Three distinguished MIT computer science professors have achieved the prestigious recognition of being named fellows of the Association for Computing Machinery (ACM) in 2020, honoring their exceptional contributions to the fields of artificial intelligence and computing technology.
These accomplished scholars join an elite group of 95 ACM members acknowledged as the top 1% for their remarkable achievements in computing and information technology. The fellowship program celebrates individuals who have demonstrated extraordinary innovation and service to ACM and the broader computing community, with selections made through a rigorous peer nomination process evaluated by a distinguished committee.
Anantha Chandrakasan, serving as dean of MIT's School of Engineering and holding the Vannevar Bush Professorship in Electrical Engineering and Computer Science, leads pioneering research in energy-efficient circuits and systems. His groundbreaking work spans ultra-low-power IoT devices, energy-efficient processors, machine learning accelerators, hardware security, and advanced wireless systems. Chandrakasan's ACM fellowship recognizes his revolutionary energy-efficient design methodologies enabling next-generation low-power wireless sensors and computing devices essential for modern AI applications.
Alan Edelman, professor of applied mathematics and leader of the Applied Computing Group at MIT's Computer Science and Artificial Intelligence Laboratory, co-created the innovative Julia programming language. His diverse research portfolio encompasses high-performance computing, numerical computation, linear algebra, random matrix theory, and scientific machine learning. Edelman's ACM fellowship celebrates his transformative contributions to numerical algorithms and programming languages that power modern scientific computing and AI research.
Samuel Madden, honored as the MIT Schwarzman College of Computing Distinguished Professor of Computing, specializes in revolutionary database systems research. His work advances database analytics and query processing across diverse environments from cloud infrastructure to sensor networks and high-performance server architectures. As co-director of the Data Systems for AI Lab and the Data Systems Group, Madden pioneers systems and algorithms for integrating machine learning with data management at scale. His ACM fellowship recognizes his influential contributions to data management and sensor computing systems that form the backbone of contemporary AI infrastructure.
