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 SakarExpertise
robotics, mechanobiology, microtechnology, smart materials, biomedical devices
Teaching & PhD PhD Students Lorenzo Francesco John Noseda, Nikita Norkin, Elif Ezgi Inan, Houman Javaheri, Mehdi Ali Gadiri, Julian Leon Raub, Junsun Hwang Past EPFL PhD Students Erik Mailand, Raquel Filipa Penacho Parreira, Murat Kaynak, Lucio Pancaldi-Giubbini, Fazil Emre Uslu, Matthias Rüegg, Ece Özelçi, Emilie Vuille-Dit-Bille Past EPFL PhD Students as codirector Laura Joan Hermans, Sourabh Monnappa Kuppanda Jafri
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 MusaExpertise
Hydraulic engineering, experimental research, sediment transport, morphodynamics, river mechanics, hydropower, hydrokinetic energy, renewable energy
Mirko Musa is a tenure-track Assistant Professor of Hydraulic Engineering within the Institute of Civil Engineering at EPFL. He directs the STREEM Lab (Sustainable River Engineering, Energy, and Morphodynamics). STREEM Lab integrates laboratory experiments, data analysis, and analytical modeling to advance water power technologies, including hydropowe
Stefana ParaschoTeaching & PhD PhD Students Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Courses Capitalizing on Uncertainty AR-809 SUMMER SCHOOL - Capitalizing on Uncertainty is a 6-day Summer school exploring uncertainty as a productive resource in design and fabrication through lectures, hands-on experiments, and the collaborative design and construction of a full-scale structure in a human-robot fabrication setting. Digital design and making: A criti
Jakov OrebTeaching & PhD Courses Stone masonry: Past, present, and future PENS-232 This course introduces students to the historical, structural, and environmental aspects of stone masonry. Emphasis is on understanding the role of stone masonry in architecture, basic structural behavior, and approaches to predict and assess the performance of stone masonry buildings.
Mathias Christian Haindl CarvalloTeaching & PhD Courses Stone masonry: Past, present, and future PENS-232 This course introduces students to the historical, structural, and environmental aspects of stone masonry. Emphasis is on understanding the role of stone masonry in architecture, basic structural behavior, and approaches to predict and assess the performance of stone masonry buildings.
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
