About Me

I am a passionate scientist specializing in computational chemistry, drug discovery, and materials science. I earned my PhD from the University of Pittsburgh, where I focused on advancing machine learning (ML) and modeling techniques for novel materials discovery. My primary research centers on modeling chemical physics to enhance the capabilities of AI and ML tools for predicting the properties of molecules and complex systems such as proteins and materials. In addition to publishing multiple works in the chemistry and ML space, I have developed software tools, including a molecular representation Python library tailored for chemistry-focused machine learning applications.

Throughout my academic career, I have worked across a broad range of challenges in computational chemistry and drug discovery. As a postdoctoral researcher, I concentrated on modeling protein systems to support structure-based drug design and virtual screening efforts. My graduate work emphasized integrating machine learning into chemical modeling, including improving conformer generation and building better molecular descriptors to support accurate predictions for both materials and molecular systems.

Earlier in my career, I gained hands-on experience in experimental chemistry, synthesizing conjugated drug linkers for targeted cancer research as an undergraduate. This work gave me a strong appreciation for how computational methods can complement and accelerate laboratory-based discovery.

In addition to my research, I have contributed to the academic community through teaching and mentorship. I served as a General Chemistry Teaching Assistant at both the University of Pittsburgh and Clarkson University, and I mentored students in introductory chemistry labs, helping foster curiosity and confidence in the sciences.

Outside of science, I earned the rank of Eagle Scout in May 2012. This experience helped shape my approach to leadership, teamwork, and ongoing personal development. I am always excited to take on new challenges and explore collaborative opportunities that push the boundaries of what is possible in computational chemistry, materials science, and biology.