Welcome to my website!

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.

Most recently, I’ve been working at Meta Reality Labs as an AI Engineer, focusing on agentic AI systems. I’m contracted through Cognara, a consulting firm that specializes in AI and cognitive devops.

I’m open to full-time opportunities in ML, AI, or full-stack data science 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 & Knowledge Graphs
• Large Language Models & Agentic AI
• 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