Find Academic Supervisors

Hazel DoughtyView profile

Assistant Professor

• Video Understanding
• Computer Vision
• Action Recognition
• +7 more

Hazel Doughty is an Assistant Professor at Leiden University in the Leiden Institute for Advanced Computer Science (LIACS) . Previously, she was a postdoctoral researcher at the University of Amsterdam and completed her PhD at the University of Bristol under the supervision of Prof. Dima Damen and Prof. Walterio Mayol-Cuevas. Research Interests: Video Understanding, Skill Determination, Self-Supervised Learning, Temporal Attention, and Adverb Recognition in Instructional Videos. Grants: Co-Applicant for DUAL-IMPACT (NWO High Tech Systems and Materials, €1.25M); Main Applicant for NWO Veni grant ( From What to How: Perceiving Subtle Differences in Videos , €280K). Scientific Recognition: Veni Grant (2023) ELLIS Member (2022) Outstanding Reviewer for CVPR, NeurIPS, ECCV, and ACCV Academic Service: Organizer of workshops at CVPR 2024, BMVC 2023, NCCV 2024, and NeurIPS'21. Area Chair for CVPR, ICCV, NeurIPS, AAAI. Teaching: Courses on Computer Vision (BSc) and Advances in Deep Learning (MSc) at Leiden University. Her work focuses on fine-grained video understanding with weak or incomplete supervision , including adverb analysis, self-supervised learning, and egocentric vision datasets. Her recent publications analyze benchmark sensitivity, motion-focused video-language models, and generalized category discovery. Collaborations include the HAVA lab at the University of Amsterdam and the EPIC-Kitchens-100 project. She leads the DUAL-IMPACT initiative on high-tech systems and co-organized workshops at CVPR, ICCV, and NeurIPS. Her students include PhD candidates Luc Sträter and Kaiting Liu , and former advisees like Fida Mohammad Thoker (now postdoc at KAUST) and Piyush Bagad (now PhD at Oxford).

Sophie SchwartzView profile

Professor

• Sleep Neuroscience
• Cognitive Neuroscience
• Neuroimaging (fMRI, hd-EEG, MEG)
• +7 more

Prof. Sophie Schwartz is a leading neuroscientist at the University of Geneva , where she heads the Sleep & Cognition Lab within the Faculty of Medicine . Her research integrates neuroimaging (fMRI, hd-EEG, MEG) , behavioral testing , and computational modeling to unravel the neural mechanisms underlying memory consolidation , emotion processing , and dreaming during sleep, while also developing clinical interventions to enhance sleep in neurological and psychiatric disorders.

Petr MotlicekView profile

Lecturer

• Speech Processing
• Audio Coding
• Signal Processing
• +1 more

Petr Motlicek is a Lecturer at the École polytechnique fédérale de Lausanne (EPFL) in the Institute of Electrical Engineering. His research focuses on speech and audio processing technologies. At the Laboratoire de l'IDIAP, he conducts interdisciplinary work bridging engineering and cognitive science. His primary research interests include digital speech coding algorithms and auditory perception models. His work examines how signal processing techniques can integrate knowledge about sound production and human auditory perception. Dr. Motlicek has supervised multiple PhD students including Kumar Shashi, Dey Subhadeep, He Weipeng, and Zuluaga Gomez Juan Pablo. He teaches the course Digital Speech and Audio Coding which covers state-of-the-art techniques in the field.

Lukas FischerView profile

Researcher

• Natural Language Processing
• Machine Translation
• Computational Linguistics
• +4 more

Lukas Fischer is a researcher specializing in Natural Language Processing and Machine Translation, currently affiliated with the Language, Technology and Accessibility project. He holds an M.Sc. in Artificial Intelligence from the University of Edinburgh (2017-2018) and a B.A. in Computational Linguistics from the University of Zurich (2012-2016). His recent roles include lead developer for the Digilinguo online platform since 2025 and contributions to multimodal machine translation projects like IICT and Bullinger Digital. Research Focus: Machine translation for historical languages (Latin, Early New High German) Text simplification and accessibility technologies Multimodal translation systems Data curation for multilingual historical corpora Code-switching detection in early modern texts Publications highlight his work on SwissADT (audio description translation for Swiss languages), LLM-based Latin translation, and medieval text processing. His projects span both computational linguistics and practical accessibility applications.

Julian TachellaView profile

Researcher

• Signal Processing
• Machine Learning
• Computational Imaging
• +5 more

Dr. Julian Tachella is a CNRS Research Scientist at the Sisyph Laboratory of École Normale Supérieure de Lyon, with co-founder/CSO roles at Blur Labs. His career spans signal processing, machine learning, and computational imaging, focusing on inverse problems and self-supervised learning. Affiliation: CNRS (French National Centre for Scientific Research), Sisyph Laboratory, École Normale Supérieure de Lyon Co-founder & CSO: Blur Labs (AI/Imaging startup) Research Interests: At the intersection of signal processing and deep learning , his work addresses imaging inverse problems through self-supervised methodologies (e.g., UNSURE, Generalized R2R) that eliminate ground-truth requirements. Key contributions include equivariant imaging frameworks for stability, spline sketches for photon-counting lidar compression, and uncertainty quantification techniques with equivariant bootstrapping. Recent Trends: 2025 publications emphasize lightweight architectures for multi-domain reconstruction (CT, super-resolution) and noise-agnostic SURE methods. 2024 works focus on audio declipping , compressed lidar , and nonlinear algorithm unrolling with applications in autonomous vehicles and medical imaging. Scientific Awards: Best Student Paper Award at ICASSP’22 Collaborations & Leadership: He leads the DeepInverse open-source project and develops algorithms for real-time 3D lidar reconstruction. His team includes researchers from University of Edinburgh and Grenoble INP, with applications in automotive lidar and underwater imaging.

Anne-Lise GiraudView profile

Professor

• Neural Bases of Language
• Speech Processing
• Vocal Communication
• +6 more

Anne-Lise Giraud is a Professor and Group Leader at the Faculty of Medicine, University of Geneva, where she directs a research laboratory focused on the neural mechanisms underlying language and vocal communication. Her work bridges experimental neurophysiology, computational neuroscience, and clinical applications for language disorders. Her research interests encompass: Neural bases of speech and language processing Audio-visual integration in communication Brain-Computer Interfaces for speech communication Neural mechanisms of language disorders (dyslexia, autism, aphasia) Computational modeling of speech processing Comparative studies of vocal communication across species Dr. Giraud's recent publications demonstrate a sophisticated integration of multiple neuroimaging techniques (EEG, fMRI, MEG) with computational approaches to understand both typical and atypical speech processing. A notable trend in her work is the emphasis on neural oscillations as fundamental mechanisms for speech perception, with applications ranging from understanding autism spectrum disorders to developing brain-computer interfaces for communication-impaired individuals. Her research increasingly explores cross-species communication mechanisms, as evidenced by her recent work on dog-human vocal interactions. Her laboratory at Campus Biotech includes multiple graduate students, postdocs, and research assistants working collaboratively on various aspects of language neuroscience.

Beat SuterView profile

Senior Lecturer

• Game Design
• Game Studies
• Digital Humanities
• +6 more

Dr. Beat Suter is a Senior Lecturer for Game Design at the Zurich University of the Arts (ZHdK) , where he has co-developed educational programs and founded the GameLab ZHdK. He holds a Dr. Phil. from the University of Zurich and has previously taught at the Merz Academy Stuttgart (2006–2014). His interdisciplinary work bridges game design, digital humanities, and electronic literature, with a focus on narrative mechanics, game preservation, and Swiss game culture. Education: Dr. Phil. (2000) – University of Zurich Lic. Phil. I (1987) – University of Zurich PALC Certificate – University of California San Diego Studies in German Literature, Linguistics, and Art History – University of Zurich and University of California His research explores intersections between game studies , digital archiving , and interactive narration , with recent publications analyzing Swiss youth culture in games, historical game packaging, and archiving digital interactive media. He co-authored the Narrative Mechanics (2021) and Games and Rules (2018) anthologies, emphasizing rule-based design and storytelling frameworks. From 2023, his 15 most recent articles (2023–2025) trace trends in game history , Swiss game design , and digital preservation , often published via the Confoederatio Ludens blog. These works highlight his focus on documenting marginalized game practices and cultural contexts. As founder of the art group AND-OR and co-director of the GameZ & RuleZ conference, Suter actively shapes interdisciplinary dialogues. He reviews for national research funds in Austria, Germany, and Switzerland and has curated exhibitions like RuleZ for the Magic Circle and Forgotten Game Mechanics , blending academic rigor with creative practice.

• Natural Language Processing
• Machine Translation
• Speech Processing
• +3 more

Popescu-Belis Andrei serves as an Associate Professor at the University of Applied Sciences and Arts Western Switzerland (HES-SO), specifically within the Institute of Information and Communication Technologies (IICT) at HEIG-VD campus in Yverdon-les-Bains. His academic work spans teaching computer science fundamentals and advanced natural language processing concepts across both undergraduate and graduate programs. His research interests focus on Natural Language Processing , Machine Translation , and Human-Machine Dialogue systems, with particular emphasis on low-resource language scenarios. His work addresses challenges in speech-to-speech translation, subword tokenization, neural machine translation optimization, and creative applications like poem generation. Recent publications through 2025 demonstrate his ongoing contributions to the field, particularly in multilingual NMT training schedules and low-resource language processing pipelines. Analysis of his 15 most recent publications reveals consistent focus on practical solutions for language barriers, with increasing attention to reinforcement learning applications and creative language generation. His work on GPoeT demonstrates the intersection of traditional literary forms with modern language models, while his research on low-resource translation pipelines addresses real-world community interpreting needs. He has led significant research projects including Digital Lyric (2019-2020), a collaboration with UNIL (University of Lausanne) to develop systems for aiding poem generation for a public exhibition at Morges Castle. This project demonstrates his interdisciplinary approach bridging computational linguistics with creative applications. His academic contributions include: Development of specialized training pipelines for low-resource neural machine translation Innovative approaches to speech-to-speech translation for community interpreting Novel methods for constrained language model applications in creative writing Significant contributions to understanding subword tokenization mechanics Popescu-Belis maintains active research collaborations across institutions, as evidenced by his work with UNIL and various international conference publications. His teaching portfolio includes courses in natural language processing, data preparation, unsupervised machine learning, and computer science fundamentals, demonstrating his commitment to both theoretical and practical aspects of the field.

• Embedded Systems
• AI Algorithms
• FPGA/VHDL Design
• +5 more

Jürgen Wassner is a Professor of Edge Computing and Co-Head of the Competence Center for Intelligent Sensors and Networks at the Lucerne School of Engineering and Architecture (HSLU T&A). He holds a master's degree from Technical University of Dresden and a PhD from ETH Zurich. His career spans industry roles in Silicon Valley Group Inc. and telecommunication R&D before joining academia in 2007. His research focuses on embedded systems, AI at the edge, FPGA/VHDL design, real-time systems, and powerline communication . He leads projects such as 'Visual-Servoing Testbed with AI-Hardware in the Loop' and 'Low-Cost High-Performance Intelligent Camera for Space Debris Mitigation,' collaborating with companies like Diehl Aerospace. Recent publications emphasize wire fault detection using powerline communication, AI-based odor classification systems, and hardware acceleration for CNNs. His work bridges theoretical research with practical applications in avionics, rail freight, and space debris mitigation. Wassner advises Master of Science in Engineering students and has been recognized for his media engagement including a feature in the Luzerner Zeitung. He teaches Digital Design (FPGA, VHDL) and Digital Signal Processing , emphasizing hands-on implementation of cutting-edge systems.

Mutian HeView profile

Academic

• Spoken Language Understanding
• Speech Synthesis
• Natural Language Processing
• +12 more

Mutian He is a PhD candidate and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, affiliated with the Idiap Research Institute and the School of Engineering. He is pursuing his doctoral studies in Electrical Engineering under the supervision of Phil Garner. He holds a B.E. from Beihang University (BUAA) and an MPhil from the Hong Kong University of Science and Technology (HKUST). B.E., Beihang University (BUAA), 2019 MPhil, Hong Kong University of Science and Technology, 2022 PhD Candidate, École Polytechnique Fédérale de Lausanne (EPFL), ongoing His research focuses on spoken language understanding, speech synthesis, and the intersection of speech and language processing with machine learning. He explores efficient model architectures, pretraining strategies, multilingual and low-resource modeling, and the use of large language models in speech tasks. His work spans both theoretical and applied aspects, including distillation to linear-complexity models, robust TTS, and commonsense reasoning via conceptualization. His recent publications at top venues such as ICLR, EMNLP, Interspeech, and KDD demonstrate a strong trend towards efficient and scalable models for speech and language, with increasing emphasis on multilingualism, knowledge transfer, and real-world deployment in low-resource settings. He has also contributed to open-source implementations and community tools like Speech Rankings. Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity (ICLR 2025) Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization (AIJ 2024) The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation (Findings of EMNLP 2023) Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding (Interspeech 2023) Multilingual Byte2Speech Models for Scalable Low-resource Speech Synthesis (2022) Mutian He has served as a teaching assistant for courses including Introduction to Natural Language Processing at HKUST and Introduction to Speech Processing at Idiap. He has also worked on speech synthesis at Microsoft, focusing on robustness and multilingual conditions. He is actively involved in research advising under Phil Garner and has collaborated with multiple researchers across institutions. He is affiliated with the LIDIAP (Laboratory of Intelligent Data Analysis and Pattern Recognition) at EPFL, where he contributes to research in deep learning for speech and language. His lab work involves developing novel neural architectures, conducting experiments on multilingual datasets, and open-sourcing code to promote reproducibility.

• Speech Processing
• Audio Coding
• Signal Processing
• +3 more

Mathew Magimai Doss is a Lecturer at the School of Engineering (STI), École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the LIDIAP Laboratory. He teaches courses on Automatic Speech Processing and Digital Speech and Audio Coding , focusing on integrating signal processing with auditory perception principles. His research likely intersects with EPFL’s strategic emphasis on interdisciplinary engineering and applied sciences. Academic Affiliation School: École Polytechnique Fédérale de Lausanne (EPFL), School of Engineering (STI), LIDIAP Laboratory Additional Teaching Roles: EDEE - Teaching, SEL - Teaching Advising Current PhD Students: El Hajal Karl, Purohit Tilak, Sarkar Eklavya, Tarigopula Neha Past EPFL PhD Students: Dubagunta Subrahmanya Pavankumar, Fritsch Julian David, Hermann Enno, Mostaani Zohreh, Muckenhirn Hannah, Rasipuram Ramya, Razavi Marzieh, Tornay Sandrine Contact Information Email: mathew.magimaidoss@epfl.ch Office: ELD 241, Bâtiment ELD, Station 11, 1015 Lausanne

• Signal Processing
• Acoustics
• Psychoacoustics
• +7 more

Armin Taghipour is a Professor in Signal Processing and Acoustics at the Institute of Electrical Engineering, Lucerne School of Engineering and Architecture. He leads the Research Group Waves & Signal Processing and oversees Continuing and Executive Education in Innovation & Technology. His roles include MSE Advisor in the HSLU Master of Science program and President of the Swiss Acoustical Society SGA-SSA. Education: B.Sc. Microelectronics (University of Guilan, Iran), M.Sc. Telecommunications (University of Hanover, Germany), Dr. Eng. in Psychoacoustics (International Audio Laboratories Erlangen, Germany). Professional expertise spans audio signal processing, psychoacoustic modeling, noise annoyance evaluation, and acoustic comfort design. He has conducted research at Empa, Fraunhofer IIS, and the Hanover Medical School. Research focuses on urban acoustics, noise mitigation, room acoustics optimization, and psychoacoustic experiments. Recent work addresses soundscape quality in residential areas, cognitive impacts of noise, and AI-driven odor classification systems. Over 50 publications span environmental acoustics, audio engineering, and multidisciplinary applications. Lab leadership: Head of Research Group Waves & Signal Processing Key projects: Soundscape design, autonomous acoustic measurement systems, and green healthcare building acoustics Grants: IDN Performance Lab project leadership (2022) Labs/Teams: Active in the Institute of Electrical Engineering's Autonomous Systems & Robotics division, collaborating with DAGA, EAA, and SGA-SSA.

• Human-Computer Interaction
• Recommender Systems
• Deep Reinforcement Learning
• +4 more

Ingram Sandy is a Professor at the Haute école d'ingénierie et d'architecture de Fribourg (HES-SO), part of the iSIS Institute for Intelligent and Secure Systems. Her research focuses on Human-Computer Interaction, Recommender Systems, and Digital Wellbeing, with a strong emphasis on applying technology to education and workplace environments. She leads and collaborates on interdisciplinary projects addressing challenges in smart environments, user experience design, and AI integration in learning platforms. Key projects include developing serious games for mental health support (Sesame Project), workplace comfort systems (SpotOn), and chatbot-enhanced educational tools. She has also contributed to frameworks like eLogBook and Graasp, aiming to bridge formal and informal learning through social software innovations. Her work spans over 15 years, with publications in top venues like IEEE, ACM, and international conferences on human-computer interaction and learning technologies. Ingram Sandy’s research interests span from foundational AI methods (reinforcement learning, deep learning) to applied domains like digital wellbeing assessment, smart office comfort modeling, and chatbot-mediated education. She actively collaborates with industry partners (e.g., OrchardAI) and academic networks across Switzerland and Europe. Her contributions highlight the intersection of technology, human behavior, and educational design.

Dongqing WangView profile

Researcher

• Neural Rendering
• Computer Graphics
• 3D Computer Vision
• +6 more

Dongqing Wang is a Doctoral Assistant and PhD candidate at the Image and Visual Representation Laboratory (IVRL), School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is advised by Prof. Sabine Süsstrunk and is currently on the academic job market. His work bridges computer graphics, 3D vision, and machine learning with a focus on neural rendering and visual representation. Bachelor of Science in Computer Science, Cornell University Master of Engineering, Cornell University His research focuses on Neural Rendering , 3D Computer Vision , and Machine Learning , particularly in developing novel models for dynamic radiance fields, 3D-consistent object editing, and neural matting for transparent objects. He explores real-time stylization of volumetric effects and disentangled representations for relighting and novel view synthesis. His recent publications in top venues like CVPR, ICCV, and BMVC demonstrate expertise in neural scene representation, 3D inpainting, and expressive visual synthesis. Trends include leveraging 3D priors for 2D editing, dynamic texture synthesis, and multimodal learning for visual effects. Qualcomm Innovation Fellowship 2024 WiGRAPH Rising Star in Computer Graphics 2024 Dongqing Wang has contributed to research projects in human-robot interaction, music visualization, and on-skin interfaces during his studies. He has not been mentioned as advising students or leading grants, though his fellowship awards indicate competitive external funding. He is actively involved in the academic community, attending and presenting at major conferences such as SIGGRAPH. He is affiliated with the Image and Visual Representation Lab (IVRL) at EPFL, a leading research group in computer vision and graphics, where he conducts research on next-generation visual representation models and tools.

Gerhard SchrattView profile

Professor

• Molecular Neuroscience
• Synaptic Plasticity
• Non-coding RNAs
• +1 more

Gerhard Schratt is Full Professor and Head of the Institute for Neuroscience at ETH Zürich. His laboratory investigates molecular mechanisms of synapse development and plasticity, with emphasis on non-coding RNA regulation in neurological disorders. Research integrates molecular neurobiology with computational approaches to study microRNA functions in neuronal development, synaptic homeostasis, and stress responses. Current projects examine RNA-based therapies for neurodegenerative conditions and computational pathology platforms for digital histology. Professor Schratt's group develops AI frameworks for neurological assessment including multimodal dementia diagnosis, voice-based cognitive testing with privacy protection, and digital pathology for kidney disease. Collaborative projects with the Chan Zuckerberg Initiative explore mitochondrial regulation by microRNAs. He teaches molecular neurophysiology and neuroscience courses, supervising doctoral candidates in systems neuroscience approaches.