I build large language models end to end, from data curation and pretraining to fine-tuning and evaluation, with a focus on code generation in settings the field tends to overlook.
I completed my Ph.D. in Computer Science at George Mason University in 2026, advised by Dr. Marcos Zampieri and Dr. Antonios Anastasopoulos. I defended and passed in June 2026. My dissertation, Exploring and Adapting Code LLMs for Underrepresented Domains, asks a recurring question: what happens to code models once you step outside English, outside Python, and outside the benchmarks everyone already optimizes for?
In Fall 2026 I join the University of Notre Dame as a Provost's Postdoctoral Fellow in Computer Science & Engineering, working with Dr. Joanna C. S. Santos on safety-by-construction guardrails and multilingual program synthesis for Code LLMs. Along the way I have released open benchmarks, corpora, and models, including mHumanEval, TigerLLM, TigerCoder, and MojoBench, that the community can build on.
Code LLMs & program synthesis
Adapting code models to low-resource programming languages and underexplored domains.
Read more →Multilingual & low-resource NLP
Evaluation and modeling across natural languages, with a focus on Bangla and code-mixed text.
Read more →LLM safety & AI in CS education
Guardrails for code assistants and the role of LLMs in introductory computing.
Read more →Benchmarks & datasets
Large, openly released resources that make under-tested settings measurable.
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