Justin Solomon, associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), has been named associate dean for engineering education at the MIT School of Engineering, effective July 1.
In this modern role, Solomon will focus on supporting innovation in engineering education across the school. It will facilitate shape modern pedagogical approaches in the context of an AI-enabled world and explore experiential, hands-on and other ways of learning. Working closely with academic departments, Solomon will serve as a thought partner in integrating AI into curricula and will facilitate create interdisciplinary and collaborative learning opportunities between departments and other schools. He will also play a key role in helping the school implement relevant recommendations from the Commission on the apply of AI in teaching, learning and research training.
Solomon will explore opportunities to build industry collaborations, including modern models of on-campus internships and industry-led learning. Working with department chairs and the School of Engineering leadership team, he will also support faculty in designing modern courses and developing existing programs to meet emerging opportunities in engineering.
“Justin’s interdisciplinary approach will be especially valuable as we continue to advance engineering education to meet new opportunities and challenges. His extensive experience applying artificial intelligence across a wide range of fields will help every academic department thoughtfully integrate artificial intelligence and new educational models into their curricula,” says Paula T. Hammond, dean of the School of Engineering and professor at the institute. “I look forward to the vision and perspective he will bring to the school’s leadership team.”
As a dedicated educator, Solomon played a key role in shaping computer science education at MIT. He is a key contributor to Common Ground for Computing, where he co-teaches Primary 6.C01 (Modeling with machine learning: from algorithms to applications) with Regina Barzilay, Delta Electronics Professor in MIT’s Department of Electrical Engineering and Computer Science and faculty member of the Institute for Medical Engineering and Science. Within EECS, he teaches 6.7350 (numerical algorithms in computer science and machine learning) and 6.8410 (shape analysis). He is also the founder Summer Geometric Initiativea six-week program that introduces students to geometry processing through intensive training, collaboration, and research experiences.
Solomon’s commitment to teaching and helping students was recognized with various awards, including the EECS Outstanding Educator Award and the Burgess Award (1952) and the Elizabeth Jamieson Award for Excellence in Teaching. He is the author of “Numerical Algorithms” – a textbook presenting a newfangled approach to numerical analysis for computer science students.
Solomon is a principal investigator at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), where he leads the Geometric Data Processing Group. His research focuses on the intersection of geometry and computation, with applications including computer graphics, autonomous navigation, political boundary transition, physical simulation, 3D modeling, and medical imaging. He is also a core faculty member of the MIT-IBM Watson AI Lab, contributing to research on the fundamentals and applications of artificial intelligence.
His scholarly contributions have been recognized with numerous honors, including the 2023 Harold E. Edgerton Faculty Achievement Award for outstanding contributions to teaching, research and service. In 2025 he received the title Schmidt Polymathsupporting interdisciplinary research in areas such as acoustics and climate that relies on large-scale simulations of physical systems.
Solomon joined the MIT faculty in 2016. Previously, he was the recipient of an NSF Mathematical Sciences Postdoctoral Research Fellowship at Princeton University’s Applied and Computational Mathematics program. He received bachelor’s, master’s and doctorate degrees from Stanford University. While attending Stanford University, he also worked as a research assistant at Pixar Animation Studios.