Justin Solomon, associate professor within the MIT Department of Electrical Engineering and Computer Science (EECS), has been appointed associate dean of engineering education within the MIT School of Engineering, effective July 1.
On this latest role, Solomon will give attention to advancing innovation in engineering education across the college. He’ll help shape latest pedagogical approaches within the context of an AI-enabled world and can explore experiential, hands-on, and other modes of learning. Working closely with academic departments, Solomon will function a thought partner in integrating AI into curricula and can help facilitate interdisciplinary and shared teaching opportunities across departments and other schools. He will even play a key role in helping the college implement relevant recommendations from the Committee on AI Use in Teaching, Learning, and Research Training.
Solomon will explore opportunities to construct industry collaborations, including latest models for internships and industry-engaged learning on campus. Collaborating with department heads and the School of Engineering leadership team, he will even support faculty in designing latest courses and evolving existing programs to fulfill emerging opportunities in engineering.
“Justin’s interdisciplinary approach might be especially helpful as we proceed to evolve engineering education to fulfill latest opportunities and challenges. His extensive experience applying AI across a wide selection of domains will help each academic department thoughtfully integrate AI and latest educational models into their curricula,” says Paula T. Hammond, dean of the School of Engineering and Institute Professor. “I sit up for the vision and perspective he’ll bring to the college’s leadership team.”
A dedicated educator, Solomon has played a central role in shaping computing education at MIT. He’s a key contributor to the Common Ground for Computing, where he co-teaches the core class 6.C01 (Modeling with Machine Learning: From Algorithms to Applications) with Regina Barzilay, the Delta Electronics Professor within the MIT Department of Electrical Engineering and Computer Science and affiliate faculty member on the Institute for Medical Engineering and Science. Inside EECS, he teaches 6.7350 (Numerical Algorithms for Computing and Machine Learning) in addition to 6.8410 (Shape Evaluation). He can be the founding father of the Summer Geometry Initiative, a six-week program that introduces students to geometry processing through intensive training, collaboration, and research experiences.
Solomon’s dedication to teaching and helping students has been honored with various awards, including the EECS Outstanding Educator Award and the Burgess (1952) and Elizabeth Jamieson Prize for Excellence in Teaching. He’s the creator of “Numerical Algorithms,” a textbook that presents a contemporary approach to numerical evaluation 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 sits on the intersection of geometry and computation, with applications spanning computer graphics, autonomous navigation, political redistricting, physical simulation, 3D modeling, and medical imaging. He can be a core faculty member of the MIT-IBM Watson AI Lab, contributing to research that advances the foundations and applications of artificial intelligence.
His scholarly contributions have been recognized with quite a few distinctions, including the 2023 Harold E. Edgerton Faculty Achievement Award for exceptional contributions in teaching, research, and repair. In 2025, he was named a Schmidt Polymath, supporting interdisciplinary research across areas comparable to acoustics and climate that depend on large-scale simulation of physical systems.
Solomon joined the MIT faculty in 2016. He previously held an NSF Mathematical Sciences Postdoctoral Research Fellowship in Princeton University’s Program in Applied and Computational Mathematics. He earned his bachelor’s, master’s, and doctoral degrees from Stanford University. While studying at Stanford, he also worked as a research assistant at Pixar Animation Studios.