Optimization Methods in Asset Management

Dr. Garud N. Iyengar is the Tang Family Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he has been a faculty member since 1998. He also serves as the Avanessians Director of the Data Science Institute (DSI) at Columbia, leading initiatives in education and research for data science. Dr. Iyengar's research interests encompass a variety of topics, including convex optimization, robust optimization, queuing networks, combinatorial optimization, and mathematical finance.He received his Ph.D. and M.S. in Electrical Engineering from Stanford University and his B.Tech from the Indian Institute of Technology (IIT). Dr. Iyengar has published extensively in his field, with over 90 publications and two patents to his name. He has held several leadership roles, including Chair of the Department of Industrial Engineering and Operations Research from 2013 to 2019 and Senior Vice Dean for Research and Academic Programs at Columbia Engineering.Dr. Iyengar teaches several courses on Coursera, such as "Introduction to Financial Engineering and Risk Management" and "Optimization Methods in Asset Management," aimed at equipping students with essential skills in finance and operations research.

Dr. Ali Hirsa is a Professor of Professional Practice in the Department of Industrial Engineering and Operations Research at Columbia University, where he has been a faculty member since 2017, having previously served as an Adjunct Professor since 2000. He is also the Managing Partner at Sauma Capital, LLC, a New York hedge fund. Dr. Hirsa's expertise lies in financial engineering, with a focus on asset pricing, derivatives, and optimization methods in asset management.He holds a Ph.D. in Applied Mathematics from the University of Maryland at College Park and an MBA with an emphasis on Finance. Dr. Hirsa has extensive industry experience, having held significant positions at firms such as Morgan Stanley and Banc of America Securities, where he developed quantitative trading strategies.Dr. Hirsa teaches several courses on Coursera, including "Introduction to Financial Engineering and Risk Management" and "Advanced Topics in Derivative Pricing." His research interests include algorithmic trading, machine learning, and computational finance, and he has authored multiple publications in these areas.

Dr. Martin Haugh is an Associate Professor of Practice in Financial Engineering at Columbia University, where he has been a faculty member since 2002, with a focus on financial engineering and operations research. After initially serving at Columbia until 2005, he worked in the hedge fund industry in New York and London, specializing in equity and credit derivatives. He returned to Columbia in 2009 and has since contributed significantly to the field through both teaching and research.Dr. Haugh holds a Ph.D. in Operations Research from MIT, as well as Master of Science degrees from the University of Oxford and University College Cork. His research interests include advanced topics in derivative pricing, risk management, and optimization methods in asset management.He teaches several courses on Coursera, such as "Introduction to Financial Engineering and Risk Management," "Advanced Topics in Derivative Pricing," and "Computational Methods in Pricing and Model Calibration," aimed at equipping students with essential skills in quantitative finance.