Martin Rajman is the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects for the engineering of complex systems in Health and the Environment. Since 2008, the Nano-Tera.ch program started more than 100 research projects for a total public funding of more than 95 Mo CHF (~100 Mo USD).
Before being appointed as Nano-Tera.ch Executive Director, Martin Rajman was Director of the EPFL Global Computing Center (CGC), an association of research groups and laboratories of the School of Computer and Communication Sciences fostering interdisciplinary research in the general area of internet computing and distributed information systems. In this position, he was managing more than 20 European projects.
In parallel with his research management activities, Martin Rajman is senior researcher at EPF Lausanne, Switzerland (EPFL). His research interests include Artificial Intelligence, Computational Linguistics and Data-driven Probabilistic Machine Learning.
Previously, he was senior researcher at the Computer Science Department of Telecom Paris-Tech, where he was in charge of the development of a research and teaching activity in the domain of Natural Language Processing.
Martin Rajman is also active in various large scale industry-research collaborations with majors economic players. In particular, he has been involved in the improvement of the product ranking technology used by e-Bay and is currently collaborating with Elsevier on enhanced article recommendation techniques.
Martin Rajman is author or co-author of more than 100 publications and former Director of the Computer Science Series of EPFL-Press (PPUR).
Publication list in EPFL Infoscience
Teaching & PhD
- Computer Science,
- Communication Systems
- Doctoral program in computer and communication sciences
On one side, this course covers the concepts of algorithms, the representation of information, signal sampling and compression, and an overview of systems (CPU, memory, etc.). On the other side, an introduction to programming in Python is given.
On one side, this course covers the concepts of algorithms, the representation of information, signal sampling and compression, and an overview of systems (CPU, memory, etc.). On the other side, an introduction to C programming is given.
The objective of this course is to present the main models, formalisms and algorithms necessary for the development of applications in the field of natural language information processing. The concepts introduced during the lectures will be applied during...