The ESD PhD program aims to produce the next generation of leading engineering systems researchers and thinkers. It provides students with a strong technical foundation and puts an emphasis on inter-disciplinary and collaborative research. This is enhanced by experiences in industry, teaching, and international exchange. The program is mentoring-intensive with a unique flexible advising structure that allows students to work with multiple faculty members and faculty members to engage with multiple students. PhD students also benefit from professional development opportunities with a focus on soft skills, including communication, leadership, and entrepreneurship. Students attending the PhD program go through a rigorous set of common core courses in optimization, operations management, probability and statistics; moreover they will also have the opportunity to choose form a diverse set of elective courses that allows them to gain in-depth knowledge in one or more specialization areas.
The Distinctiveness of the ESD PhD
The ESD PhD program offers students the opportunity to work with faculty who are at the very forefront of their fields and come from the very best universities in the world, including MIT, Stanford, Cambridge, and Cornell, and with diverse nationalities, including countries from North America, Europe, and Asia Pacific.
The ESD pillar is rapidly growing and will continue to do so for the next several years. ESD faculty are engaged in leading edge research in a wide range of disciplines including optimization, stochastic modeling, game theory, economics, control science, system dynamics, public policy, organizational and behavioral sciences. They are also engaged in important applications including supply chains, transportation and logistics, healthcare, energy and the environment, service systems, financial engineering, critical infrastructure and security, social networks, telecommunication systems, renewable energy, and electricity markets. ESD faculty are tackling these problems using analytical, computational, empirical, and experimental approaches and methodologies.