About me

I am a PhD student at École Polytechnique Fédérale de Lausanne (EPFL). I joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.

My current research interests lie primarily in geometric deep learning, signal processing, and inverse problems, with application to network science, energy systems, and intelligent infrastructure.

Prior to joining EPFL, I obtained my master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua University (NTHU) where I conducted research in convex and non-convex optimization, statistical signal processing, deep learning, and hyperspectral imaging under the supervision of Prof. Chong-Yung Chi (IEEE Fellow). I also had the opportunity to work as a machine learning engineer intern at PranaQ, where I focused on developing signal processing and feature extraction algorithms for biomedical signals such as photoplethysmogram (PPG) and electrocardiogram (ECG).

Featured Publications

	Robust Hyperspectral Inpainting via Low-Rank Regularized Untrained Convolutional Neural Network Keivan Faghih Niresi, and Chong-Yung Chi IEEE Geoscience and Remote Sensing Letters, 2023 IEEE Xplore | PDF | Code
	Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution Keivan Faghih Niresi, and Chong-Yung Chi IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 IEEE Xplore | PDF | Code | Open Remote Sensing