Sofia Charlotta OlhedeSofia Olhede is a professor of Statistics at EPFL in Switzerland. She joined UCL prior to this in 2007, before which she was a senior lecturer of statistics (associate professor) at Imperial College London (2006-2007), a lecturer of statistics (assistant professor) (2002-2006), where she also completed her PhD in 2003 and MSci in 2000. She has held three research fellowships while at UCL: UK Engineering and Physical Sciences Springboard fellowship as well as a five-year Leadership fellowship, and now holds a European Research Council Consolidator fellowship. Sofia has contributed to the study of stochastic processes; time series, random fields and networks. Sofia was part of the multi-institutional team that set up the UK national data science institute, the Alan Turing Institute. She organised and served as chair of the science committee that developed the initial 500 000 pounds scientific programme of the institute; peer-reviewing over 100 workshop proposals and hosting over 30. She also chaired the first recruitment wave of the institute hiring 13 data scientists as a multi-university recruitment drive. Sofia was a member of the Royal Society and British Academy Data Governance Working Group, and the Royal Society working group on machine learning. Most recently she was one of 3 commissioners on a law society commission on the usage of algorithms in the justice system.
Ali MeimandiExpertise
Research interests:Analog and digital circuit designBiomedical circuits and systems
Ali Meimandi received B.Sc degree in electrical engineering from Amirkabir University of Technology(Tehran Polytechnic), Tehran, Iran, and M.Sc. degree in electronic engineering from Politecnico di Milano, Milan, Italy, in 2018 and 2022, respectively. He is a Research Assistant and doctoral candidate in the BioCMOS Interfaces(BCI) Laboratory at école Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.His res
Vittorio ErbaEnseignement et PhD Cours Statistical physics of computation PHYS-512 Les étudiants comprennent les outils de la physique statistique des systèmes désordonnés et les appliquent pour étudier des problèmes d'informatique et de statistiques en théorie des graphes, en optimisation discrète, ainsi qu'en inférence et en apprentissage automatique.
Andres Osorio SalazarExpertise
Robotics, advanced actuator design, soft actuators, sensor design, embedded systems, human-machine interface architecture, electronic-less control, mechanism design, additive and traditional manufacturing, industrial automation, process control, and fluid robotics.
Current Work
Smart Footwear for Diabetic Foot Care and Ulcer PreventionEvery 20 seconds, a person with diabetes has to face an amputation somewhere in the world. The main risk factor is high plantar pressure combined with foot nephropat
Yujia ZhangEnseignement et PhD Doctorant·es actuel·les Yuyan Su, Shulang Shen, Jiaqi Liu Cours Advanced microfabrication practicals MICRO-373 Ce TP permet une formation approfondie sur les méthodes avancées de micro et nanofabrication dans un environnement de salle blanche pour des applications sélectionnées, d'acquérir des connaissances plus approfondies sur les processus MEMS/NEMS, de travailler dans un petit groupe avec des doctorants/ MOOC: Micro and Nanofabrication (MEMS) - Fall MICRO-
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
Lénaïc ChizatEnseignement et PhD Doctorant·es actuel·les Javier Esteban Maass Martinez A dirigé les thèses EPFL de Guillaume Yitian Wang Cours Computational optimal transport MATH-528 Aspects computationnels de la théorie du transport de mesures, du problème classique du transport optimal classique au modèles de diffusion modernes. Topics in machine learning MATH-520 Analyse mathématique des techniques modernes d'apprentissage supervisé, avec une emphase sur les réseaux de neurones arti
