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Xiao-Hua (Helen) Yu

Xiao-Hua (Helen) Yu

Professor Xiao-Hua (Helen) Yu

Phone: 805-756-2441
Office: 20A-311

Spring 2024 Schedule

Time Monday Tuesday Wednesday Thursday Friday
8:10-8:30 AM  




8:40-9:00 AM          
9:10-9:30 AM






9:40-10:00 AM          
10:10-10:30 AM          
10:40-11:00 AM          
11:10-11:30 AM          
11:40 AM-12:00 PM          
12:10-12:30 PM  

EE 509-01



EE 509-01


12:40-1:00 PM      
1:10-1:30 PM      
1:40-2:00 PM      
2:10-2:30 PM   Office Hour   Office Hour


EE 563-01


2:40-3:00 PM    
3:10-3:30 PM





3:40-4:00 PM        
4:10-4:30 PM

EE 514-01



EE 514-01


4:40-5:00 PM      
5:10-5:30 PM      
5:40-6:00 PM      
6:10-6:30 PM Office Hour


Office Hour    
6:40-7:00 PM          
7:10-7:30 PM          
7:40-8:00 PM          
8:10-8:30 PM          
8:40-9:00 PM          
9:10-9:30 PM          
9:40-10:00 PM          

Teaching and Research Interests

  • Artificial Intelligence
  • Digital Signal Processing
  • Adaptive Control


Current Research Interest

  • Inspired by biology and the study on human behavior, computational intelligent systems refer to a class of “sophisticated” systems which can solve problems that normally require the intelligence of a human being. Beyond traditional methods, the computational intelligence based approach has some valuable characteristics, such as the adaptive learning, distributed association, nonlinear mapping, as well as fault tolerance. It has found many applications in system identification, adaptive control, signal processing, optimization, etc.
  • Computational intelligence, by its nature, is a research field for multidisciplinary studies. I am looking for graduate students from all engineering disciplines (especially Electrical, Computer, Biomedical, and Mechnical Engineering), and Mathematics. Students with strong programming skills and mathematical background are preferred.
  • Some potential projects include computational intelligence applications in medical diagnosis, power network, traffic signal control, smart sensor network for civil infrastructures, robotics, etc.

Previous Projects

  • Rotorcraft Acoustic Data Modeling and Analysis with Wind Tunnel Test Data from NASA Ames Research Center
  • Neural Network Controller for DC Power Supply
  • A Neural Network Receiver for EM-MWD Baseband Communication Systems
  • Electrocardiogram (ECG) Signal Modeling and Noise Reduction Using Wavelet Neural Networks
  • Parameter Optimization using Genetic Algorithm
  • Neural Network Pruning Algorithm Development
  • Traffic Signal Control with Swarm Intelligence
  • Ant Colony Optimization Algorithm for Robot Path Planning
  • Bioinformatics Data Mining Using Artificial Immune Systems and Neural Networks

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