A machine learning engineer with an interdisciplinary background spanning biology, physics, and computer science. Holds a PhD in Biology, with a focus on bridging understandings of biological and artificial information processing networks. Developed novel techniques to enhance flow cytometry analysis, resulting in a patent-pending algorithm that improves upon decades of standard practice. Additional experience across diverse fields including molecular dynamics simulations, systems biology, physics-based modeling, education research, and more.Skilled at working across disciplines to advance state-of-the-art capabilities in AI and computation. A creative problem-solver able to integrate cross-domain knowledge to push boundaries. Passionate about leveraging interdisciplinary experience to enable AI to reach its full potential and drive innovation. Seeking opportunities to continue multidisciplinary R&D at the leading edge of machine learning and its applications.