With over seven years of progressive experience at Ford Motor Company, culminating in my current roles as a Data Science Manager and Tech Lead, I specialize in steering the entire data science lifecycle for high-impact automotive projects. I lead teams from initial data exploration and model conceptualization through to the architecture and deployment of robust, enterprise-scale machine learning pipelines. My work has been central to driving measurable improvements in Ford's Electric Vehicle (EV) customer experience and enhancing company-wide operational efficiency.

My project portfolio includes delivering advanced AI solutions for critical business needs, such as optimizing vehicle cycle plans, architecting cost-effective fleet management strategies for Autonomous Vehicles (AVs), and pioneering fully autonomous customer support systems from concept to pilot testing. To achieve this, I leverage a modern AI toolkit, applying Generative AI to build sophisticated customer chatbots and using Explainable AI (XAI) and Natural Language Processing (NLP) to unlock actionable insights from complex datasets. As a hands-on leader, I am also a proficient software engineer (Python, Java, SQL) with a firm grasp of MLOps, enabling me to bridge the gap between research and production to rapidly deliver high-quality AI products.

This practical industry experience is built upon a rigorous academic foundation, including a Ph.D. in Mechanical Engineering from the University of Illinois at Urbana-Champaign and a Postdoctoral Research Fellowship at the University of Michigan. My core research in Optimization, Robotics, and Multi-agent Systems directly informs my approach to solving complex AI problems today. My contributions to the field are further demonstrated by over 10 first-author publications in premier robotics and AI conferences and journals, including T-RO, ICRA, and IROS.