Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
Allison Marie BurnsTeaching & PhD Courses Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b) This course will take place at EPFL in June 2026, from 8th to 12th, in room AAC 137.It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data.
Emily Clare GrovesProfessionals experiences Associate Lecturer 2018–2018 University of the Arts LondonResearch Assistant 2016–2017 Royal College of Art
Teaching & PhD Courses Design in innovation: creation for adoption MGT-406 In an ever more complex world, adoption is a critical factor for innovation. Using creativity and a transdisciplinary approach, this course brings together user-centred design and a deep understanding of value to develop sustainable innovations that benefit both citizens and the economy
Andy BushbyTeaching & PhD Courses CCMX Advanced Course - Instrumented Nanoindentation MSE-656 This course is intended for current nanoindentation users who want to gain the experience and knowledge required to extract useful data from challenging sample materials. It is also intended for users of conventional indentation methods who wish to add this approach to their portofolio of methods.
Nicholas X. RandallTeaching & PhD Courses CCMX Advanced Course - Instrumented Nanoindentation MSE-656 This course is intended for current nanoindentation users who want to gain the experience and knowledge required to extract useful data from challenging sample materials. It is also intended for users of conventional indentation methods who wish to add this approach to their portofolio of methods.
Edoardo ChiarottiTeaching & PhD Courses Data Science & Causal Inference for Sustainability MGT-499 This class explores key climate questions through data. Students will learn to collect, clean, and analyze data, apply causal methods using Python, and communicate insights clearly. With a focus on sustainability, the course builds skills to avoid pitfalls and draw meaningful conclusions.
Mathias Benjamin ThoenigTeaching & PhD Courses Economics for challenging times MGT-494 This course analyzes socio-economic issues related to poverty, inequalities, climate change, globalization, migration, AI, etc. We teach students how to analyze data using quantitative methods in economics and develop solutions compatible with the functioning of market economies.
Show more