Postdoctoral Researcher / Arizona State University

Hi, I'm Jeevan Chapagain

Learning Engineering Institute, Arizona State University

LLMs, NLP, educational AI, intelligent tutoring systems, code comprehension, and automated assessment.

Jeevan Chapagain

About Me

Learning systems meet language intelligence

Currently I am working as a postdoctoral researcher at the Learning Engineering Institute at Arizona State University, conducting my research under the mentorship of Dr. Danielle McNamara.

I completed my Ph.D. in Computer Science at The University of Memphis, where I conducted my research in the Language and Information Processing (LIPS) Lab under the guidance of Dr. Vasile Rus in the Department of Computer Science. My research focused on NLP, machine learning, and large language models, with an emphasis on educational AI, code comprehension, and automated assessment. I also worked on developing benchmark datasets and fine-tuning language models to improve intelligent, user-centered learning systems. Prior to that, I completed my MS in Computer Science at the University of Memphis in 2023 and obtained my B.Sc. in Computer Science and Information Technology from the Tribhuvan University in Nepal.

Beyond my main research, I am also interested in NLP for low-resource languages, especially Nepali, where I have worked on creating benchmark datasets and developing algorithms for named entity recognition. If you are interested in such work, let’s connect and work together.

In my free time, I love being outdoors;playing soccer, going on hikes, or camping with friends. I also enjoy unwinding with a good book or getting lost in a movie or documentary. When I want to relax and recharge, I usually play my guitar or play a game of chess to keep my mood fresh.

Research Interests

Large Language Models Natural Language Processing Educational AI Intelligent Tutoring Systems Code Comprehension Automated Assessment Low-resource Languages Nepali NLP Machine Learning
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News

Recent updates

Recent research activities, talks, papers, and conference updates.

Paper titled Enhancing Intelligent Tutoring Systems with Instruction-Tuned LLMs: Automated Assessment of Student Code Comprehension accepted as a full paper at Artifical Intelligence in Education(AIED2026) Conferene.

Presented research paper titled “SelfCode 2.0: An Annotated Corpus of Student and Expert Line-by-Line Explanations of Code Examples for Automated Assessment” at FLAIRS-38

Presented research paper titled “Generative AI for Named Entity Recognition in Low-Resource Language Nepali” at FLAIRS-38

Presented research paper titled “Automated Assessment of Student Self-explanation in Code Comprehension Using Pre-Trained Language Models” at EAAI25

Presented research paper titled " A Study of LLM Generated Line-by-line Explanations in the Context of Conversational Program Comprehension Tutoring Systems at 19th European Conference on Technology Enhanced Learning(ECTEL)

Presented research paper titled “SelfCode: An Annotated Corpus and a Model for Automated Assessment of Self-explanation during Source Code Comprehension” at FLAIRS-36

Presented research paper titled “DanfeNER - Named Entity Recognition in Nepali Tweets” at FLAIRS-36

Presented research paper titled “Automated Assessment of Student Self-explanation During Source Code Comprehension” at FLAIRS-35

Presented research paper titled “Named Entity Recognition for Nepali: Data Sets and Algorithms” at FLAIRS-35