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Research Assistant, Machine Learning Research Group

Oracle Labs

Mentored by Alex Kogan.

• Inference optimization for mixture-of-experts LLMs; accelerated Llama 4 token generation on a single H100

Student Researcher

Google Research

Generative ranking for information retrieval, with Felix Yu's team (New York).

• Proved expressivity advantages of pointwise generative ranking over dual encoders; proposed SToICaL, a rank-aware token–item calibrated loss for LLM finetuning (arXiv:2601.05588)
• Invited talk at Google DeepMind (Feb 2026) after the group moved from Google Research

Research Assistant, Machine Learning Research Group

Oracle Labs

Mentored by Ari Kobren.

• LLM agents for automated program repair (Bug Fixes via Latent Program Sketches)

Scientist Intern

Charles River Analytics

Research internship in Cambridge, MA.

• Transformer-based contrastive learning for authorship embeddings (IARPA HIATUS) — advanced CRA from last to 2nd place in evaluation
• Probabilistic programming in Pyro for generation/inference of military activity patterns

PhD Student

University of Massachusetts, Amherst

Doctoral research in machine learning and NLP, advised by Andrew McCallum.

• Discrete diffusion models for text — non-autoregressive, flexible, and controllable language generation (thesis focus)
• Generative ranking for information retrieval
• Efficient inference with mixture-of-expert LLMs
• Geometric representation learning for large directed graphs

Engineer II

Raytheon BBN Technologies

Software engineer and researcher in information extraction and NLP.

• Multilingual information extraction (DARPA AIDA)
• Full NLP stack for COVID-19 machine reading system (IARPA COVID Seedling)
• Maintained internal NLP and deep learning libraries; integrated open-source and research models

Research Intern (TechStudent)

Raytheon BBN Technologies

Summer research internship.

• Multilingual neural relation extraction via machine translation and MGIZA++ token-level annotation projection to train mBERT

Teaching Assistant

Brandeis University

TA for five undergraduate and graduate courses.

• Statistical Approaches to NLP (Fall 2019)
• Phonological Theory (Spring 2019)
• Data Structures and Algorithms (Fall 2018)
• Theory of Computation (Spring 2018)
• Discrete Structures (Fall 2017)

Research Assistant

Brandeis University — BiRCh Project

Bilingual Russian Children corpus.

• Morphological analysis, parsing, segmentation, tokenization, transcription, and adjudication

PhD

University of Massachusetts, Amherst

Computer Science

• Machine Learning
• Distributed and Operating Systems
• Advanced Algorithms
• Probabilistic Graphical Models
• Reinforcement Learning
• Randomized Algorithms

MS

Brandeis University

Computational Linguistics

BS

Brandeis University

Computer Science, Linguistics, and Mathematics

🥈 Silver Reviewer Award

International Conference on Machine Learning (ICML)

Aravind K. Joshi Award for Outstanding Achievement in Computational Linguistics

Brandeis University

Giumette Academic Achievement Award

Brandeis University

Humanities Fellowship

Brandeis University