Princeton University

School of Engineering & Applied Science

Dr. Zhuo Wang
Graduate Student
Graduation Year: 
2017
Thesis Title: 
Relaxing the Implementation of Embedded Sensing Systems through Machine Learning and Statistical Optimization
Advisor: 
Naveen Verma
Current Employer: 
IBM T. J. Watson Research Center
Current Department: 
Electrical Engineering

I am interested in machine learning algorithms and corresponding hardware system realizations in general. During my PhD, I have been working on applying statistical learning approaches to sensing systems, for achieving low-energy embedded systems that can provide high-value inferences from large amount of complex sensory data.

For achieving the above goal, I not only develop new algorithmic and architectural principles for the design of embedded machine learning systems, but also map these principles to building prototype systems in different technologies (FPGA, ASIC, LAE), and for various applications (bio-medical sensing, image recognition, etc).