I am a Ph.D. candidate at Purdue University, working on Natural Language Understanding with Dr. Julia Taylor Rayz at the AKRaNLU Lab. My work focuses on enhancing language model reasoning by addressing challenges in resolving linguistic ambiguity and enhancing generalization, particularly in cases where the structural form (locution) diverges from the communicative function, such as in manipulative discourse.

During my PhD, I have worked on quantifying how alignment methods can exacerbate countervailing biases, demonstrated that calibrated models lack generalizability, developed methods for sense-enrichment of contextualized representations, worked on fuzzy models for intent classification, including task-based intent as well as covert malicious intents.

Currently, I am finalizing my dissertation on Reliable Detection of Manipulative Discourse. My research takes a two-pronged approach:

• Structured Knowledge for Context-Aware Detection: Examining how structured representations of communication patterns can enhance social reasoning, particularly in detecting manipulative discourse.
• Uncertainty Estimation in Language Tasks: Developing methods to quantify the uncertainty in language model outputs when reasoning with underspecified inputs.

For more information regarding my work, please check out my Google Scholar.

Recent Updates

• Mar 2025 - Received A.H. Ismail Interdisciplinary Graduate Degree Grant from Purdue University!
• Mar 2025 - Received Graduate Student Travel Grant from Purdue Polytechnic Institute!
• Jan 2025 - Delivered an ignite talk, “Bridging the Gap: Advancing AI for Detecting Covert Online Harms,” in the Digital and Social Media Track at HICSS-58
• Dec 2024 - Paper on “Examining Language Model’s Behavior with Occupation Attributes” accepted to COLING 2025 - paper
• Aug 2024 - Paper on “The Reliability Paradox: Exploring How Shortcut Learning Undermines Language Model Calibration” accepted to HICSS-58 - paper