Introduction of the Principal Investigator
Shaowei received his Ph.D. in Mathematics in 2011 from the University of California, Berkeley, where he analyzed singularities in statistical models over large data sets through the lens of modern algebraic geometry. This work was continued at Stanford University in a one‐year DARPA postdoctoral collaboration with Andrew Ng to explore mathematical challenges in deep learning. In 2012, he returned to Singapore to start the Sense‐making Group in the Sense and Sense‐abilities programme in A*STAR. The group focused on exploiting deep learning techniques in sensor systems to enable intelligence at the edge of the network. In 2016, Shaowei joined SUTD where he crystallized his ideas for Distributed Artificial Intelligence. His research focuses on biologically plausible local learning rules for spiking neural networks based on path integrals in statistical physics, and on hierarchical geometric inference rules for scalable machine reasoning based on homotopy type theory. In 2017, he spent six months as a
visiting professor in Tomaso Poggio’s Center for Brains, Minds and Machines at MIT. Shaowei is currently an assistant professor in the Engineering Systems and Design pillar at SUTD.