Roger Hersch is a current researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL) . His scholarly work spans disciplines including photonics, optical engineering, and computer graphics, with significant contributions to color imaging and electronic imaging technologies. Affiliation: PH-IC (Physics Section, Institute of Condensed Matter Physics) Units: Photonics Systems Laboratory (LSP), Vision Processing and Robotics Laboratory (IVRL), and others His research focuses on photonic systems , imaging science , and optical engineering , as reflected in his publications in journals like the Journal of Imaging Science and Technology and IEEE Computer Graphics and Applications . While specific article titles are not listed here, his work trends toward interdisciplinary applications in optical engineering and computational imaging. As a prolific academic, he has contributed to over 250 publications, primarily in conference papers and research articles, and holds 24 patents. His roles include collaborations with units such as ISIM (Integrated Systems for Microelectronics) and AVP-R-TTO (Research and Technology Transfer Office).
Federica Arrigoni is an Associate Professor at the Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano (Italy). She holds an MS in Mathematics (2013, University of Milan) and a PhD in Industrial and Information Engineering (2018, University of Udine), where her thesis won awards from CVPL and the University of Udine. Her career spans Junior Researcher at Czech Technical University in Prague (2018-2020), Assistant Professor (RTD-A) at University of Trento (2020-2022), and Tenure-Track Assistant Professor (RTD-B) at Politecnico di Milano (2022-2024). Research Interests focus on geometric problems in 3D Computer Vision, including: Viewing graph solvability via cycle consistency Quantum motion segmentation Rotation synchronization Multi-model fitting Recent publications highlight synchronization algorithms, quantum computing applications, and geometric consistency in computer vision. She was honored with Best Paper Finalist at ICCV 2023 and Best Paper Honorable Mention at ICCV 2021. As Associate Editor for CVIU and reviewer for major conferences (CVPR, ECCV, ICCV), she contributes actively to the academic community. Scientific Recognition : Best Thesis Award, CVPL (2018) Best Thesis Award, University of Udine (2019) Best Paper Honorable Mention, ICCV 2021 Best Paper Finalist, ICCV 2023 Outstanding Reviewer, CVPR 2021
Haoyu Chen is a Tenure-track Assistant Professor at the Center for Machine Vision and Signal Analysis (CMVS), University of Oulu. He is also a co-founder of the AI startup Aitomore and an AI-based restaurant Aitofresh. His research focuses on Machine Learning, Human Behaviour Analysis, Emotion AI, and Adversarial Learning, with particular emphasis on Hybrid Intelligence and human-AI interaction. Dr. Chen received his Ph.D. from the University of Oulu, Finland, where he was advised by Academy Professor Guoying Zhao. During his PhD studies, he visited CEL, TU Delft, the Netherlands. Prior to that, he received his B.E. degree from China University of Geosciences, China, and Master degree from University of Oulu, Finland. Before joining as faculty, he conducted Postdoc research in CMVS, University of Oulu, with projects on Emotion AI (Academy Finland project) and trustworthy AI (Infotech project). His research spans multiple areas of artificial intelligence with a focus on understanding human behavior through AI systems. Dr. Chen's work particularly emphasizes emotion recognition, 3D pose transfer, micro-gesture analysis, and the development of hybrid intelligence systems where humans and AI mutually enhance each other's capabilities. His recent work has increasingly incorporated large language models for multimodal understanding of human emotions and behaviors, with significant publications in ICML, CVPR, and NeurIPS. Academy Research Fellow funding (622k euros), ranked 1st in AI panel ELLIS member IEEE Finland Jt. Chapter SP/CAS Best Paper Award Dr. Chen actively supervises multiple students including PhD candidates, Master's students, and research interns. His teaching includes courses on Affective Computing and Computer Graphics at the University of Oulu. He also organizes workshops and seminars, including the MiGA workshop series on Micro-gesture Analysis for Hidden Emotion Understanding and the HAECU tutorial on Human-AI mutual promotion for emotion and cognition understanding.
Nicolas Courty is a Full Professor in Computer Science at University of Brittany South since 2018, where he leads the Obelix research team at IRISA (Institut de Recherche en Informatique et Systèmes Aléatoires). His research sits at the intersection of machine learning and Earth Observation, with a focus on optimal transport theory and its applications. Dr. Courty obtained his PhD in 2002 from INSA Rennes and his Habilitation à diriger des recherches in 2013, with early work focused on computer graphics and animation. Since 2014, he has developed expertise in optimal transport and its applications to machine learning, becoming a principal investigator in an ANR Chair program on AI (OTTOPIA) in 2020, focusing on applied optimal transport for Remote Sensing. Since 2024, he serves as co-director of Cluster SequoIA, a center of excellence in artificial intelligence research and training in Brittany. His research interests span optimal transport, statistical learning, kernel methods, manifold and geometric approaches to machine learning, with applications to computer graphics, vision, and remote sensing. He is particularly known for pioneering work at the intersection of non-Euclidean geometry and optimal transport, developing novel methods for dimensionality reduction, domain adaptation, and representation learning in complex data spaces. Analysis of his recent publications reveals a strong trend toward geometric machine learning, with increasing focus on non-Euclidean spaces (particularly hyperbolic geometry), sliced optimal transport methods, and applications to remote sensing and neuroscience. His work consistently bridges theoretical advances in optimal transport with practical applications in Earth observation, demonstrating a commitment to both theoretical rigor and real-world impact. Best paper prize at Eurographics 2024 Stanford/Elsevier's Top 2% Scientist Rankings Multiple papers accepted at top conferences including NeurIPS (with oral presentations), ECCV, BMVC, and Eurographics As principal investigator of the ANR Chair program OTTOPIA, Dr. Courty has secured significant research funding for applied optimal transport in Remote Sensing. His leadership extends to directing the Obelix research team at IRISA and co-directing Cluster SequoIA, demonstrating his growing influence in the AI research community in Brittany. He is actively involved in mentoring researchers and fostering collaborations across institutions. Dr. Courty leads the Obelix research team at IRISA, which focuses on the intersection of machine learning and Earth Observation. Under his direction, the team has developed innovative approaches to applying optimal transport theory to remote sensing data, contributing significantly to the field of geospatial AI. The team's work has practical applications in environmental monitoring, land use classification, and climate change analysis.
Rostyslav Hryniv serves as Professor of Applied Mathematics and Statistics at Ukrainian Catholic University (UCU), holding dual leadership roles as Deputy Dean for Research and Head of the Machine Learning Laboratory. His academic profile uniquely bridges rigorous mathematical physics with cutting-edge artificial intelligence applications, reflecting UCU's interdisciplinary research vision. Hryniv's educational foundation includes dual PhDs in Mathematics (1996, 2007) and a higher doctorate (dr hab.) from the Institute of Mathematics of the Polish Academy of Sciences (2009). His postdoctoral trajectory features prestigious appointments as a Humboldt Research Fellow at the University of Bonn (2003-2005) and PIMS Postdoctoral Fellow at the University of Calgary (1998-1999), complemented by teaching roles across institutions in Ukraine, Canada, Poland, and the United States. His research demonstrates a strategic evolution from foundational work in spectral theory and inverse problems to contemporary machine learning. Early career contributions focused on Schrödinger operators with singular potentials, trace formulas, and quantum scattering phenomena. Recent publications (2021-2025) reveal a decisive pivot toward applied AI, including Ukrainian NLP benchmarks, symmetry-based 3D reconstruction, and minimal solvers for computer vision. This transition exemplifies his commitment to leveraging deep mathematical insights for real-world technological challenges. Analysis of his publication trends indicates a clear interdisciplinary trajectory: while maintaining mathematical rigor, his work increasingly addresses Ukrainian language technology and geometric deep learning. The Machine Learning Laboratory under his direction has become a regional hub for AI innovation, particularly in developing resources for low-resource languages and symmetry-aware computer vision systems. Hryniv's scholarly recognition includes: Humboldt Research Fellowship (University of Bonn, 2003-2005) PIMS Postdoctoral Fellowship (University of Calgary, 1998-1999) As Head of UCU's Machine Learning Laboratory, Hryniv leads research initiatives spanning Ukrainian NLP, 3D vision, and quantum machine learning. The lab's recent focus on symmetry-based algorithms and Ukrainian language resources positions it at the forefront of culturally contextual AI development in Eastern Europe, while maintaining connections to his foundational work in mathematical physics through quantum-inspired computing approaches.
Nuria Oliver, PhD is a pioneering computer scientist and ACM Fellow , recognized as the first female Spanish computer scientist to achieve both ACM Distinguished Scientist and IEEE Fellow status. Current affiliations include Microsoft Research and former roles at MIT Media Lab. First female Spanish ACM Fellow IEEE Fellow Academia Europaea member Her research spans human behavior modeling , intelligent user interfaces , and mobile computing , with notable work in: Wearable context-aware systems (DyPERS, HealthGear) Music-adaptive exercise platforms (MPTrain, TripleBeat) Social network analysis (information propagation, community link modeling) Computer vision interfaces (LAFTER facial expression recognition) Scientific achievements include: 41 patents 15+ years of continuous multimodal systems research Recognized for LAFTER system (2000 paper) She actively promotes technology accessibility through: Media collaborations Technical/non-technical keynotes STEM outreach for girls
Peter Kiefer is a Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering, specifically within the Institute for Cartography and Geoinformation. He leads the geoGAZElab research group since 2011 and has established himself as a prominent researcher in eye tracking applications for spatial decision-making. His work bridges geography, computer science, and human factors with a focus on creating cognition-aware systems. Dr. Kiefer's research spans multiple domains with a consistent focus on how eye tracking technology can enhance spatial decision situations. His primary interests include gaze-based interaction with maps, location-based services, mobile interfaces, and aviation applications. He has pioneered work in intention recognition from gaze patterns, gaze-adaptive interfaces, and the application of eye tracking in outdoor environments. His research aims to make information systems cognition-aware by inferring users' cognitive states and adapting interfaces accordingly. Analyzing his recent publications reveals strong trends toward practical applications of eye tracking in real-world scenarios, particularly in aviation safety and spatial decision-making. His work increasingly integrates machine learning with gaze data to create intelligent systems that can predict user needs and adapt interfaces dynamically. The research shows a clear progression from theoretical foundations to applied solutions in domains like weather visualization for pilots, 3D sketch mapping, and unobtrusive interaction techniques. Dr. Kiefer has been actively involved in numerous research projects as Principal Investigator or key contributor, including IGAMaps (Swiss National Science Foundation), PEGGASUS (EU Horizon 2020), EFDISA (Federal Office of Civil Aviation), and FRS 2 (National Research Foundation Singapore). These projects demonstrate his ability to secure competitive funding and lead interdisciplinary research teams across international boundaries. As an educator, Dr. Kiefer teaches Mobile GIS and Location-Based Services for Geomatics Master students, GIS I for Environmental Engineers, and contributes to courses on Mobile GIS, Human-Computer Interaction in GIS, and GIS III. He also participates in continuing education programs including the Certificate of Advanced Studies on Spatial Information Systems and the Master of Advanced Studies on Mobility of the Future. His teaching is deeply integrated with his research, particularly through the geoGAZElab where students gain hands-on experience with cutting-edge eye tracking technologies. The geoGAZElab under Dr. Kiefer's leadership serves as a hub for innovative research at the intersection of geography, computer science, and cognitive science. The lab has developed specialized tools and methodologies for outdoor eye tracking, gaze-based map interaction, and aviation interface design. The lab's work has significant implications for improving spatial decision-making across multiple domains including transportation, urban planning, and emergency response.
Christina Tsalicoglou is a Postdoctoral Researcher at the ETH AI Center , affiliated with the Advanced Interactive Technologies Lab and Computational Robotics Lab . Her work bridges computer science and physical simulation for augmented reality applications. She earned her Ph.D. at ETH Zurich from the Institute of Fluid Dynamics , developing 3D fluid flow reconstruction methods. During her doctoral studies, she contributed to Google Zurich's generative Text-to-3D project. Current research focuses on learning material properties from image sequences Develops physics simulation techniques for AR environments Applications span digital humans, animation, and measurement technologies Her recent publication Gaussian Garments (2025) demonstrates simulation-ready clothing reconstruction from multi-view video, combining 3D modeling and photorealistic appearance capture for augmented reality applications. She collaborates with leading researchers including Michael J. Black and Bernhard Thomaszewski , and welcomes students interested in Semester/Master projects.
Fabrizio Pece is a postdoctoral researcher at ETH Zurich , affiliated with the Advanced Interactive Technologies Lab under the Institute of Intelligent Interactive Systems . Prior to this, he completed his PhD (2010-2014) and MSc (2009) at University College London in the Virtual Environment and Computer Graphics group under Prof. Jan Kautz. He holds a BSc in Computer Science from Università degli Studi di Roma Torvergata (2008) and interned at Disney Research Zurich (2010) supervised by Prof. Wojciech Matusik. His research spans Human-Computer Interaction (HCI) , Computer Vision , and Machine Learning , focusing on Virtual/Augmented Reality , Interactive Systems , and Computational UI Design . His work integrates novel hardware with data-driven methods to explore digital interaction trends. Recent publications highlight expertise in 3D motion infilling , digital ink editing , wearable haptics , and deformable input devices . He has received prestigious awards including Honorable Mentions at UIST 2017 and CHI 2013 , SNF Grant funding , and ETH Postdoctoral Fellowship (Marie Curie Co-Fund). Teaching experience across ETH Zurich (User Interface Engineering, ML for Interactive Systems) and UCL (Computer Graphics, Multimedia Computing) Supervised multiple BSc/MSc thesis students including Adrian Spurr, Ralph Aeschimann, and Manuel Kaufmann Active in academic service as a reviewer for ACM CHI, SIGGRAPH, and IEEE ISMAR
Prof. Hans-Peter Hutter is a Professor of Computer Science at the ZHAW School of Engineering, specializing in Deep Learning-based Automatic Speech Recognition, Conversational User Interfaces, and Human-Centered Computing. He leads the Human-Centered Computing research group at InIT/ZHAW and has held this position since 2005. His work focuses on accessibility technologies, mobile usability, and inclusive design for visually impaired users. Education: Dr. sc. techn. ETH in Computer Engineering (ETH Zurich, 1996) Dipl. El.-Ing. ETH in Electrical Engineering (ETH Zurich, 1986) Research Interests: Advancing accessibility in digital systems (e.g., accessible PDFs, navigation aids for visually impaired users) Speech recognition and dialogue systems Mobile application design principles Service engineering and platform development His recent work emphasizes multimodal interaction, accessible document remediation, and SLAM systems for navigation assistance. Projects: Leading the InCrowd-VI dataset project for indoor navigation Developing MathNet for mathematical expression recognition Creating accessible tourism services in Lake Constance region Grants & Labs: Active in EU-funded and industry collaborations, leading the InIT Institute founded in 2002. Collaborates with organizations like SwissICT and ACM.
Anastasia Remizova is a Doctoral Assistant at the Lab for Statistical Mechanics of Inference in Large Systems (SMILS) within the School of Computer and Communication Sciences (IC) at EPFL. She is concurrently enrolled in the Doctoral Program in Computer and Communication Sciences . Additionally, she serves as Treasurer of the Association des Étudiants Russophones . Her research interests revolve around Machine Learning , Computer Vision , and Statistical Mechanics , focusing on topics like stochastic gradient dynamics, image inpainting, and adversarial learning. Recent publications highlight contributions to test risk analysis in weak feature scenarios and resolution-robust image restoration techniques. While no scientific awards are explicitly mentioned, her work demonstrates engagement with cutting-edge interdisciplinary research at the intersection of inference algorithms and large-scale systems. She is affiliated with the SMILS lab, where her doctoral research likely intersects theoretical and applied aspects of statistical mechanics in modern AI systems.
Dr. Jing Ren is affiliated with the Department of Computer Science at ETH Zürich, holding a role within the Professorship for Computer Science. Their research focuses on computational geometry, 3D reconstruction, and computer graphics, with notable contributions to shape analysis, non-rigid matching, and fabric modeling. Dr. Ren’s work bridges theoretical advancements with practical applications in textile design, architectural modeling, and medical imaging. They collaborate extensively on projects involving functional maps, optimization algorithms, and geometric morphometrics. Key research interests include: Non-rigid shape correspondence and matching Computational modeling of woven fabrics and textiles 3D face and building reconstruction techniques Efficient spectral and discrete optimization methods Recent publications (2022–2024) emphasize innovations in fabric parameterization, Gaussian noise distribution, and rethinking 3D face reconstruction benchmarks. Their work often employs machine learning and functional map frameworks to solve geometric problems across disciplines. Laboratory and team affiliations are not explicitly detailed in the provided materials, but their research aligns with ETH Zürich’s broader initiatives in computer science and engineering. No grants or advising activities are specified in the current data.
Roles & Affiliations: PD Dr. Alexander Ilic is a Lecturer at the Department of Computer Science and Executive Director of the ETH AI Center at ETH Zürich. He co-founded the ETH AI Center and previously led Magic Leap Switzerland, focusing on R&D in Computer Vision and Advanced Photonics. He holds a PhD from ETH Zurich and a habilitation from the University of St. Gallen. Education: PhD in Computer Science, ETH Zurich Habilitation in Entrepreneurship, University of St. Gallen MSc in Computer Science, TU Munich Research Interests: Alexander’s work spans Artificial Intelligence, Entrepreneurship, and Technology Investing. He pioneered AI-driven start-ups like Dacuda (acquired by Magic Leap) and developed cutting-edge sensors and imaging systems. His research emphasizes real-time systems, computer vision applications, and wearable technology. Notable Achievements: Co-founder of Dacuda and Magic Leap Switzerland 两次获得“Entrepreneur of the Year”（2011年和2012年） Swiss Economic Award Over 50+ patents in imaging, AR, and sensor technology Courses Taught: Data Science Lab Technology Investing Patenting Digital Innovations Technology and Entrepreneurship Labs & Leadership: Leads the ETH AI Center, driving AI innovation and interdisciplinary projects. His teams focus on applied AI in real-time systems and cross-reality devices.
Dr. Ndaona Chokani is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich. Their research focuses on aerothermodynamics, mechanical engineering, and process engineering, with a recent emphasis on interdisciplinary applications in computer vision and image processing. Affiliated with the Professur f. Aerothermodynamik, their work spans theoretical and applied domains. While explicit educational background details are not provided, their academic career includes contributions to fields such as fluid dynamics and process systems engineering. Research interests are inferred from departmental affiliation and recent publications, emphasizing computational methods in mechanical systems and image quality assessment. Recent publications highlight work in perceptual quality metrics for images and videos, immersive systems (VR/360 content), and machine learning applications in 3D pose estimation and generative models. Key areas include diffusion models for low-light imaging, spatial-temporal geometric networks, and benchmarking frameworks for image harmonization. No awards or grants are explicitly listed in the provided text. Their research often involves collaborations on datasets like Salient360! and tools for gaze data analysis in 3D environments. Future work appears to focus on improving perceptual metrics and expanding applications in healthcare and immersive technologies.
Dr. Yi-Chi Liao is a Lecturer in the Department of Computer Science at ETH Zürich, specializing in intelligent interactive systems. Their research focuses on human-robot interaction, wearable technology, and optimization techniques for user interface design. Key areas include developing datasets for naturalistic handover behaviors with robotic limbs, human-in-the-loop optimization methods, and computational workflows for designing input devices. Research Interests: Explores the intersection of robotics, machine learning, and human-centered design. Recent work emphasizes Bayesian optimization techniques, affordance theory, and tactile feedback systems. Projects like the 3HANDS dataset and ThirdHand wearable robotic arm demonstrate innovation in human augmentation and interaction design. Advising: Supervises doctoral student Peizhuo Li in the D-INFK program. Research outputs span 2015–2025, with notable contributions to haptic interfaces, multi-objective optimization, and wearable computing. Active in conferences and journals addressing HCI, robotics, and design automation.
