AI/ML-Driven Scientific Advances: A Personal Journey, Lessons, and Outlook
Human thought and scientific enquiry have undergone various stages of evolution, from Greek idealism, classical scientific, modern pre-digital scientific, and all the way to the modern digital, data-centric era in which we are now living. Our day-to-day reality, scientific disruptions, and revolutions are now almost entirely defined, shaped, and guided by the data. One can make a strong case that biology was one of the early sciences reshaped by the amount of the data collected by throughput technologies, spewing off entire new sub-disciplines, such as computational biology and bioinformatics, and undergoing minor and large disruptions at a rapidly increasing pace. My own AI research bears witness to such an evolution, both in the questions we can now ask and answer, and the methodologies with which we can suddenly unravel complex problems. I will give a rapid view of this evolution through a highly personal lens on bioinformatics. The end of the talk will provide diverse examples of scientific advances at the intersection of AI/ML and the material sciences, social sciences, civil engineering, urban planning, and more. The talk will conclude with some lessons learned and wishes for the process of scientific discovery and the education of the next generation of scientists.
Date and Time
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- Date: 15 Mar 2022
- Time: 07:00 PM to 08:00 PM
- All times are (GMT-05:00) US/Eastern
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- Co-sponsored by Northern Virginia/Washington Computational Intelligence Society
- Starts 15 February 2022 06:54 PM
- Ends 15 March 2022 12:01 PM
- All times are (GMT-05:00) US/Eastern
- No Admission Charge
Speakers
Dr. Amarda Shehu of George Mason University/Center for Advancing Human-Machine Partnerships
Biography:
Dr. Amarda Shehu is a Professor in the Department of Computer Science in the College of Engineering and Computing with affiliated appointments in the Department of Bioengineering and School of Systems Biology at George Mason University. She is also Co-Director of the Center for Advancing Human-Machine Partnerships (CAHMP), a Transdisciplinary Center for Advanced Study at George Mason University. Shehu obtained her Ph.D. from Rice University in 2008, where she was an NIH predoctoral fellow in the Nanobiology Program and was dually trained in AI and Molecular Biophysics. Shehu's research is at the intersection of AI/ML and scientific enquiry. Shehu has published over 150 technical papers with postdoctoral, graduate, undergraduate, and high-school students. She is a 2022 Fellow of the American Institute for Medical and Biological Engineering (AIMBE) and has received several awards, including the 2022 Outstanding Faculty Award from the State Council of Higher Education for Virginia, the 2021 Beck Family Presidential Medal for Faculty Excellence in Research and Scholarship, the 2018 Mason University Teaching Excellence Award, the 2014 Mason Emerging Researcher/Scholar/Creator Award, the 2013 Mason OSCAR Undergraduate Mentor Excellence Award, and the 2012 National Science Foundation (NSF) CAREER Award. Her research is regularly supported by various programs at the NSF and the Department of Defense, as well as state and private research entities. Shehu currently serves as an NSF Program Director in the Information and Intelligent Systems Division of the Computer and Information Science and Engineering Directorate.
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| AI/ML-Driven Scientific Advances | Slides from Dr. Amarda Shehu's talk "AI/ML-Driven Scientific Advances: A Personal Journey, Lessons, and Outlook" | 8.08 MiB |