Three MIT computer technology faculty members have actually been elected as fellows of the Association for Computing Machinery (ACM).

The brand-new fellows are among 95 ACM members acknowledged as the top 1 percent for their exceptional accomplishments in computing and infotech and/or outstanding service to ACM and the bigger computing community. Fellows are chosen by their peers, with nominations examined by a prominent choice committee.

Anantha Chandrakasan is dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Technology. He leads the MIT Energy-Efficient Circuits and Systems Group, which works on a variety of jobs such as ultra-low-power internet-of-things devices, energy-efficient processors, artificial intelligence processors, hardware security for computing gadgets, and wireless systems. He was acknowledged as a 2020 ACM fellow for energy-efficient design methodologies and circuits that enable ultra-low-power cordless sensors and computing gadgets.

Alan Edelman is an applied mathematics professor for the Department of Mathematics, the Applied Computing Group leader for the Computer Science and Expert System Laboratory, and co-founder of the Julia programming language. His research study consists of high-performance computing, mathematical computation, direct algebra, random matrix theory, and clinical machine learning. He was acknowledged as a 2020 ACM fellow for contributions to algorithms and languages for mathematical and scientific computing.

Samuel Madden is the MIT Schwarzman College of Computing Distinguished Professor of Computing. Madden’s research is in the area of database systems, focusing on database analytics and query processing, ranging from clouds to sensing units to modern high-performance server architectures. He co-directs the Data Systems for AI Lab initiative and the Data Systems Group, examining concerns related to systems and algorithms for information concentrating on applying new methods for processing data, including applying machine learning methods to data systems and engineering information systems for applying artificial intelligence at scale. He was recognized as a 2020 ACM fellow for contributions to information management and sensing unit computing systems.