The Age of Disruption:  Challenges and Opportunities in Computer Science Education and Research

Abstract:  The history of civilization is punctuated by great and small disruptions. Some have even led to revolutions. Whether we realize it or not, the pace of the disruptions of our age is increasing rapidly. Consider these examples just from molecular biology alone. John Kendrew’s famous sentences in the 60s  “The way in which the chain of amino acid units in a protein molecule is coiled and folded in space has been worked out for the first time. The protein is myoglobin, the molecule of which contains 2,600 atoms.” instigated decades of computational studies on macromolecular structure, dynamics, and function, starting with the seminal work of Scheraga, Karplus, Levitt, Warshel, and others. Some of the most interesting computational concepts and techniques were debuted in these studies, many of which we would now categorize as “artificial intelligence” (AI). In the 70s, Anfinsen showed us that protein tertiary structure was largely encoded in the amino-acid sequence, which fascinated folks like me and single-handedly turned the focus of much research in my laboratory towards structure determination. In December 2020, Google’s DeepMind largely shut down this line of research, as their AlphaFold2 was shown to have solved what we could not do for forty years. 

This particular anecdote aside, whether we realize it or not, we are at an important crossroads in the history of higher education. The pandemic has exposed weaknesses and tensions that we knew existed but could afford to ignore or downplay for a while longer. The pervasiveness of online education has now brought to the forefront the question of what a brick-and-mortars academic organization offers to students. The online training and workforce development programs, customized to diverse student backgrounds, such as those pioneered by Amazon, are confronting us to a new and rather slick game in town. The research breakthroughs by companies, such as Google, which can afford to invest millions of dollars in research and development with none of the usual demands of rapid turnarounds that used to characterize R&D, are sending even more jolts to our collective identity. An important question confronts us: What do we offer in this shifting landscape?   I believe that the challenges we face present great opportunities if we take the time to outline our principles and be driven by them. We are increasingly living in an algorithmically-mediated world, so the responsibility to train our citizens of diverse backgrounds, ethnicities, and identities, prepare them for active participation in this new world, to be productive, gain and contribute meaning and value, and do so while preserving their dignity, falls to us. In this talk, I will share with you some of my experiences and vision to answer this call.

Bio: Dr. Amarda Shehu is a Professor in the Department of Computer Science in the Volgenau School of Engineering with affiliated appointments in the Department of Bioengineering and School of Systems Biology at George Mason University. She is also Founder and 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. in Computer Science from Rice University in 2008, where she was also an NIH predoctoral fellow. Shehu's research focuses on novel algorithms in artificial intelligence and machine learning to bridge between computer and information sciences, engineering, and the life sciences. In particular, the Shehu laboratory designs unifying computational frameworks that build over problem solving, search, optimization, planning, and machine learning to fully characterize and simulate complex dynamic systems operating in the presence of constraints.  This research has resulted in many AI-driven scientific discoveries in close collaboration with domain scientists, including civil engineers, social scientists, molecular biologists, cancer biologists, neuroscientists, and others. Algorithms developed in the Shehu laboratory constitute a computational microscope into the inner workings of the healthy and diseased cell, and Shehu has made many contributions in computational molecular biology and bioinformatics in characterizing the relationship between macromolecular sequence, structure, dynamics, and (dys)function over disparate spatio-temporal scales. Shehu has published over 140 technical papers with postdoctoral, graduate, undergraduate, and high-school students. She is the recipient of an NSF CAREER Award, and her research is regularly supported by various NSF programs, as well as state and private research awards. Shehu is also the recipient of the 2018 Mason University Teaching Excellence Award, the 2014 Mason Emerging Researcher/Scholar/Creator Award, and the 2013 Mason OSCAR Undergraduate Mentor Excellence Award. She is an Associate Editor of various journals and Chair of the ACM/IEEE Trans Bioinf and Comp Biol (TCBB) Steering Committee. Shehu currently serves as Program Director at the National Science Foundation in the Information and Intelligent Systems Division of the Computer and Information Science and Engineering Directorate.