Incoming fourth-year B.S. in Computer Science · UC San Diego
I am a Computer Science major with a strong interest in advancing large language models (LLMs). My current work focuses on enhancing LLM reasoning through human-inspired approaches, agentic frameworks, and data mining—with particular attention to context awareness, agent learning and navigation, and forecasting. I am especially motivated by aligning machine reasoning more closely with human thought processes to build more reliable and adaptive AI systems.
I study how large language models, agentic frameworks, and data mining can support rigorous qualitative inquiry and more human-aligned reasoning.
Developing frameworks that combine LLMs with grounded theory and schema induction for qualitative research, and surveying how qualitative data analysis is evolving in the LLM era.
Building and evaluating agentic systems that coordinate planning, tool use, and multi-step reasoning to solve complex research and real-world tasks more reliably.
Applying large-scale data mining and topic modeling to extract patterns from unstructured text and behavioral data, supporting both qualitative discovery and quantitative validation.
Exploring approaches that improve context awareness, agent learning and navigation, and forecasting by bringing machine reasoning closer to human cognitive processes.
Prior work on parental concerns in online gaming platforms, using large-scale social media analysis and user studies to inform safer, more transparent platform design.
All publications below list me as first co-author. My name is in bold.
Bridging Human Interpretation and Machine Representation: A Landscape of Qualitative Data Analysis in the LLM Era
arXiv preprint arXiv:2601.11739, 2026
LOGOS: LLM-driven End-to-End Grounded Theory Development and Schema Induction for Qualitative Research
arXiv preprint arXiv:2509.24294, 2025
“Parent seeking Roblox Safety Help”: Comparing Parental Roblox Concerns to Roblox Offerings
2024 IEEE International Symposium on Technology and Society (ISTAS), pp. 1–9, 2024
Research assistant in the Halıcıoğlu Data Science Institute, working on large language models, agentic frameworks, and data mining for qualitative research—including grounded theory development, schema induction, and human-aligned reasoning.
Analyzed facial enhancements from three filter applications (Snatched, Blochi Gora, Baby Girl), investigating cultural biases in appearance modifications. Migrated the Facial Landmarks Analysis Before and After Filter Enhancement algorithm to a remote server for parallel processing at scale.
Implemented DeepFace and Retina for facial recognition and racial classification on a Raspberry Pi smart mirror, delivering real-time facial analysis for a public art installation addressing racial bias.
“Parent seeking Roblox Safety Help”: Comparing Parental Roblox Concerns to Roblox Offerings
Conducted topic modeling on 10,000+ Reddit posts and surveyed 100 participants to identify four primary parental concerns on Roblox. Proposed actionable solutions published at IEEE ISTAS and presented at the ERSP symposium.
Course, club, and team-based projects outside of formal research appointments.
Designed and implemented the database schema for a zoo navigation Android application. Revamped the Android UI and maintained project documentation for the development team.
Credit Card Fraud Detector
Experimented with KNN, Random Forest, Decision Tree, SVM, and Logistic Regression for credit card fraud detection. Built and presented a fraud detection web application at the ACM symposium.
B.S. in Computer Science
Incoming fourth year · Expected graduation June 2026