Aloimonos Is Named IEEE Fellow
Yiannis Aloimonos, a professor of computer science with an appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), was just named a Fellow of the Institute of Electronic and Electrical Engineers (IEEE), the world’s largest technical professional organization for the advancement of technology.
Aloimonos joins 340 other researchers worldwide in receiving Fellow status for 2025, the highest grade of IEEE membership, and one that is recognized by the technical community as a prestigious honor and an important career achievement. Each year, only 0.1%, at most, of the 450,000-plus IEEE voting members can be elevated to Fellow status.
Aloimonos was specifically noted for his work involving active perception—biologically-inspired mechanisms that allow computers to shift their geometric parameters to improve their sensory abilities—and his work in the perception of action, the process by which computers can sense their environment, as well as specific objects and movement within that environment.
Much of Aloimonos’ research in these areas has been applied to computer vision systems used in robotics and other autonomous vehicles, including groundbreaking work in small drones that can pollinate flowers.
Aloimonos has edited two books on active perception, one titled “Active Perception” and the other “Visual Navigation.” He is also the author of several papers that expanded scientific knowledge on visual motion analysis, including the concept of a trilinear tensor that could identify the constraint between lines (or points) from three different viewpoints.
His computer vision work in obstacle avoidance has been of great value to small autonomous drones used in search and rescue operations or for the inspection of infrastructures. Other work with drones involves minimizing the computing power needed for the vehicle to accomplish its task.
His academic papers devoted to active perception as a methodology have received more than 3,340 citations, with other academic work related to visual motion analysis, segmentation and tracking having a similar number of citations.
Aloimonos’ work in perception of action is essential for two areas in computing—the recognition of human activity from videos, and imitation learning in robotics. He co-authored a landmark paper on this work in 2012 that introduced the concept of minimalist grammar for human action as it relates to computer vision platforms.
His seminal work in imitation learning resulted in a flurry of media activity, when, in 2015, his team’s research involving a robot that could teach itself to cook by watching YouTube cooking videos went viral, with media coverage including stories in The Washington Post, USA Today, NBC News and other outlets. A YouTube video featuring this work earned more than 30,000 views within 48 hours of it being posted.
Aloimonos came to the University of Maryland (and UMIACS) in late 1986 after earning his Ph.D. in computer science from the University of Rochester.
He currently co-directs the Perception & Robotics Group at the University of Maryland along with Cornelia Fermüller, a research scientist in UMIACS. The group is active in research and scholarship, with more than 30 academic papers accepted to major conferences and workshops in 2024 alone.
Aloimonos has advised more than 40 Ph.D. dissertations during his time at the University of Maryland. In addition to his appointments in computer science and UMIACS, Aloimonos is active in the Maryland Robotics Center, the Institute for Systems Research and the Brain and Behavior Institute.
Go here to view an overview of Aloimonos’ work in a video produced in 2023 by the College of Computer, Mathematical, and Natural Sciences.