The workshop was over. Rows of brown bag lunches were lined up and ready to be taken from a conference table covered in a black tablecloth. A bus was waiting outside.
But still, participants at the event, titled “Foundational & Applied Data Science for Molecular and Material Science & Engineering” lingered, talking in small groups in Iacocca Hall’s Wood Dining Room on Lehigh University’s Mountaintop Campus. It was exactly the scene the workshop was meant to generate.
“There was a common thread here of machine learning and data science, but the workshop brought together a diverse range of fields, which gave people the opportunity to engage with those they wouldn’t ordinarily encounter,” says Srinivas Rangarajan, an assistant professor of chemical and biomolecular engineering at the P.C. Rossin College of Engineering and Applied Science. “And that was the goal of the event—to bring together top experts from a range of disciplines to share the latest techniques as well as the challenges in machine learning.”
The three-day event—organized by Rangarajan, fellow Lehigh engineering faculty members Jeetain Mittal and Joshua Agar, and Payel Das of IBM Thomas J Watson Research Center—started on May 22, and was the first in a series of conferences and lectures funded by an NSF TRIPODS-X grant awarded to Lehigh’s Institute for Data, Intelligent Systems, and Computation (I-DISC).
Paulette Clancy, head of the chemical and biomolecular engineering department at Johns Hopkins University gave a plenary talk on “Merging Physical Science and Machine Learning to Tackle Complexity and Combinatorics in Materials Processing.”
“Attendees were impressed with the beauty of Lehigh’s campus, the spectacular setting for the conference, the list of speakers, and the diversity and range of topics,” says Mayuresh V. Kothare, chair of the Department of Chemical and Biomolecular Engineering. “It’s an example of how I-DISC is promoting new knowledge by creating new networks of professionals in these complex domains.”
The second workshop in the series, scheduled for early Fall 2019, will focus on machine learning topics related to robotics, automated control, and dynamical systems.
Read the full story in the Lehigh University News Center.
