Welcome to my website!

I’m a machine learning researcher and engineer with expertise in NLP, deep learning, LLMs, and knowledge graphs, backed by formal education in mathematics and computer science. I specialize in building practical ML applications while bringing versatile experience across front-end development and scientific computing.

My work sits at the intersection of theoretical ML and practical engineering, combining rigorous mathematical thinking with hands-on software development. Through this portfolio, I showcase selected projects that demonstrate my ability to translate complex ML concepts into impactful applications.

I’m currently employed at Pacific Northwest National Laboratory as a Machine Learning Research Associate, where my work has involved developing RAG systems, interactive web applications, and physics-based environmental simulations.

I’m open to full-time opportunities in { ML | data } { science | engineering} in the greater Boston area. Feel free to reach out if you think I’d be a good fit for your team!

Expertise:

  • Natural Language Processing & Large Language Models
  • Network Science & Knowledge Graphs
  • Full-stack Development
  • Data Science & Machine Learning

Publications

  • Ammon C Shurtz, Lawry Sorenson, Braden K Webb, Momoka Matsushita, Kelly Ko, Stephen D. Richardson. MMMC: A Massively Multi-way-aligned Multilingual Corpus. In progress.

  • Braden K Webb, Sumit Purohit, Rounak Meyur. Cyber Knowledge Completion Using Large Language Models. Under review. https://arxiv.org/abs/2409.16176

  • Rounak Meyur, Sumit Purohit, Braden K Webb. Fortify Your Defenses: Strategic Budget Allocation to Enhance Power Grid Cybersecurity. Presented at The AAAI-24 Workshop on Artificial Intelligence for Cyber Security, Feb 26, 2024, Vancouver, Canada. https://arxiv.org/abs/2312.13476

  • Trevor Ashby, Braden K Webb, Gregory Knapp, Jackson Searle, and Nancy Fulda. 2023. Personalized Quest and Dialogue Generation in Role-Playing Games: A Knowledge Graph- and Language Model-based Approach. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ‘23). Association for Computing Machinery, New York, NY, USA, Article 290, 1–20. https://doi.org/10.1145/3544548.3581441

Projects

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