EDIC Orientation
Week 1: September 6th -9th, 2022
Room BC 420
- Tuesday, Sept 6
- 13:00-13:20 : Geometric Computing – Mark Pauly
13:20-13:40 : Decentralized Distributed Systems – Bryan Ford
13:40-14:00 : Visual Intelligence and Learning – Amir Zamir – Slides–
14:00-14:20 : Laboratory for Information and Inference Systems – Volkan Cevher – Slides– - Wednesday, Sept 7
13:20-13:40 : Programming Methods – Martin Odersky
13:40-14:00 : Parallel Systems Architecture – Babak Falsafi
14:00-14:20 : Chair of Mathematical Data Science – Emmanuel Abbé- Thursday, Sept 8
- 13:00-13:20 : Data Analysis Theory and Applications – Christoph Koch
13:20-13:40 : Processor Architecture – Paolo Ienne
13:40-14:00 : High-Assurance Operating Systems and Networks – George Candea
14:00-14:20 : Robust Scalable Systems Software – Sanidhya Kashyap - Friday, Sept 9
- 13:00-13:20 : Network Architecture Lab – Katerina Argyraki
13:20-13:40 : Security and Privacy Engineering – Wouter Lueks for Carmela Troncoso
13:40-14:00 : Scalable Computing Systems – Anne Marie Kermarrec
14:00-14:20 : Distributed Computing – Rachid Guerraoui
Week 2: September 12th-16th, 2022
Room BC 420
- Monday, Sept 12
- 13:00-13:20 : Information and Network Dynamics – Patrick Thiran
13:20-13:40 : Sensing and Networking Systems – Haitham Hassanieh
13:40-14:00 : Systems Control And Multiagent Optimization Research – Maryam Kamgarpour - Tuesday, Sept 13
- 13:00-13:20 : online Information Measures in Networks and Machine Learning – Michael Gastpar – CANCELLED!
13:20-13:40 : Immersive Interaction – Ronan Boulic – Slides
13:40-14:00 : Machine Learning and Optimization – Martin Jaggi
14:00-14:20 : Computational Neuroscience – Wulfram Gerstner - Wednesday, Sept 14
- 13:00-13:20 : Automated Reasoning and Analysis – Viktor Kuncak –Slides
13:20-13:40 : Data-Intensive Applications and Systems – Anastasia Ailamaki
13:40-14:00 : Realistic Graphics – Wenzel Jakob
14:00-14:20 : online Information Measures in Networks and Machine Learning – Michael Gastpar - Thursday, Sept 15
- 13:00-13:20 : Machine Learning for Education – Tanja Käser
13:20-13:40 : Machine learning for biomedicine- Maria Brbic
13:40-14:00 : Machine Learning for Chemistry – Philippe Schwaller
14:00-14:20 : Signal Processing Laboratory – Pascal Frossard - Friday, Sept 16
- 13:00-13:20 : Computer Vision – Mathieu Salzmann – Slides