About

I am a Research Scientist at Dataminr, where I design, deploy, and evaluate production LLM and agentic AI systems that reason over hundreds of millions of real-time events every day.

My work sits at the intersection of large language models, agentic systems, natural language processing, and information retrieval — taking ideas from problem definition through deployment, monitoring, and iteration in production. I focus on making these systems genuinely useful and dependable: grounded, well-calibrated, and reliable under real-world load.

I completed my Ph.D. in Computer Science at the University of Massachusetts Amherst, advised by Prof. W. Bruce Croft, followed by a postdoc with Prof. Carsten Eickhoff at Brown University. During my Ph.D. I interned at Microsoft Research. My research on neural retrieval, robustness, and uncertainty has appeared at venues including ACL, NAACL, SIGIR, EMNLP, CIKM, and ICML, with two best-paper awards.

You can browse my publications, read my CV, or find my full list of papers on Google Scholar.