Research Experience

Siebel School of Computing and Data Science. University of Illinois Urbana-Champaign
Undergraduate Research Scholar, TRAILS Lab | Jan 2023 - Present
Mentor: Dr. Kathryn Cunningham

• Pursuing research to design a socio-technical system to assist instructors in efficiently identifying common code patterns in application-focused domains like web development with Django, that interest non-computer science majors.
• Implementing a web interface to formulate a question generator that creates various types of questions, including multiple-choice, reordering, and fill-in-the-blank tasks using programming patterns.
• Designed an LLM-powered pipeline that can suggest candidate programming patterns using chain-of-thought prompting to identify code examples and clustering similar code snippets into patterns.
• Co-administered a design workshop with this design artifact with 7 experts from 3 domains to understand what interactions best assist instructors in navigating these candidate patterns efficiently and effectively.
• Developed a web application framework using HTML/CSS, JavaScript, and Flask to create PLAID, an interface that assists instructors in designing programming patterns in any application-focused domain as part of the Illinois CS Summer Research Program.
• Conducted an evaluation study with 12 instructors from 3 domains using validated survey instruments, including the NASA TLX cognitive load survey and PSSUQ usability survey in a think aloud setting.
• Grounded the design of the LLM-powered pipeline using results from a formative study with 10 instructors. Performed qualitative coding on the interview transcripts to thematically analyze how educators find and create programming patterns and its key challenges.
• Presented preliminary ideas to identify programming patterns and evaluate their quality as a poster at ACM Conference on International Computing Education Research in Jul. 2023.

Human-Computer Interaction Institute. Carnegie Mellon University (& University of Memphis)
Undergraduate Research Intern, GEM Team | May 2024 - Present
Mentors: Dr. Jionghao Lin, Dr. John Hollander, Liang Zhang, Dr. John Sabatini

• Examining the inconsistencies and weaknesses in the properties of large language models in performing reading comprehension tasks. Submitting the findings as a proposal to HCI International 2025 Conference.
• Inspecting the quality of these multiple choice questions using linguistic characteristic comparisons with human-generated questions.
• Coded a RAG-based pipeline for question generation using a few-shot prompting approach to the OpenAI API with readings given to students as context.
• Assessed the accuracy of ChatGPT in answering human-generated questions and evaluated its question-generation capabilities in reading comprehension.
• Developed a tutor-learner simulation with Autogen, enabling a multi-agent interaction-based environment where the learner agent answered questions generated by the tutor agent, and the tutor adapted the difficulty of the questions depending on the learners' responses.

Siebel School of Computing and Data Science. University of Illinois Urbana-Champaign
Undergraduate Research Scholar, SCUBA Lab | Aug 2023 - Present
Mentor: Dr. Eshwar Chandrasekharan

• Designing a quasi-experimental study to identify how exposure to positive and negative feedback mechanisms on Reddit (gilds, upvotes, removals) affect users' longitudinal behavior.
• Identifying feedback mechanisms, including gilds, upvotes, and removals, and measurable outcomes like positive affect and negative affect, to analyze any significant differences in user activity due to exposure.
• Implementing an algorithm to identify treatment and control groups with pre-treatment and post-treatment comments on a large dataset of more than 1,000,000 data points and leveraged LIWC analysis to measure outcomes.
• Performing stratified propensity score matching to group treatment and control authors with the most similar characteristics used DiD estimation to reveal lexico-semantic and content-based changes in user activity.

Siebel School of Computing and Data Science. University of Illinois Urbana-Champaign
Undergraduate Research Scholar, OnCARE Lab | Aug 2023 - Present
Mentor: Dr. Koustuv Saha

• Examined the capabilities of LLMs in supporting users in Alzheimer’s related online communities using causal inference analysis.
• Collected top 50 questions from the r/Alzheimers subreddit using the PRAW API, 70 posts from Alzconnected.org, and queried ChatGPT using the OpenAI API for responses to posts from these social media platforms.
• Employed inductive coding analysis to observe differences between human-authored comments and LLM-generated content.
• Deployed open-source LLMs (Llama and Mistral) on GPUs and the used OpenAI API to gather LLM-generated content for a large-scale quantitative evaluation of psycholinguistics, lexico-semantics, and content level differences.
• Designed pipelines for employing pre-trained classifiers for psycholinguistic analysis, including empathy and formality classifiers.