Daisy Fan is a teaching professor of computer science who teaches in the areas of programming, scientific computing, and optimization. Fan's interests include collaborative learning methodologies and technologies in computer science and engineering education, application of systems-analysis techniques for water resources and environmental problems, and development of numerically efficient optimization methods for engineering applications. Problems she has investigated include optimal control of multiple-reservoir operation using stochastic dynamic programming and river basin water quality management.

Kuan Fang is an assistant professor of computer science who conducts research at the intersection of robotics, machine learning, and computer vision. His research aims to enable robots to perform diverse and complex tasks in unstructured environments using deep learning. To achieve this, his lab develops scalable algorithms and systems for robot perception and control with the following focuses: acquiring versatile and generalizable skills for visuomotor control by learning from massive and diverse data; continuously improving the capabilities of robots through autonomous data collection and generation; and boosting generalization to novel tasks, environments, and robots by integrating prior knowledge from broad sources. Fang did his postdoctoral research at the University of California, Berkeley and received his Ph.D. and M.S. from Stanford University. His bachelor's degree is from Tsinghua University. Fang also spent time at the RAI Institute, Google Brain, Google X Robotics, and Microsoft Research Asia.