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 research focuses on advancing computational sensing and imaging through the development of innovative algorithms and mathematical frameworks. I am particularly interested in contemporary topics at the intersection of machine learning, signal processing, and computational mathematics, such as inverse problems, graph representation learning, domain adaptation, physics-informed learning, and optimization. These methods are applied to diverse applications, including low-level vision (image restoration, image fusion, image compression, etc.), Industrial Internet of Things, remote sensing and Earth observation, intelligent infrastructures, and smart cities. My research emphasizes two key aspects: 1) exploring the fundamental mathematical principles of sensing and metrology, and 2) pursuing application-driven projects through collaborations with experts from various disciplines such as electrical engineering, computer science, civil and environmental engineering, applied mathematics, mechanical engineering, and physics.

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. 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 multimodal biomedical signals.

Featured Publications

	Physics-Enhanced Graph Neural Networks for Soft Sensing in Industrial Internet of Things Keivan Faghih Niresi, Hugo Bissig, Henri Baumann, and Olga Fink IEEE Internet of Things Journal, 2024 IEEE Xplore | PDF | Code
	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