In a sunlit conference room in Amy Gutmann Hall, a group of researchers convenes for a regular lunch meeting. Physicists converse with linguists, computer scientists collaborate with chemists, and psychologists speak to engineers. These postdoctoral researchers represent the University’s response to a shifting research landscape prompted by recent advances in artificial intelligence (AI).
Pointing to those gathered, Bhuvnesh Jain, who co-directs the School of Arts & Sciences’ Data Driven Discovery Initiative (DDDI) notes that “at Penn, we have a remarkable opportunity to build on our closely knit community of researchers in dozens of fields across all our Schools. Postdoctoral fellows are at the forefront of our research, and so that’s the group we are bringing together.”
This breadth is precisely what Penn is leveraging as AI development increasingly shifts from academic labs to corporate campuses, says Penn Integrates Knowledge University Professor René Vidal, who directs the School of Engineering and Applied Science’s Innovation in Data Engineering and Science Initiative.
Jain, a cosmologist by training, teamed up with Vidal, whose work centers around machine learning, to create AI x Science, a postdoctoral fellowship that brings together researchers from across the University in seemingly disparate domains to enhance and accelerate discovery. The selected fellows receive a small stipend, research funding, and dual mentorship, plus structured opportunities for peer engagement through weekly lunches, mixers, co‑hosted seminars, and hands‑on access to campus research centers, laboratories, and computational resources.