Pascal Frossard
EPFL STI IEL LTS4
ELE 241 (Bâtiment ELE)
Station 11
1015 Lausanne
+41 21 693 56 55
+41 21 693 26 01
Office:
ELE 241
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Awards
SNSF Professorship
Swiss National Science Foundation
2003
IBM Faculty Award
2005
Exploratory Stream Analytics Innovation Award
IBM Research
2008
Teaching & PhD
PhD Students
Amel Abdelraheem, Tuna Alikasifoglu, Mahdi Amiri, Jérémy Jean Philippe Baffou, Cem Bilaloglu, William Cappelletti, Alba Carballo Castro, Adam Hazimeh, Vincent Jung, Manuel Madeira, Elisa Messori, Sevda Ögüt, Yiming Qin, Abdellah Rahmani, Vasiliki Rizou, Ke Wang, Yike Zhao
Past EPFL PhD Students
Ana Karina De Abreu Goes (2015), Clémentine Léa Aguet (2023), Zafer Arican (2010), Beril Besbinar (2022), Eirina Bourtsoulatze (2013), Isabela Cunha Maia Nobre (2022), Stefano D'Aronco (2018), Nikolaos Dimitriadis (2026), Xiaowen Dong (2014), Alhussein Fawzi (2016), Ádám Dániel Ivánkay (2023), Dan Jurca (2007), Sofia Karygianni (2015), Renata Khasanova (2019), Effrosyni Kokiopoulou (2009), Javier Alejandro Maroto Morales (2024), Apostolos Modas (2022), Seyed Mohsen Moosavi Dezfooli (2019), Guillermo Ortiz Jimenez (2023), Arnaud Pannatier (2024), Hermina Petric Maretic (2021), Ivana Radulovic (2008), Mattia Rossi (2020), Ortal Yona Senouf (2026), Yamin Sepehri (2024), Jelena Simeunovic (2024), Effrosyni Simou (2022), Dorina Thanou (2016), Vijayaraghavan Thirumalai (2012), Ivana Tosic (2009), Tamara Tosic (2013), Clément Vignac (2023), Elif Vural (2013), Jean-Paul Wagner (2008), Ahmet Caner Yüzügüler (2023)
Past EPFL PhD Students as codirector
Luigi Bagnato (2012), Alessandro Favero (2025), Angelos Katharopoulos (2022), Harshitha Machiraju (2024), Suraj Srinivas (2022)
Courses
EECS Seminar: Advanced Topics in Machine Learning
ENG-704
Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strengths and weaknesses of scientific arguments of both theoretical and experimental results.
Network machine learning
EE-452
Fundamentals, methods, algorithms and applications of network machine learning and graph neural networks