behavior analysis.. Journal of Psychopathology and Clinical Science.

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Vasudha Varadarajan, Akhila Yerukola, Mona T Diab, Maarten Sap (2026). CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries. COLM.

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Aaron Marker, Oscar Kjell, Vasudha Varadarajan, H Andrew Schwartz (2026). Evaluating Document-Tuned Transformer Representations for Person-level Mental Health Assessment. Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2026).

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Kieran Henderson, Kian Omoomi, Vasudha Varadarajan, Allison Lahnala, Charles Welch (2026). Examining the Utility of Self-disclosure Types for Modeling Annotators of Social Norms. Findings of the Association for Computational Linguistics: EACL 2026.

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Adithya v Ganesan, Vasudha Varadarajan, Yash Kumar Lal, Veerle C Eijsbroek, Katarina Kjell, Oscar NE Kjell, Tanuja Dhanasekaran, Elizabeth C Stade, Johannes C Eichstaedt, Ryan L Boyd, Others (2026). Explaining GPTs’ schema of depression: A machine behavior analysis.. Journal of Psychopathology and Clinical Science.

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