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Reproducible Research: moving to the BEAT

Research in computational science is overwhelmed by the constant influx of new algorithms and techniques promising improved performance, generalization and robustness.
However, reproducibility of results is often an overlooked feature accompanying publications and benchmark evaluations.

The main reasons behind such a gap arise from natural complications in research and development: 
the distribution of data can be a sensitive issue for most countries and organisations; 
software frameworks are difficult to install and maintain;
test protocols may involve a potentially large set of intricate steps which are difficult to handle. 
In this talk, we will first explain and demonstrate why reproducible research is important and beneficial.
However, given the raising complexity of research challenges and the constant increase in data volume, the conditions for achieving reproducible research in the domain are also increasingly difficult to meet.

To bridge this gap, we will present the BEAT platform ( ) for research, development and certification in computational science. By making use of such a system, academic, governmental or industrial organizations enable users to easily and socially develop processing toolchains, re-use data, algorithms, workflows and compare results from distinct algorithms and/or parameterizations with minimal interaction. 
The talk will present such a platform and will discuss some of its key features.


Sébastien Marcel received the Ph.D. degree in signal processing from Université de Rennes I in France (2000) at CNET, the research center of France Telecom (now Orange Labs). He is currently interested in pattern recognition and machine learning with a focus on biometrics security. He is a senior researcher at the Idiap Research Institute (CH), where he heads a research team and conducts research on face recognition, speaker recognition, vein recognition and presentation attack detection (anti-spoofing). In 2010, he was appointed Visiting Associate Professor at the University of Cagliari (IT) where he taught a series of lectures in face recognition. He is lecturer at the Ecole Polytechnique Fédérale de Lausanne (EPFL) where he is teaching on “Fundamentals in Statistical Pattern Recognition”. He serves on the Program Committee of several scientific journals and international conferences in pattern recognition and computer vision. He is Associate Editor of IEEE Signal Processing Letters. He was Associate Editor of IEEE Transactions on Information Forensics and Security, a Co-editor of the “Handbook of Biometric Anti-Spoofing”, a Guest Editor of the IEEE Transactions on Information Forensics and Security Special Issue on “Biometric Spoofing and Countermeasures”, and Co-editor of the IEEE Signal Processing Magazine Special Issue on “Biometric Security and Privacy”. Finally he was the principal investigator of international research projects including MOBIO (EU FP7 Mobile Biometry), TABULA RASA (EU FP7 Trusted Biometrics under Spoofing Attacks) and BEAT (EU FP7 Biometrics Evaluation and Testing).