| Session
|
Applications
|
| Duration
|
1 hour
|
| Date/Time
|
24 Apr 2024 16:00 GMT
|
| 9:00am PDT/12:00pm EDT
|
| 4:00pm GMT/6:00pm CEST
|
| Convener
|
Ram D. Sriram
|
Agenda
- 12:00-12:05 Ram D. Sriram Healthcare Applications Panel
- 12:05-12:35 Venkat Venkatasubramanian Ontology-based Machine Learning in Pharmaceutical Engineering
- Abstract: The startling success of ChatGPT and transformer-based generative neural networks in applications such as natural language processing and image synthesis has many researchers excited about the potential opportunities in pharmaceutical engineering. However, there is an essential difference between such applications and pharmaceutical engineering. The latter is governed by fundamental laws of physics, chemistry, and biology, constitutive relations, and highly technical knowledge about materials, processes, and systems. While purely data-driven machine learning has its immediate uses, the long-term success of AI here would depend on leveraging first principles and technical knowledge effectively using ontologies. In this talk, I will discuss these challenges and opportunities going forward.
- Bio: Professor Venkat Venkatasubramanian is Samuel Ruben-Peter G. Viele Professor of Engineering in the Department of Chemical Engineering, Professor of Computer Science (Affiliate), and Professor of Industrial Engineering and Operations Research (Affiliate) at Columbia University. He earned his Ph.D. in Chemical Engineering at Cornell, M.S. in Physics at Vanderbilt, and B.Tech. in Chemical Engineering at the University of Madras, India. He taught at Purdue University for many years before returning to Columbia in 2011.
- Venkat is a complex-dynamical-systems theorist interested in developing mathematical models of their structure, function, and behavior from fundamental conceptual principles. He considers himself an artist in science whose natural tendency is to conduct curiosity-driven research in a style that might be considered impressionistic, emphasizing conceptual issues over mere techniques. He strives to create a simplified but essentially correct model of the reality that he studies. Venkat's research interests are diverse, ranging from AI to systems engineering to theoretical physics to economics, but they are centered around the theme of understanding complexity and emergent behavior in different domains.
- Venkat received the Norris Shreve Award for Outstanding Teaching in Chemical Engineering three times at Purdue University. He won the Computing in Chemical Engineering Award from AIChE and is a Fellow of AIChE. In 2011, the College of Engineering at Purdue University recognized his contributions with the Research Excellence Award. He is a past president of the CACHE Corporation. From 2009-19, he served as Editor for Computers and Chemical Engineering. His book, How Much Inequality is Fair? Mathematical Principles of a Moral, Optimal, and Stable Capitalist Society, was published in 2017. Three of his papers are among the ten most-cited papers in the 46-year history of Computers & Chemical Engineering. Venkat's other interests include comparative theology, classical music, and cricket.
- Slides
- 12:35-13:00 Kaushik Roy Healthcare Assistance Challenges-Driven Neurosymbolic AI
- Topic and Brief Bio: Kaushik Roy is a fourth-year Doctoral student at the AI Institute at the University of South Carolina. His research interests include developing algorithms to combine statistical data-driven learning mechanisms with curated domain-specific information from external knowledge sources, focusing on social good applications. He has published several papers and delivered talks at premier venues on his work on AI for mental health assessment assistance, and other social good applications.
- Slides
Conference Call Information
- Date: Wednesday, 24 April 2024
- Start Time: 9:00am PDT / 12:00pm EDT / 6:00pm CEST / 5:00pm BST / 1600 UTC
- Expected Call Duration: 1 hour
The unabbreviated URL is:
https://us02web.zoom.us/j/87630453240?pwd=YVYvZHRpelVqSkM5QlJ4aGJrbmZzQT09
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