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Prof. Hervé Bourlard was Director of the Idiap Research Institute between 1996 and 2023. He is a Full Professor at EPFL and External Fellow (and member of the Board of Trustees) of the International Computer Science Institute (ICSI), Berkeley, CA (USA). He was the founding Director of the National Center of Competence in Research (NCCR) on Interactive Multimodal Information Management (IM2, 2001-2013).

His research interests mainly include statistical pattern classification, signal processing, multi-channel processing, artificial neural networks, and applied mathematics, with applications to a wide range of information and communication technologies, including spoken language processing, speech and speaker recognition, language modeling, multimodal interaction, augmented multi-party interaction, and distant group collaborative environments.

He is a Fellow of the IEEE and ISCA (International Speech Communication Association), a member of the ACM Europe Council, and elected member of the Swiss Academy of Engineering Sciences. He is the recipient of several prestigious scientific and entrepreneurship awards.

Prof. Michael Liebling leads the Computational Bioimaging Group at Idiap. He is also affiliated with the University of California Santa Barbara, where he served as Associate Professor until 2017. He received his PhD (Dr.ès sc.) from EPFL in 2004.

His research interests are biological image acquisition, reconstruction, processing, and analysis. More specifically, he focuses on developing novel microscopy instrumentation combined with computational tools to quantify dynamic biological systems. Tools developed in his lab have enabled dynamic, multi-modal, and in vivo cellular imaging during embryonic heart morphogenesis.

Prof. Sébastien Marcel is Head of the Biometrics Security and Privacy Group. He is also Director of the Swiss Center for Biometrics Research and Testing. In 2010, he was appointed Visiting Associate Professor at the University of Cagliari (IT). He is also a lecturer at the Ecole Polytechnique Fédérale de Lausanne (EPFL). He received his Ph.D. in Signal Processing from the Université de Rennes I (France) in 2000.

He is currently interested in pattern recognition and machine learning with a focus on biometric security ie. face, voice, and vein recognition and the detection of presentation attacks (anti-spoofing). He is currently Associate Editor of the IEEE Signal Processing Letters. He has been Associate Editor of IEEE Transaction on Information Forensics and Security (TIFS), and was co-Editor of the "Handbook of Biometric Anti-Spoofing",and Guest Editor of an IEEE TIFS Special Issue on "Biometric Spoofing and Countermeasures" and of the IEEE Signal Processing Magazine Special Issue on "Biometric Security and Privacy".

He has been the principal investigator of EU FP7 research projects including MOBIO, TABULA RASA and BEAT. His recent research has been supported by the SNSF, CTI, and EU, and by Norway, and the industry (including Safran Morpho, and Google).

Prof. Lonneke van der Plas is head of the Computation, Cognition and Language Group at Idiap. She has been leading several national and EU research projects since her junior professorship at the University of Stuttgart in 2012. She holds a PhD from the University of Groningen and an M.Phil from the University of Cambridge. Currently, she is affiliated to the University of Malta as a Professor.

Her research is in the field of Natural Language Processing, in particular in the areas of multilingual processing and language understanding. She is known for her work on vector-based semantics, NLP for low-resource languages, and semantic role labelling. Her current research focuses on exploring cognitive models to enhance computational models for language processing and generation in order to encompass the flexibility and creative processes at play in language use and interaction, and the efficiency in language learning.

Dr. Jean-Marc Odobez received his PhD from Rennes University/INRIA in 1994 and was, from 1996 to 2001, Assistant Professor at the University of Maine, France. He is now a Senior Researcher at Idiap and adjunct faculty at the École Polytechnique Fédérale de Lausanne (EPFL) where he is a member of the School of Engineering (STI).

His research theme is the creation of multimodal perception systems and the research of methods in the fields of signal processing, computer vision, machine learning, or social sciences to model, understand and recognize human activity, behaviors, non-verbal communication and human-robot interactions. Application areas are surveillance, multimedia content analysis or social robotics.

He is the author or coauthor of more than 150 papers, and has been the principal investigator of more than 14 European and Swiss projects. He holds several patents in computer vision, and is the cofounder of the companies Klewel SA (www.klewel.ch) and Eyeware SA (http://www.eyeware.tech/) companies. He is a member of the IEEE, and Associate Editor of the IEEE Transaction on Circuits and Systems for Video Technology and of Machine Vision and Application journals.

Dr. Sylvain Calinon has been a lead scientists at Idiap since May 2014, with research interests covering robot learning and human-robot interaction.

His research focuses on human-centric robotic applications in which the robots can learn new skills by interacting with the end-users. The challenge is to acquire skills from only few demonstrations and interactions, with strong generalization requirements. This requires the development of intuitive active learning interfaces to acquire meaningful demonstrations, the development of models that can exploit the structure and geometry of the acquired data in an efficient way, and the development of adaptive control techniques that can exploit the learned task's variations and coordination patterns.

Dr James Henderson is the Head of the Natural Language Understanding group, since joining Idiap in September 2017. He received his PhD from the University of Pennsylvania.

His research is in Natural Language Processing and Machine Learning, covering a wide range of topics but focusing on deep learning architectures for natural language understanding tasks. He did pioneering work on deep learning for structured prediction in natural language processing, and has extensive experience in spoken dialog systems. His current research interests focus on deep learning methods for discovering representations of meaning in natural language, including representations of semantic abstraction and their application to large scale opinion summarization.

Dr. Philip N. Garner received an M.Eng. Degree in Electronic Engineering from the University of Southampton, (UK) in 1991, and his Ph.D. (by publication) from the University of East Anglia, (UK) in 2012.

As of April 2007, he is a senior research scientist at Idiap continuing his work in the research and development of speech recognition, synthesis and signal processing. He also holds a lecturing position at EPFL.
He is a Senior Member of the IEEE, has published internationally in conference proceedings, patent, journal and book form and has served as coordinating editor of ISO/IEC 15938-4 (MPEG-7 Audio). He is the author of several patents.

Dr. Mathew Magimai Doss has been a senior researcher within the Speech and Audio Processing Group since 2007. He has also been a lecturer at EPFL since 2010. He was awarded a PhD (Dr.ès sc.) in Electrical and Electronics Engineering from EPFL in 2005. He has published more than 90 papers in peer-reviewed journals and a range of conference papers.

He is the co-founder of AudioSearch SARL, an Idiap spin-off created in 2010. His research interests are speech and audio processing, signal processing, statistical pattern recognition, and artificial neural networks.

André Anjos received his Ph.D. degree in signal processing in 2006 studying the application of neural nets and statistical methods for particle recognition in the context of High-Energy Physics experiments at Large Hadron Collider at CERN, Switzerland. He joined the Idiap Research Institute in 2010 where he works with biosignal processing and biometrics applications. He currently heads the Biosignal Processing Group at Idiap. Current interests include medical applications, reproducible research, pattern recognition, image processing and machine learning. André teaches graduate-level machine learning courses at the École Polytechnique Fédérale de Lausanne (EPFL) and serves as reviewer for various scientific journals in pattern recognition, image processing and biometrics.

Ina Kodrasi received the Master of Science degree in Communications, Systems, and Electronics from Jacobs University Bremen, Germany, in 2010, and the Ph.D. degree from the University of Oldenburg, Germany, in 2015. Since January 2021, she is leading the Signal Processing for Communication group at Idiap. She is also teaching in the Master in Artifical Intelligence program offered by Idiap and the Swiss Distance University Institute.

Her current research interests are in the area of signal processing and machine learning for speech, audio, and clinical applications. The main focus of her group is to establish novel algorithms to automatically detect speaking and hearing impairments, to provide speaking and hearing assistance, and to improve the communication experience in the presence of interferences.

She has been awarded the "Preis der ITG 2019" and the "EURASIP 2020 Best PhD Award". She serves as an elected member of the IEEE Signal Processing Society Technical Committee on Audio and Acoustic Signal Processing and of the EURASIP Technical Area Committee on Acoustic, Speech and Music Signal Processing.

André Freitas leads the Reasoning & Explainable AI group at Idiap. He is also a senior lecturer (associate professor) at the Department of Computer Science at the University of Manchester and the AI group leader at the digital Experimental Cancer Medicine Team (CancerResearchUK).

His main research interests are on enabling the development of AI methods to support abstract, explainable and flexible inference. In particular, he investigates how the combination of neural and symbolic data representation paradigms can deliver better inference. Some of his research topics include: explanation generation, natural language inference, explainable question answering, knowledge graphs and open information extraction. He is actively engaged in collaboration projects with industrial and clinical partners.