Short biography
André Anjos holds a Ph.D. degree in signal processing from the Federal University of Rio de Janeiro (2006). He spent nearly a decade (2001–2010) at CERN’s ATLAS Experiment, where he played a key role in developing and deploying the Trigger and Data Acquisition systems that enabled groundbreaking discoveries, including the Higgs boson. During this period, André explored the application of neural networks and statistical methods to particle recognition, contributing several software components that remain in use today. In 2010, André joined the Biometrics Security and Privacy Group at the Idiap Research Institute, where he focused on face and vein biometrics and presentation-attack detection, with a keen interest in reproducibility and open science. Since 2018 André leads the Medical AI Group (MedAI) at Idiap, investigating medical applications, image and signal processing, machine learning, research reproducibility, and open science. Among André’s open-source contributions are Mednet and the BEAT framework for evaluation and testing of machine-learning systems. He teaches graduate-level machine-learning courses at the École Polytechnique Fédérale de Lausanne (EPFL) and Idiap’s Master of AI, and serves as a reviewer for various scientific journals in pattern recognition, machine learning, and image processing.Very short biography
André Anjos holds a Ph.D. in signal processing and machine learning (2006), studying neural networks and statistical methods for particle recognition in High-Energy Physics experiments at CERN’s Large Hadron Collider. He joined the Idiap Research Institute in 2010, focusing on biometrics. Today André leads the Medical AI Group at Idiap. Current interests include medical decision making, image and signal processing, machine learning, research reproducibility, and open science. He teaches graduate-level machine-learning courses at EPFL and Idiap’s Master of AI, and reviews for journals in pattern recognition, image processing, and biometrics.One-liner
André Anjos leads the Medical AI Group at the Idiap Research Institute, working on machine learning, computer vision, and signal processing for medical decision making, research reproducibility, and open science.Profile photo
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