Discovery and Characterization of Novel Feedback Control Mechanisms in Synthetic Gene Networks: From Principled Models to Deep Learning
Dr. Enoch Yeung has a B.S. in Mathematics from Brigham Young University, magnua cum laude with university honors and a Ph.D. in Control and Dynamical Systems from the California Institute of Technology. He has led many interdisciplinary research projects at the interface of synthetic biology and learning theory including the DARPA Synergistic Discovery & Design Program (currently serving as a performer and PI), DARPA Friend or Foe program (serving as co-PI), DARPA Living Foundries program, the 2018 High Performance Data Analytics Program, the NSF Molecular Programming Project, and the AFOSR Biological Research Initiative. He is an assistant professor in the Department of Mechanical Engineering at the University of California Santa Barbara. Previously, he served as senior research scientist in the Data Science and Analytics Group at Pacific Northwest National Laboratory and lead several internal research efforts in deep learning, network inference, and control of complex systems. His research interests center on learning algorithms for dynamical systems, control theory, synthetic and systems biology. He has served on several advisory panels for DARPA, NIST, the DoD SBME initiative, and the National Defense University. He is the recipient of Kanel Foundation Fellowship, the National Science Foundation Graduate Fellowship, a National Defense Science and Engineering Fellowship, the PNNL Project Team of the Year Award, and the PNNL Outstanding Performance Award.