Young Innovators | Generated by AI
The MIT Technology Review’s “35 Innovators Under 35” list recognizes outstanding young individuals who are making significant contributions to various fields, including computer science and machine learning. These individuals are not necessarily MIT alumni, but their work is considered groundbreaking and impactful.
It’s important to understand that the list encompasses a broad range of innovation, and while many honorees work in areas related to computing and AI, not all are strictly focused on “computer & machine learning” in a traditional academic sense. Their work often involves applying these technologies to solve real-world problems in diverse domains.
Here are some notable figures who have been recognized by the MIT 35 Under 35 and whose work significantly intersects with computer science, machine learning, and related fields:
- Regina Barzilay: An MIT Professor in the Department of Electrical Engineering and Computer Science, she was recognized for her innovative machine learning algorithms that have led to advances in human language technology and demonstrated impact on the field of medicine, particularly in drug design and early cancer diagnostics. She received the IEEE Frances E. Allen Medal in 2025 for this work.
- Shawn Shan: A PhD student at the University of Chicago, co-advised by professors who were themselves MIT TR35 recipients, Shan was named an MIT Technology Review’s 35 Innovators Under 35 and Innovator of the Year for his work on Glaze and Nightshade. These tools protect artists from the exploitation of generative AI models by masking their artistic style from AI mimicry and introducing “proactive protection” systems.
- Anna Ivanova: An alumna of MIT with a PhD, now at the Georgia Institute of Technology, Ivanova is recognized for her work in unlocking a greater understanding of how both large language models and the human brain work.
- Cynthia Breazeal: An MIT alumna and professor at the MIT Media Lab, she is a pioneer in social robotics and the founder of Jibo, Inc., which created a personal assistant robot. Her work focuses on the principles and potential of social robots to help people achieve personal goals in areas like education, health, and well-being.
- Dina Katabi: An MIT Professor in the Department of Electrical Engineering and Computer Science, and a MacArthur Fellow, her work revolves around wireless networks, mobile computing, and applying machine learning to improve network performance and reliability.
- Erik Demaine: An MIT Professor of Computer Science, his research spans algorithms, data structures, computational geometry, and the mathematical theory of origami, often with applications in robotics and other fields. He was a recipient of the MacArthur Fellowship.
- Daniela L. Rus: The Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, her research interests include robotics, artificial intelligence, and machine learning, with a focus on developing intelligent robots that can collaborate with humans.
- Joy Buolamwini: An MIT Media Lab alumna, she founded the Algorithmic Justice League, which works to highlight algorithmic bias in AI systems, particularly in facial analysis technology, and develop practices for accountability.
- Leila Pirhaji: An MIT alumna with a PhD, she founded ReviveMed, a startup that uses AI technology developed at MIT to leverage metabolomics data for expediting drug discovery.
- Feng Zhang: While primarily known for his work in CRISPR technology, which has revolutionized genetic engineering, Zhang is an alumnus of MIT and his work heavily involves computational biology and machine learning for analyzing genomic data.
This list is not exhaustive, and many other MIT 35 Under 35 honorees have made significant contributions to areas closely related to computer science and machine learning, even if their primary field is listed differently (e.g., biotechnology, materials science). The award celebrates the interdisciplinary nature of innovation and the increasing role of computational methods in various scientific and technological advancements.
To get a more comprehensive list, you can explore the MIT Technology Review’s “Innovators Under 35” website, which has archives of past honorees categorized by year and field. You can then filter or search for individuals whose work aligns with computer science and machine learning.