Syeda Mahwish | Ph.D. Student at Cornell University

About

I am a first-year graduate student in the Better Outcomes Lab interested in understanding protective factors that support psychological well-being and adaptability following periods of stress and adversity.

I’m also interested in the ways language encodes these psychological processes and how natural language processing (NLP) can be used to study them in a theoretically grounded manner.

I value collaborative, interdisciplinary, and quantitatively grounded research, and I am committed to open and transparent science through the reporting of both significant and non-significant findings. Prior to beginning my Ph.D., I earned an MPH in Biostatistics and Epidemiology and spent three years as a researcher and coordinator in a human-centered NLP lab (HLAB) within the Computer Science Department at Stony Brook University.

Outside of research, I am a sister, the eldest daughter of two immigrant parents, and a plant lover. I have many interests, but you will most often find me sketching and painting, cooking, running, and my most expensive hobby: horseback riding. I'm also a coffee and matcha enthusiast, with an extensive home espresso-making setup.

Publications

Mahwish, S., Boyd, R. L., Varadarajan, V., Kotov, R., Luft, B. J., Schwartz, H. A., & Clouston, S. A. P. (2026). Measuring resilience using language modeling: A computational approach to observing resilience. Journal of Traumatic Stress, 1-14. DOI
Soni, N., Nilsson, A. H., Mahwish, S., Varadarajan, V., Schwartz, H. A., & Boyd, R. L. (2025). Who we are, where we are: Mental health at the intersection of person, situation, and large language models. Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025), 300–313. DOI
Singh, K., Varadarajan, V., Ganesan, A. V., Nilsson, A. H., Soni, N., Mahwish, S., Chitale, P., Boyd, R. L., Ungar, L., Rosenthal, R. N., & Schwartz, H. A. (2025). Systematic Evaluation of Auto-Encoding and Large Language Model Representations for Capturing Author States and Traits. Findings of the Association for Computational Linguistics: ACL 2025, 18955–18973. DOI
Varadarajan, V., Lahnala, A., Vankudari, S., Raghavan, A., Feltman, S., Mahwish, S., Ruggero, C., Kotov, R., & Schwartz, H. A. (2025). Linking language-based distortion detection to mental health outcomes. Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025), 62–68. DOI
Nilsson, A. H., Schwartz, H. A., Rosenthal, R. N., McKay, J. R., Vu, H., Cho, Y. M., Mahwish, S., Ganesan, A. V., & Ungar, L. (2024). Language-based EMA assessments help understand problematic alcohol consumption. PLOS ONE, 19(3), e0298300. DOI
Matero, M., Vu, H., Nilsson, A., Mahwish, S., Cho, Y. M., McKay, J., Eichstaedt, J., Rosenthal, R., Ungar, L., & Schwartz, H. A. (2024). Using Daily Language to Understand Drinking: Multi-Level Longitudinal Differential Language Analysis. Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024), 133–144. DOI
Nilsson, A., Boyd, R. L., Ganesan, A. V., Kjell, O. N. E., Mahwish, S., Huang, H., & Schwartz, H. A. (2024). Language-based assessments for experienced well-being: Accuracy and external validity across behaviors, traits, and states. Preprint
Varadarajan, V., Mahwish, S., Liu, X., Buffolino, J., Luhmann, C. C., Boyd, R. L., & Schwartz, H. A. (2025). Capturing Human Cognitive Styles with Language: Towards an Experimental Evaluation Paradigm. Proceedings of NAACL-HLT 2025 (Short Papers). DOI
Varadarajan, V., Juhng, S., Mahwish, S., Liu, X., Luby, J., Luhmann, C., & Schwartz, H. A. (2023). Transfer and Active Learning for Dissonance Detection: Addressing the Rare-Class Challenge. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 11923–11936. DOI

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Publications