John Tsitsiklis
John N. Tsitsiklis is a Clarence J Lebel Professor, with the Department of Electrical Engineering and Computer Science (EECS) at MIT and the Laboratory for Information and Decision Systems (LIDS).
Munther Dahleh is director of the Institute for Data, Systems, and Society. He was previously the associate department head of EECS. He is also a member of MIT’s Laboratory for Information and Decision Systems (LIDS).
Discover Applied AI and Data Science Program: a comprehensive curriculum designed for professionals seeking to excel in data analysis, agentic AI, visualization, and machine learning. Gain hands-on experience & earn a prestigious certificate of completion by MIT Professional Education.
An active area of research, reinforcement learning has already achieved impressive results in solving complex games and a variety of real-world problems. However, organizations that attempt to leverage these strategies often encounter practical industry constraints. In this dynamic course, you will explore the cutting-edge of RL research, and enhance your ability to identify the correct approach for applying advanced frameworks to pressing industry challenges.
Artificial intelligence (AI) is a powerful tool—but without the right system-wide architecture in place to support your initiatives, your organization is leaving value on the table. Featuring interactive exercises, industry speakers, and a hands-on group project, this dynamic five-day course is designed to equip you with the skills and strategies you need to deploy an AI systems engineering approach that maximizes the value of your digital products and services.
Robert T-I. Shin
Dr. Robert T-I. Shin is a Principal Staff member in the Intelligence, Surveillance, and Reconnaissance (ISR) and Tactical Systems Division at MIT Lincoln Laboratory. He is also the Director of the MIT Lincoln Laboratory Beaver Works Center and a member of the MIT School of Engineering Extended Engineering Council. Prior to becoming Principal Staff, he served as the Head of the ISR and Tactical Systems Division, where he oversaw research and prototype development of systems for ISR, tactical applications, and counterinsurgency and counterterrorism, and he oversees programs assessing U.S. air vehicle survivability.
Jonathan E. Gans
Dr. Jonathan E. Gans leads the Systems and Architectures Group at MIT Lincoln Laboratory. He oversees multiple BMD related programs for the Missile Defense Agency, Office of the Secretary of Defense, and the Air Force, with a focus on developing new discrimination techniques and providing in-depth assessments of domestic and foreign Ballistic and Hypersonic defense concepts. Dr. Gans recently led a report to Congress on Space Based Interceptors and his team was a major contributor to the MDA Defense Against Hypersonic Weapons AoA. Jonathan graduated from Vassar College in 1999 and earned a Ph.D. in particle physics from Yale University in 2004.
Edwin F. David
Dr. Edwin F. David is the Head of the Engineering Division at MIT Lincoln Laboratory. He joined the Laboratory in 1998 as a technical staff member in the Systems and Analysis Group, supporting the Air Vehicle Survivability program. His research focused on modeling, simulation, and testing of navigation and guidance systems, sensor systems, and directed energy systems. In this role, he supported the Defense Science Board Task Force for the Global Positioning System space segment modernization. He also served as program manager for the Directed Energy Countermeasures Assessment Team.
Chris Gordon has been a lecturer at MIT’s Center for Real Estate for over 20 years. He teaches a course on Innovative Project Delivery in the Public & Private Sectors in our MSRED program. As a practitioner, Chris serves as an advisor and manager on complex capital projects worldwide. He works in a hands-on capacity to establish the project strategies, project team, and management process, and then monitors and/or leads the project to improve the chances of success significantly. He is also a Lecturer at both the Harvard Business School and the Massachusetts Institute of Technology Center for Real Estate, teaching several courses and writing on complex capital projects.
Reinforcement learning (RL), is enabling exciting advancements in self-driving vehicles, natural language processing, automated supply chain management, financial investment software, and more. In this three-day course, you will acquire the theoretical frameworks and practical tools you need to use RL to solve big problems for your organization.