Lizhe Tan

Lizhe Tan serves as Professor and Department Chair of Electrical and Computer Engineering at Purdue University Northwest. With prior academic roles at Purdue University North Central (now PNW) and DeVry University, his expertise spans digital signal processing, control systems, robotics, and machine learning applications in real-world engineering solutions.

His educational background includes:

• Ph.D. in Electrical Engineering, The University of New Mexico
• M.S. in Electrical Engineering, The University of New Mexico

Professor Tan's research integrates mathematical rigor with practical innovation, focusing on fractional-order control systems, active noise control, and computer vision for robotics. His work bridges theoretical signal processing with machine learning applications, resulting in over 100 publications, a granted US patent, and four textbooks including the 2025 fourth edition of Digital Signal Processing: Fundamentals, Applications and Deep Learning.

Recent publications reveal a strong trajectory toward machine learning integration in traditional engineering domains, with 2020-2024 works addressing bearing fault diagnosis via sparse wavelet CNNs, fractional-order PID control improvements, and acoustic echo cancellation using sparsity-aware filters. His 2025 textbook formalizes the deep learning/signal processing convergence.

Professor Tan actively mentors students through senior design projects and Master's thesis research, emphasizing hands-on application of signal processing and control theory principles in robotics and measurement systems.