Title:
Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation
Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation
| dc.contributor.author | Zhao, Huimin | |
| dc.contributor.corporatename | Georgia Institute of Technology. Institute for Data Engineering and Science | en_US |
| dc.contributor.corporatename | University of Illinois at Urbana-Champaign. Dept. of Chemical and Biomolecular Engineering | en_US |
| dc.date.accessioned | 2020-11-25T17:54:07Z | |
| dc.date.available | 2020-11-25T17:54:07Z | |
| dc.date.issued | 2020-11-13 | |
| dc.description | Presented online on November 13, 2020 at 2:00 p.m. | en_US |
| dc.description | Dr. Huimin Zhao is the Steven L. Miller Chair of chemical and biomolecular engineering, and professor of chemistry, biochemistry, biophysics, and bioengineering, and Director of NSF AI Research Institute for Molecule Synthesis at the University of Illinois at Urbana-Champaign (UIUC). Zhao's laboratory develops and applies synthetic biology, machine learning, and laboratory automation tools to engineer functionally improved or novel proteins, pathways, and genomes for biotechnological and biomedical applications. | en_US |
| dc.description | Runtime: 56:46 minutes | en_US |
| dc.description.abstract | Inspired by the exponential growth of the microelectronic industry, my lab has been attempting to build a biofoundry that integrates biology, automation and artificial intelligence (AI)/machine learning for rapid prototyping and manufacturing of biological systems for synthesis of bioproducts ranging from chemicals to materials to therapeutic agents. In this talk, I will discuss the challenges and opportunities at the nexus of synthetic biology, machine learning, and automation and highlight a few of our accomplishments and the recently launched NSF AI research institute for molecular synthesis. Specifically, I will introduce three interconnected stories, including: (1) development of the Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB) for next-generation synthetic biology applications; (2) development of genome-scale engineering tools for rapid metabolic engineering applications, and (3) integration of biocatalysis and chemical catalysis for synthesis of value-added chemicals, which necessitates the development of AI-enabled synthesis planning and catalyst design tools. | en_US |
| dc.format.extent | 56:46 minutes | |
| dc.identifier.uri | http://hdl.handle.net/1853/63944 | |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | IDEaS-AI Seminar Series | en_US |
| dc.subject | Artificial intelligence (AI) | en_US |
| dc.subject | Automation | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Synthetic biology | en_US |
| dc.title | Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation | en_US |
| dc.type | Moving Image | |
| dc.type.genre | Lecture | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | Institute for Data Engineering and Science | |
| local.relation.ispartofseries | IDEaS Seminar Series | |
| relation.isOrgUnitOfPublication | 2c237926-6861-4bfb-95dd-03ba605f1f3b | |
| relation.isSeriesOfPublication | 315185f2-d0ec-4ea2-8fdc-822ed04da3a8 |
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