Pierre Vandergheynst

Pierre Vandergheynst is a Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Electrical Engineering (EE) department. His research is associated with the Signal Processing Laboratory 2. He is involved in teaching courses such as Matrix Analysis (EE-312) and Signals and Systems II (for MT and SV) (MICRO-311). He also supervises PhD students and is a member of several academic committees at EPFL. His research interests include complex data processing, high-dimensional data processing, visual information processing, computational harmonic analysis, data compression, and computer vision. He has published in various journals and conferences, including IEEE Transactions on Signal Processing and Neuroimage.

Pierre Vandergheynst is a Professor of Electrical Engineering at Ecole Polytechnique Fédérale de Lausanne (EPFL). His research focuses on data science, machine learning, artificial intelligence, network science, and computer vision. He has contributed significantly to the development of signal processing techniques on graphs, including spectral graph theory and geometric deep learning. His work explores methods for analyzing irregular data structures, such as networks, and has applications in computer vision, biomedical engineering, and signal processing. Vandergheynst's research also includes advancements in compressed sensing, wavelet transforms, and graph signal processing, with a focus on real-time and energy-efficient algorithms.