Shashwat ShrivastavaI am a Ph.D. student at EPFL, advised by Dr. Mirjana Stojilović. I am broadly interested in FPGA architecture and Computer-Aided Design. My research is focused on reducing the compile time for FPGAs by incorporating architectural enhancements and rethinking CAD algorithms.
Thomas Emile BourgeatEnseignement et PhD Doctorant·es actuel·les Neelu Shivprakash Kalani, Jiawei Lin, Alexandre Pinazza, Jiacheng Ma, Martina Camaioni, Guokai Chen, Mohammadarman Soleimani Cours Computer security and privacy COM-301 C'est un cours d'introduction à la sécurité informatique et privée. L'objectif est de fournir aux étudiants les moyens de raisonner sur les problèmes de sécurité et de confidentialité et de leur donner les moyens de les affronter. Constructive Computer Architecture CS-62
Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Pasquale Davide SchiavoneEnseignement et PhD Cours Design technologies for integrated systems CS-472 La synthèse hardware est le processus de transformation - itérativement raffiné, détaillé et optimisé - d'une représentation faite en langage de description matérielle en un circuit. Ce cours présente les algorithmes, outils et méthodes de la compilation matérielle et de la synthèse logique.
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
Alireza MafiExpertise
Théorie de l'électromagnétismeAntennes et Micro-ondesCircuits Intégrés de RadiofréquenceRéseaux PhasésBioélectronique
Expertise
Théorie de l'électromagnétismeAntennes et Micro-ondesCircuits Intégrés de RadiofréquenceRéseaux PhasésBioélectronique
Je suis doctorant en Génie électrique à l'école Polytechnique Fédérale de Lausanne (EPFL). J'ai obtenu mon Master en Génie électrique (Communications Micro-ondes et Optiques) à l'Université de Technologie de Sharif, Téhéran, Iran, en 2022. J'ai également t
Benjamin Alexander Kellenberger2020–: Postdoctoral Researcher, EPFL, Sion, Switzerland2020: Postdoctoral researcher, Wageningen University, Netherlands2017–2020: PhD (cont'd); Wageningen University, Netherlands2016–2017: PhD; University of Zurich, Switzerland2009–2014: BSc. and MSc. in geography (remote sensing and GIS) and computer science; University of Zurich, Switzerland
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
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
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