Xingyu Li, PhD

Assistant Professor, Faculty of Engineering - Electrical & Computer Engineering Dept

Contact

Assistant Professor, Faculty of Engineering - Electrical & Computer Engineering Dept
Email
xingyu@ualberta.ca
Phone
(780) 492-8571
Address
11-209 Donadeo Innovation Centre For Engineering
9211-116 St
Edmonton AB
T6G 2H5

Overview

Area of Study / Keywords

Artificial intelligence Computational medical imaging Weak supervision Deep model compression Computer vision


About

Xingyu Li is an assistant professor with the Department of Electrical and Computer Engineering at the University of Alberta. She received the B.Sc degree in Electrical Engineering from Peking University in 2007, the M.Sc degree from the University of Alberta in 2009, and Ph.D from the University of Toronto in 2017, both in Electrical and Computer Engineering. Before joining the ECE department, Xingyu was a postdoctoral fellow at the University of Toronto and a postgraduate affiliation of the Vector Institute for Artificial Intelligence. Besides academia, Xingyu also worked in industry as a video algorithm engineer for 2+ years.


Research

Xingyu's research interests include artificial intelligence, computational medical imaging, weak supervision, deep model compression, and color visual signal processing. A general theme is intelligent computational systems for (i) multi-dimensional data analytics and understanding, (ii) computer vision, and (iii) health informatics. Her research outcomes have been applied to biologists' state-of-the-art study on pathology image based breast cancer prognosis.

Xingyu's current research projects include:

  • Computational medical imaging (e.g trusted diagnostic systems, deep pathological diagnosis, etc)
  • Learning-based visual data analysis and quality improvement
  • Deep model compression for edge devices


Announcements

I am looking for self-motivated students (undergraduate, M.Sc, or Ph.D) and postdocs to work with me. If interested, please contact me with your CV, transcripts, and a brief description of your research interest (a specific topic is a bonus!). Thesis and sample publications are highly welcomed.

I also plan to host visiting scholars who share common research interests with me. 


Courses

ECE 380 - Introduction to Communication Systems

Basics of analog communication: amplitude, angle, and analog pulse modulation; modulators and demodulators; frequency multiplexing. Basics of digital communication: sampling, quantization, pulse code modulation, time division multiplexing, binary signal formats. Prerequisite: ECE 240 or E E 238. Credit may be obtained in only one of ECE 380 or E E 390.

Winter Term 2021
ECE 740 - Advanced Topics in Signal and Image Processing

Fall Term 2020

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