Soft AE - Exploring Research and Educational Intersections of


Soft AE Kickoff group photo by Lamont Abrams

2023 Symposium Attendees (2023 program)

2024 Symposium
Thursday, May 2, 2024
10:00 AM - 3:15 PM

Glandt Forum
Singh Center for Nanotechnology
3205 Walnut Street, Philadelphia PA


Register here


nsf logo
Funded by NSF Award #2152205

10:00 am

Opening Remarks

Dawn Bonnell, PhD
Senior Vice Provost for Research, University of Pennsylvania

Chinedum Osuji, PhD
NRT Soft AE Director and PI

10:15 am

Greg Doerk portrait

Exploring Polymer Blend Directed Self-Assembly Using Autonomous X-Ray Scattering
Greg Doerk, PhD, Brookhaven National Lab

The directed self-assembly of block copolymer thin films is a promising approach for next-generation nanolithography and functional material synthesis. Polymer blending can augment the assembly process for enhanced scalability and performance, but each new additive expands compositional dimensionality and processing complexity. This talk will discuss our recent and ongoing work applying autonomous X-ray scattering methods, where machine learning guides measurements and experiments to compress experimental loops, to develop polymer blend assembly strategies for nanolithography. I will also present progress in developing a new platform combining automated spraying, in situ x-ray scattering and machine learning to direct nonequilibrium blend self-assembly.

11:00 am

Lightning Round: Soft AE Trainees

multiple photos of the NRT 3 Cohorts

11:45 am

Andrew Zahrt portrait

Machine-Learning-Guided Discovery of New Electrochemical Reactions
Andrew Zahrt, PhD, University of Pennsylvania

Reaction discovery in synthetic chemistry is typically a process driven by empiricism or serendipity. In this work, we use automation and machine learning to create a workflow for the computer-guided discovery of new synthetic electrochemical reactions.

12:30 am

Group Photo and Lunch

1:30 pm

Chris Callison-Burch portrait

Ask an Expert about ChatGPT
Chris Callison-Burch, PhD, University of Pennsylvania

Generative AI had its breakthrough moment in November 2022 with the release of OpenAI’s ChatGPT. Prof. Callison-Burch is an expert in artificial intelligence who has been in the field for 20 years, and has been using language models in his research for much of that time. He'll explain how large language models work, what their limitations are. In this interactive session, Prof. Callison-Burch will answer any questions that you have about LLMs, and discuss their potential application for scientific discovery in fields other than computer science.

2:15 pm

Gwen Ottinger portrait

Engineering’s Hardest Problem
Gwen Ottinger, PhD, Drexel University

Innovation reshapes our world. Because it’s impossible to know in advance the full range of an innovation’s consequences, one important ethical obligation of engineers and scientists is to respond when undesirable effects of their innovations emerge. But successful innovations quickly become infrastructure, and rolling back or changing course to mitigate deleterious consequences can seem unthinkable when large capital investments have been made. Ensuring the ability to respond to the emerging effects of innovation is thus an engineering problem, not just an ethical one. This talk suggests new directions in STEM research to develop engineers’ capacity for responsiveness.

3:00 pm

Closing Remarks

Russell Composto, PhD
NRT Soft AE Associate Director and co-PI

Kristin Field, PhD
NRT Soft AE Education Director, Program Coordinator and co-PI