ASSET Seminar: “Bridging the Gap Between Learning and Programming”
September 4 at 12:00 PM - 1:15 PM
Abstract:
For decades, we have built software by writing code, but in recent years machine learning has emerged as a new approach to create software with features that would be impossible to code by hand. However, the use of learning to build software risks ignoring some of the lessons we have learned for how to build computer systems that are robust and maintainable. In this talk, I will describe a new class of techniques we have developed under the term “neurosymbolic programming” which aim to support learning while maintaining some of the benefits of traditional programming, such as modularity, interpretability, reusability and incremental development, and will show some of the benefits these techniques can offer in domains ranging from robotics to computational biology.
Zoom Link (if unable to attend in-person): https://upenn.zoom.us/j/93017587225
Armando Solar-Lezama
Distinguished Professor of Computing at the MIT Schwarzman College of Computing
Armando Solar-Lezama is a Distinguished Professor of Computing at the MIT Schwarzman College of Computing and Associate Director and COO of the Computer Science and Artificial Intelligence Lab at MIT (CSAIL). Prof. Solar-Lezama is best known for his pioneering work on program synthesis. More recently, his work focuses on the intersection of machine learning and programming technology, with a special focus on leveraging ideas from programming systems to improve learning. He currently leads the NSF Expeditions project “Understanding the World Through Code” which aims to develop neurosymbolic learning techniques to support scientific discovery. Prof. Solar-Lezama is the recepient of the 2024 Robin Milner Young Researcher Award from ACM SIGPLAN.