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Justin Solomon appointed associate dean of engineering education | MIT News



Justin Solomon, associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), has been appointed associate dean of engineering education in the MIT School of Engineering, effective July 1.

In this new role, Solomon will focus on advancing innovation in engineering education across the school. He will help shape new pedagogical approaches in the context of an AI-enabled world and will explore experiential, hands-on, and other modes of learning. Working closely with academic departments, Solomon will serve as a thought partner in integrating AI into curricula and will help facilitate interdisciplinary and shared teaching opportunities across departments and other schools. He will also play a key role in helping the school implement relevant recommendations from the Committee on AI Use in Teaching, Learning, and Research Training. 

Solomon will explore opportunities to build industry collaborations, including new models for internships and industry-engaged learning on campus. Collaborating with department heads and the School of Engineering leadership team, he will also support faculty in designing new courses and evolving existing programs to meet emerging opportunities in engineering.

“Justin’s interdisciplinary approach will be especially valuable as we continue to evolve engineering education to meet new opportunities and challenges. His extensive experience applying AI across a wide range of domains will help each academic department thoughtfully integrate AI and new educational models into their curricula,” says Paula T. Hammond, dean of the School of Engineering and Institute Professor. “I look forward to the vision and perspective he will bring to the school’s leadership team.”

A dedicated educator, Solomon has played a central role in shaping computing education at MIT. He is 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 in the MIT Department of Electrical Engineering and Computer Science and affiliate faculty member at the Institute for Medical Engineering and Science. Within EECS, he teaches 6.7350 (Numerical Algorithms for Computing and Machine Learning) as well as 6.8410 (Shape Analysis). He is also the founder 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 is the author of “Numerical Algorithms,” a textbook that presents a modern 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 sits at the intersection of geometry and computation, with applications spanning computer graphics, autonomous navigation, political redistricting, physical simulation, 3D modeling, and medical imaging. He is also 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 numerous distinctions, including the 2023 Harold E. Edgerton Faculty Achievement Award for exceptional contributions in teaching, research, and service. In 2025, he was named a Schmidt Polymath, supporting interdisciplinary research across areas such as acoustics and climate that rely 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.



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