Ayberk OzkirliExpertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Expertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Jean-Marc OdobezEnseignement et PhD Doctorant·es actuel·les Vivek Samir Gupte, Yesmine Abdennadher, Samy Tafasca, Shalutha Navindu Rajapakshe Rajapakshe Mudiyanselage, Gökhan Özbulak, Karl El Hajal, Hasindri Sankalpana Watawana, Mingchi Hou, Pierre François Marie Vuillecard, João Pedro Gandarela de Souza, Anirban Mukherjee, Elija Maria Vida, Nawal Haidar, Mojtaba Nafez A dirigé les thèses EPFL de Jagannadan Varadarajan, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Do Hoang Nam Le, Christian Jaques, Yu Yu,
Amir Roshan ZamirAmir Zamir is a Tenure-Track Assistant Professor of Computer Science at the Swiss Federal Institute of Technology in Lausanne (EPFL). Prior to EPFL, he spent time at Stanford, UC Berkeley, and UCF. His research interests are broadly in computer vision, machine learning, perception-for-robotics, and AI. He has been recognized with CVPR (2018) Best Paper Award, CVPR (2016) Best Student Paper Award, CVPR (2020) Best Paper Award Nomination, and NVIDIA Pioneering Research Award (2018), among others. His research has been covered by various press outlets, such as The New York Times or Forbes.
Francesca RodinoExpertise
Electrochemical BiosensorsSensors and Biosensors interfaces | front-end electronicsBiomedical circuits and systems
RechercheOther Tavakolidakhrabadi, A., Domange, T., Nalm, C., Rodino, F., Meimandi, A., Bessire, C., & Carrara, S. (2024). A Novel Microfluidic System for Capacitive Detection via Magnetophoretic Separation of Malaria-Infected Red Blood Cells. IEEE Sensors Letters. DOI: 10.1109/LSENS.2024.3451238Barbruni, G. L., Rodino, F., Ros, P. M., Demarchi, D., Ghezzi, D., & Carrara, S. (2024). A
Martin SchrimpfExpertise
NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]
Mission
Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to
Andrea CavallaroExpertise
Machine learning for multimodal perception, computer vision, machine listening, and information privacy.
Enseignement et PhD Doctorant·es actuel·les Yung-Chen Tang, Ante Maric, Cen Lu, Haruki Shirakami, Lei Xu, Dina El Zein, Jose Rafael Espinosa Mena, Shashi Kumar, Martin Schonger, Olena Hrynenko, Darya Baranouskaya Cours Deep learning EE-559 Ce cours explore la conception de réseaux de neurones discriminatifs et génératifs fiables, ainsi que les enjeux éthiques de l'acquisition
Touradj EbrahimiTouradj EBRAHIMI received his M.Sc. and Ph.D., both in Electrical Engineering, from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1989 and 1992 respectively. In 1993, he was a research engineer at the Corporate Research Laboratories of Sony Corporation in Tokyo, where he conducted research on advanced video compression techniques for storage applications. In 1994, he served as a research consultant at AT&T Bell Laboratories working on very low bitrate video coding. He is currently Professor at EPFL heading its Multimedia Signal Processing Group. He is also the Convenor of JPEG standardization Committee. He was also adjunct Professor with the Center of Quantifiable Quality of Service at Norwegian University of Science and Technology (NTNU)between 2008 and 2012.
Prof. Ebrahimi has been the recipient of various distinctions and awards, such as the IEEE and Swiss national ASE award, the SNF-PROFILE grant for advanced researchers, Four ISO-Certificates for key contributions to MPEG-4 and JPEG 2000, and the best paper award of IEEE Trans. on Consumer Electronics . He became a Fellow of the international society for optical engineering (SPIE) in 2003. Prof. Ebrahimi has initiated more than two dozen National, European and International cooperation projects with leading companies and research institutes around the world. He is a co-founder of Genista SA, a high-tech start-up company in the field of multimedia quality metrics. In 2002, he founded Emitall SA, start-up active in the area of media security and surveillance. In 2005, he founded EMITALL Surveillance SA, a start-up active in the field of privacy and protection. He is or has been associate Editor with various IEEE, SPIE, and EURASIP journals, such as IEEE Signal Processing Magazine, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, EURASIP Image Communication Journal, EURASIP Journal of Applied Signal Processing, SPIE Optical Engineering Magazine. Prof. Ebrahimi is a member of Scientific Advisory Board of various start-up and established companies in the general field of Information Technology. He has served as Scientific Expert and Evaluator for Research Funding Agencies such as those of European Commission, The Greek Ministry of Development, The Austrian National Foundation for Scientific Research, The Portuguese Science Foundation, as well as a number of Venture Capital Companies active in the field of Information Technologies and Communication Systems. His research interests include still, moving, and 3D image processing and coding, visual information security (rights protection, watermarking, authentication, data integrity, steganography), new media, and human computer interfaces (smart vision, brain computer interface).
He is the author or the co-author of more than 200 research publications, and holds 14 patents. Prof. Ebrahimi is a member of IEEE, SPIE, ACM and IS&T.
See the URL below for more details:
http://mmspl.epfl.ch 