Bruno Emanuel Ferreira De Sousa CorreiaThroughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.
Cécile HardebolleCurrent work
Responsible information systems (https://go.epfl.ch/digitalethics), ethical skills Jupyter notebooks for education (https://go.epfl.ch/notebooks), digital skills, computational thinking Transversal/professional skillsEngineering design skillsFlipped classrooms Project-based learning
Education PhD | Computer Science 2006 – 2008 Université Paris-Sud XI, France Directed by Prof. Guy Vidal-Naquet MSc | Electrical Engineering, major in Computer and Inf Johanni Michael BreaTeaching & PhD PhD Students Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Courses Artificial intelligence and society HUM-286 This course integrates social sciences and humanities with engineering sciences, and introduces students to the social, technical and political issues surrounding artificial intelligence. Biological data science II : machine learning BIO-322 Students understand basic concepts and methods of machine learning. They can describe them in mathematical
Hannes Markus PeterCurrent work
I am a microbial ecologist and mainly interested in factors shaping bacterial communities and functioning in freshwater ecosystems. I use combinations of field observations, experiments and molecular techniques to test hypotheses regarding the assembly of microbial communities, the influence of environmental variability and relationships between diversity and funcioning. I enjoy working in alpine environments, which are sensitive to climate change and represent excellent model systems.
Teaching
Amaury Pierre Jiezhi WeiExpertise
Deep Learning, Computer Vision, Physics Informed Machine Learning, Graph Neural Networks
Amaury obtained his Master's degree in Robotics from the Federal Institute of Technology in Lausanne (EPFL) in 2021.Before joining IMOS, he worked for multiple years at Logitech Europe S.A. as a Software Engineer in the field of Augmented and Virtual Reality. He researched 6DoF tracking solutions for handheld devices, developed the firmware and designed the testing strategy for the MR Stylus MX Ink.During his
Andreas ZüttelTeaching & PhD PhD Students Boyu Ouyang, Wai Kwan Liu, Guillaume Bérenger Rod, Aleksandar Mihaylov Mikov, Rui Li, Akhil Varma Penmathsa Past EPFL PhD Students Robin Tobias Andreas Mutschler, Kun Zhao, Loris Giovanni Lombardo, Mo Li, Jie Zhang, Youngdon Ko, Cedric David Koolen, Thi Ha My Pham, Zohreh Akbari, Yasemen Kuddusi Courses Thermodynamics of energy conversion and storage ChE-414 The course is an introduction to the energy conversion. It focusseson the thermodynamics of the engines a
David Lyndon EmsleyCurrent Work
Our research centres on the development of new NMR spectroscopy experiments to determine the atomic-level structure and dynamics of complex materials and molecular systems, to solve a range of problems across disciplines.
Teaching & PhD PhD Students Ray Cowen, Ümmügülsüm Günes, Máté Visegrádi, Ruben Rodriguez Madrid Past EPFL PhD Students Dominik Józef Kubicki, Arthur César Pinon, Albert Hofstetter, Federico Maria Paruzzo, Baptiste Busi, Snaedis Björgvinsdóttir, Martins Balodis, Aditya Mishra
Babak RahmaniI am a PhD student in Electrical Engineering department of EPFL where I am advised by Christophe Moser. I also work closely with Demetri Psaltis on Machine learning and its applications in inverse problems, information retrieval and control systems. Prior to joining EPFL, I graduated from Sharif University of Technology, Iran with a M.Sc. and Tehran University, Iran with a B.Sc. both in Electrical Engineering. My goal is to build robust and reliable machine learning algorithms for controlling real-world complex systems in various disciplines ranging from communication, imaging systems to neuroscience and robotics.Please visit my Google Scholar (link above) for an updated list of my publications.
Paul DelrotExpertise
Volumetric printing, optics, photopolymers.
Current work
Investigating innovative laser-based additive manufacturing technologies.
Education PhD | Photonics 2018 Р2018 Ecole Polytechnique F̩d̩rale de Lausanne MSc | Optics 2014 Р2014 Institut d'Optique Graduate School MSc | Engineering Physics 2014 Р2014 Kungliga Tekniska H̦gskolan
Tom Ian BattinTeaching & PhD PhD Students Zhe Liu, Aleksei Dukat, Martin Boutroux, Jingyi Hou, Léa Francomme, Stefan Eckensperger Past EPFL PhD Students Amin Niayifar, David Scheidweiler, Asa Lovisa Viktoria Horgby, Marta Boix Canadell, Pier Luigi Segatto, Anna Depetris, Jade Brandani, Massimo Bourquin, Jonas Paccolat, David Touchette Past EPFL PhD Students as codirector Jeremy Wong Courses Aquatic ecosystems ENV-321 Inland waters are now being recognized are major players of global biogeochemical cycle
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
