Jaïr Kees Evert Karel CampfensJair Kees Evert Karel Campfens is a doctoral assistant at the HERUS lab. He is an engineer by Eindhoven University of Technology (TU/e) and holds a MSC in Sustainable Energy Technology. Moreover, he holds a double degree MSc in Public Policy & Human Development from Maastricht University and the United Nations University. Education Public Policy & Human Development | Master of Science 2021 – 2022 Maastricht University UNU-MERIT Sustainable Energy Technology | Master of Science
Mahmut Selman SakarEnseignement et PhD Doctorant·es actuel·les Lorenzo Francesco John Noseda, Nikita Norkin, Elif Ezgi Inan, Houman Javaheri, Mehdi Ali Gadiri, Julian Leon Raub, Junsun Hwang A dirigé les thèses EPFL de Erik Mailand, Raquel Filipa Penacho Parreira, Murat Kaynak, Lucio Pancaldi-Giubbini, Fazil Emre Uslu, Matthias Rüegg, Ece Özelçi, Emilie Vuille-Dit-Bille A co-dirigé les thèses EPFL de Laura Joan Hermans, Sourabh Monnappa Kuppanda Jafri Cours Dynamical systems ME-221 Introduction à la modélisa
Simon HolzerHi, I am Simon Holzer. I received my B.Sc. and M.Sc. degrees in mechanical engineering with a focus on microtechnology from the Swiss Federal Institute of Technology Zurich (ETHZ) in 2020 and 2022, respectively. I am currently working towards Ph.D. in the Integrated Actuators Laboratory (LAI) at EPFL in Neuchâtel, Switzerland. My research interests lie in the field of soft robotics, artificial muscles, and biomechanics.
Matteo FaveroExpertise
Dynamic thermal comfort, Indoor environmental quality, Occupant-centric modelling, Human-building interaction, Multi-domain environmental exposure, Building physics, Building performance simulation, Thermal flexibility, Climate-adaptive buildings, Multilevel modelling, Statistical thinking, Causal thinking, Simulated-data experimentation.
Matteo Favero is a Postdoctoral Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is currently a member of the Human-Oriented Bu
Martin JaggiMartin Jaggi is a Tenure Track Assistant Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before that, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at École Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich.
Mirko MusaEnseignement et PhD Doctorant·es actuel·les Louise Cayroche, Antonio Magherini Cours Hydraulic engineering and infrastructures CIVIL-312 L'eau est indispensable à la vie, mais c'est aussi une force naturelle puissante. L'ingénierie hydraulique vise une gestion durable de l'eau pour l'approvisionnement, l'énergie et la protection.
Stefana ParaschoEnseignement et PhD Doctorant·es actuel·les Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Cours Capitalizing on Uncertainty AR-809 Digital design and making: A critical introduction AR-503 Le cours présente des méthodes de conception et de fabrication numériques en combinant des compétences techniques avec des connaissances théoriques et une réflexion critique. Les sujets incluent: la programmation pour la conception, la fabr
Jakov OrebEnseignement et PhD Cours Stone masonry: Past, present, and future PENS-232 Ce cours présente les aspects historiques, structurels et environnementaux de la maçonnerie en pierre, en particulier le rôle de la maçonnerie en pierre dans l'architecture, le comportement structurel de base et les approches permettant de prédire et d'évaluer la performance des bâtiments.
Mathias Christian Haindl CarvalloEnseignement et PhD Cours Stone masonry: Past, present, and future PENS-232 Ce cours présente les aspects historiques, structurels et environnementaux de la maçonnerie en pierre, en particulier le rôle de la maçonnerie en pierre dans l'architecture, le comportement structurel de base et les approches permettant de prédire et d'évaluer la performance des bâtiments.
Sanggyu ChongSanggyu "Raymond" Chong obtained his BS, MS and PhD degrees in Chemical and Biomolecular Engineering from Korea Advanced Institute of Science and Technology (KAIST), where he primarily focused on the computational design of metal-organic frameworks for applications ranging from gas storage to functional electronics. In March 2022, Sanggyu joined COSMO as a postdoctoral researcher, and he is currently investigating the robustness of local and/or component-wise predictions made by atomistic machine learning m
