Machine Learning Research Scientist
As both a scientist and an engineer by training, I’m motivated by work that blends deep investigation with disciplined system-building. I enjoy using scientific exploration to uncover insights that generalize, while applying an engineering mindset to translate those insights into scalable, dependable tools. I’m especially drawn to problems where Natural Language Processing, Database Systems, and Statistical Modeling intersect with complex, real-world challenges.
I currently lead applied AI research at the Big Data Analytics Lab of New Jersey Institute of Technology, where my team builds predictive-maintenance and retrieval-augmented generation products for the U.S. Navy. I also partner with Materium Technologies as a Consulting Machine Learning Engineer to develop inverse-design pipelines for polymer nanocomposites. I earned my M.S. in Statistics from the University of Chicago, and I’m always interested in work that connects rigorous research with impactful engineering.
Outside of research, I experiment with automated music production and sound design—blending algorithms, synthesizers, and generative tools to explore new ways of creating rhythm and texture.
For collaboration or inquiries, you can reach me via email or connect with me on LinkedIn.