Machine learning

Thomas Dietterich will receive the highest honor for a career in artificial intelligence for his four decades of intellectual leadership in machine learning. Only 23 others have received the Award for Research Excellence from the International Joint Conference on Artificial Intelligence since its inception in 1985. The first to receive the award was John McCarthy, known as the father of AI. Dietterich will accept the award in August at the annual conference 2024 IJCAI in Jeju, South Korea.

Zahir Alsulaimawi, a postdoctoral researcher in the School of Electrical Engineering and Computer Science at Oregon State University, received a best paper and presentation award at the Sixth International Conference on Big Data and Artificial Intelligence.

Alsulaimawi, who earned master’s and doctoral degrees in electrical and computer engineering at Oregon State, researches ways to make machine learning models smarter without compromising people’s privacy.

Sanghyun Hong, assistant professor of computer science at Oregon State University, has been selected as one of six cybersecurity researchers in the U.S. to participate in the 2023 Google Research Scholar Program.

Supporting growth in Internet of Things systems is the primary thrust of the NSF-funded Pervasive Personal Intelligence Center. Started just over 2 1/2 years ago, the PPI center, led by the University of Colorado Boulder, includes Oregon State University and, soon, Oakland University. Involving seven faculty members and 13 graduate students thus far, the PPI center supports growth in IoT systems that push Pervasive Personalized Intelligence to the edge of the network, where minimizing latency is critical.

Cassie the bipedal robot recently earned a spot in the Guinness Book of World Records for being the fastest two-legged robot on Earth, running the 100-meter dash in just under 25 seconds. The feat is especially impressive, considering Cassie pulled it off blind, without an onboard camera. Instead, Cassie first learned how to run through a series of “sim-to-real” training sessions.