Founder & CEO
Lead Optimization Scientist
Michael, our Founder and CEO, is responsible for driving the Company vision. Additionally, Michael serves as Executive Director of McFadden Group, a data-driven advisory firm focused on FinTech and residential mortgage finance.
Previously, Michael served as Chief of Staff and SVP-Finance for Stonegate Mortgage Corporation (NYSE:SGM). He led the company’s IPO efforts in 2013 and Company sale process in 2017, which concluded with a sale to Home Point Financial in May 2017.
Michael earned his undergraduate degree in Physics from University of Indianapolis, where he was also a 4-year member of the baseball team. He also received his MBA from Kelley School of Business at Indiana University and holds the Chartered Financial Analyst (CFA) designation.
Dr. Durai Sundaramoorthi is a Senior Advisor at OptiFunder. Dr. Sundaramoorthi’s is instrumental in the creation of powerful Machine Learning models focused on loan funding and settling predictive analytics. He is also a senior lecturer of Data Analytics at Olin Business School, Washington University in St. Louis. He received his PhD in Industrial Engineering (Data Analytics) from the University of Texas at Arlington. He performed his doctoral research in the Center on Stochastic Modeling, Optimization, and Statistics (COSMOS). He also has a M.S. in Industrial Engineering from the University of Texas at Arlington and a B.S. in Mechanical Engineering from Bharathiar University, India.
Dr. Durai's research interests include Business Analytics, Data Mining, Optimization, Simulation, and Simulation-based Optimization applied to diverse applications. In a collaborative research with nursing and engineering faculty members, and health care professionals from hospitals, he developed a novel data-driven simulation-based analytics approach using tree-based data mining methods to optimize nurse-to-patient assignments based on Big Data from Baylor Regional Medical Center, Grapevine, TX. This research was a pioneering attempt in using Big Data for Business Analytics and Intelligence. The success of this research has paved way to the development of data- driven simulation-based models for other applications. Apart from academic research, he has worked on process improvement projects at Heartland Regional Medical Center, Baylor Regional Medical Center, FedEx, GE, Thomas & Betts, Peabody Energy, Syngenta, and BioMerieux that utilized data mining, simulation, optimization, and financial modeling.
Lingxiu Dong serves as a Senior Advisor to OptiFunder with her main focus on Machine Learning and Optimization algorithm creation. In addition to her role at OptiFunder, Lingxiu is a Professor of Operations and Manufacturing Management at Olin Business School, Washington University in St. Louis. Her current research focuses on developing efficient algorithms for optimal design, control, and contract design in supply chain networks, and exploring innovative solutions to business challenges at the interface of operations-marketing and the interface of operations-finance. A prolific researcher, she has published widely at flagship journals in the field of operations and supply chain management.
She has consulted and collaborated with companies in high-tech, financial service, retail, logistics, and agriculture industries.
She received her Ph.D. degree in Industrial Engineering and Engineering Management from Stanford University. She has also received an M.S. degree in Applied Mathematics from Georgia Institute of Technology and a B.S. degree in Computer Science from University of Science and Technology of China.
Harrison serves as the Lead Optimization Scientist. His experience includes being a data scientist at Bayer Crop Science, mainly working on optimization and machine learning models for breeding pipeline. He earned a Master of Science degree in Operations Research from Cornell University, and a Bachelor of Science in Math from UC Irvine. He has extensive experience in building large-scaled optimization models from scratch and using optimization to improve business decisions.