Bio

This all started with wastewater! Ever since I was first introduced to the power and beauty of computer aided problem solving when I was given the task of translating bacterial bio-chemical reactions into ones and zeros at Cargill I have been hooked. A passion for solving computer aided problems was born and naturally evolved to a Ph.D. where I focused on the technical and economic optimization and analysis of biorefineries. Today, the focus is not bacteria or biorefineries but world-scale supply chains for Dow. The same rules hold true, focus on asking the right questions, solving the right problems, and keeping the economic incentive front and center. Technically, I have added to my MIP skills developed during my Ph.D. with additional capabilities in ML, DL, and RL model development. I work as part of a full-stack agile scrum team to build and deploy complete end-to-end solutions which deliver value for internal partners. All in all, I love to solve problems that drive value for companies using mathematics. Bringing AI to a legacy global manufacturer has not always been a smooth ride (no surprise there!) but this has allowed me to grow tremendously and now I am a leading part of the team responsible for defining the AI Strategy for Dow. Outside of work I tend to find myself coding still - be it home automation, tinkering with self-driving robots (Jetbot) or the occasional kaggle competition but also find myself being the family IT/tech guy - a role I actually enjoy playing. I am also passionate about inspiring the next generation and have volunteered for STEM outreach efforts and mentor University of Minnesota graduate students. Skills/Experience/Interest: Mixed Integer Programming, Machine Learning, Deep Learning, Reinforcement Learning, Python, Gurobi, scikit-learn, Tensorflow, PyTorch, Ray (RLLib, Ray Tune, Ray Serve), Azure ecosystem, Agile Development.