Event details
Mar
7
AI Lab Distinguished Lecture Series- Eric Xing
Distinguished Lecturer Series: “Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels”
Eric Xing, president of Mohamed bin Zayed University of AI
Details
Eric Xing
Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels: At the core of medicine, pharmacy, public health, longevity, agriculture, and environment, is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamper with. In this talk, I present a vision of using AI to model and simulate biology and life. I will layout an engineering viable approach to construct an AI-Driven Digital Organism (AIDO), leveraging self-supervised pretraining and adaption of large-scale foundation models, and I introduce some early results including 5 SOTA foundation models for DNA, RNA, Protein, Structure, and Single Cell, respectively, and their abilities to tackle biological problems at the full spectrum of granularities, from sequence, to structure, to network, to phenotype, to diseases, and to drug responses. We envision that AIDO opens up a safe, affordable and high-throughput alternative platform for predicting, simulating and programming biology at all levels from molecules to cells to individuals, and is poised to trigger a new wave of better-guided wet-lab experimentation and better-informed first-principle reasoning, which can eventually help us better decode and improve life.
Professor Eric P. Xing is the President of the Mohamed bin Zayed University of Artificial Intelligence, Professor of Computer Science at Carnegie Mellon University, and Co Founder & Chief Scientist at GenBio AI. His main research interests are the development of machine learning and statistical methodology, and large-scale computational system and architectures, for solving problems involving automated learning, reasoning, and decision-making in artificial, biological, and social systems. Prof. Xing has served on the editorial boards of leading scientific journals including the Journal of the American Statistical Association, Annals of Applied Statistics, PLOS Journal of Computational Biology, IEEE Journal of Pattern Analysis and Machine Intelligence, Machine Learning Journal, and and Journal of Machine Learning Research. He was elected Fellows AAAI, ACM, ASA, IEEE, and IMS.
RSVP here: https://docs.google.com/forms/d/e/1FAIpQLScAuQM_UOPkXY0psLTfHmth8XQSUJCexw4hVI-eza_3opNY5w/viewform
Eric Xing, president of Mohamed bin Zayed University of AI
Details
Eric Xing
Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels: At the core of medicine, pharmacy, public health, longevity, agriculture, and environment, is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamper with. In this talk, I present a vision of using AI to model and simulate biology and life. I will layout an engineering viable approach to construct an AI-Driven Digital Organism (AIDO), leveraging self-supervised pretraining and adaption of large-scale foundation models, and I introduce some early results including 5 SOTA foundation models for DNA, RNA, Protein, Structure, and Single Cell, respectively, and their abilities to tackle biological problems at the full spectrum of granularities, from sequence, to structure, to network, to phenotype, to diseases, and to drug responses. We envision that AIDO opens up a safe, affordable and high-throughput alternative platform for predicting, simulating and programming biology at all levels from molecules to cells to individuals, and is poised to trigger a new wave of better-guided wet-lab experimentation and better-informed first-principle reasoning, which can eventually help us better decode and improve life.
Professor Eric P. Xing is the President of the Mohamed bin Zayed University of Artificial Intelligence, Professor of Computer Science at Carnegie Mellon University, and Co Founder & Chief Scientist at GenBio AI. His main research interests are the development of machine learning and statistical methodology, and large-scale computational system and architectures, for solving problems involving automated learning, reasoning, and decision-making in artificial, biological, and social systems. Prof. Xing has served on the editorial boards of leading scientific journals including the Journal of the American Statistical Association, Annals of Applied Statistics, PLOS Journal of Computational Biology, IEEE Journal of Pattern Analysis and Machine Intelligence, Machine Learning Journal, and and Journal of Machine Learning Research. He was elected Fellows AAAI, ACM, ASA, IEEE, and IMS.
RSVP here: https://docs.google.com/forms/d/e/1FAIpQLScAuQM_UOPkXY0psLTfHmth8XQSUJCexw4hVI-eza_3opNY5w/viewform
Speakers
Eric Xing
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