Eugenio Culurciello named interim director of Purdue’s Institute for Physical Artificial Intelligence

Karen Plaut, Purdue University’s executive vice president for research, has named Eugenio Culurciello, a professor of biomedical engineering, as interim director of the Institute for Physical Artificial Intelligence (IPAI), a key interdisciplinary research institute that contributes to one of what are now four key pillars in the Purdue Computes initiative.

As IPAI’s interim director, Culurciello’s work will include engaging a larger faculty group through “town halls,” building and maintaining open-access repositories and working with each team to build their research portfolio, and helping to build a curriculum for the recently established online master’s of science program.

“Eugenio brings important leadership skills and deep subject matter expertise at critical time as we establish IPAI,” Plaut said.

A national search will begin for a permanent director.

IPAI will tackle problems at the intersection between the virtual and the physical, leveraging Purdue’s signature strengths in materials science, engineering, microelectronics, computer science and life sciences. The institute is part of the Purdue Computes initiative announced in April, which includes investments in Purdue’s computing faculty and in research on physical AI, semiconductors and (as recently announced)quantum technologies. Since the April announcement, a faculty steering committee and an advisory board have been working to establish the institute’s foundations. This semester, an IPAI cluster faculty search with many colleges will be launched with the Provost’s Office.

Culurciello, who serves on the IPAI faculty steering committee, is a pioneer with more than 20 years of experience in deep learning and neural networks hardware and software and is well positioned to lead the nascent institute.

“I am honored to be able to help colleagues advance Purdue’s reputation and leadership in the physical applications of artificial intelligence and machine learning,” Culurciello said.

Culurciello’s lab is focused on deep learning software and hardware that can replicate the human brain in algorithms and computing devices. He has worked on deep neural networks in applications such as computer vision, speech recognition, multi-modal networks, and NLP, as well as reinforcement learning applied to robotics, and AI algorithms for 3D and graphics. He earned a doctorate in electrical engineering from Johns Hopkins University and is the recipient of numerous honors, including the Presidential Early Career Award for Scientists and Engineers (PECASE) and Distinguished Lecturer of the IEEE (CASS).