جست‌وجوی استاد و پژوهشگر

Ekrem Fatih Yilmazerمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Rendering
• Scientific Visualization
• +۳ مورد دیگر

Ekrem Fatih Yilmazer is a Doctoral Assistant and PhD student at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the Realistic Graphics Lab (RGL) in the School of Computer and Communication Sciences . His position is active under the Institute of Computer Science (IINFCOM), and he is enrolled in the Doctoral Program in Computer and Communication Sciences (EDIC). Institution: École Polytechnique Fédérale de Lausanne (EPFL) School: School of Computer and Communication Sciences (IC) Department: Institute of Computer Science (IINFCOM) Lab: Realistic Graphics Lab (RGL) Status: Doctoral Assistant (Staff), PhD Student (EDIC) His research is centered in computer graphics, with a focus on realistic image synthesis, rendering techniques, and visual computing. The Realistic Graphics Lab at EPFL is known for its work in physically based rendering, light transport simulation, and computational imaging, indicating his involvement in advanced visual simulation and graphics algorithms. No publications are currently listed in the provided text, so no trends can be inferred at this time. There are no scientific awards mentioned in the provided information. As a doctoral assistant, Ekrem is likely involved in research projects funded by EPFL or collaborative grants, though specific funding sources are not disclosed. He may also contribute to academic mentoring within his lab, although no formal advisees are listed. His dual role supports both research and academic training within a leading computer science institution. He is a member of the Realistic Graphics Lab (RGL) at EPFL, a research group focused on advancing the state-of-the-art in image synthesis, rendering, and visual content creation using computational methods.

• Data Management
• Big Data Systems
• Knowledge Graphs
• +۱۲ مورد دیگر

Philippe Cudré-Mauroux is a Full Professor in the Department of Computer Science at the University of Fribourg, affiliated with the Faculty of Science and Medicine. His research spans data management, big data systems, knowledge graphs, semantic web, and human-AI collaboration. His primary research interests include Data Management , Big Data Systems , Knowledge Graphs , Time Series Analytics , Database Systems , Human-AI Collaboration , and Machine Learning for Data Cleaning . His work integrates theoretical database research with practical applications in smart cities, social media, and healthcare analytics. The recent publications reflect a strong trend toward knowledge graph embeddings , large language models for data quality , time series benchmarking , and human-in-the-loop systems . His research combines symbolic and neural methods, emphasizing schema awareness, explainability, and real-world deployment. He actively supervises numerous PhD and Master’s students and collaborates widely across institutions. His group contributes to open-source tools and benchmarking frameworks for database and AI systems.

• Augmented Reality
• Eye Tracking
• Mixed Reality
• +۴ مورد دیگر

Dr. Kenan Bektas is a researcher at the University of St.Gallen, focusing on Augmented Reality , Eye Tracking , and Context-Aware Systems . His work bridges Mixed Reality and Human-Computer Interaction , with a particular emphasis on gaze-enabled interfaces, object identification, and activity recognition. University of St.Gallen His research explores how Augmented Reality can enhance cognitive offloading and improve user performance. He develops systems like NeighboAR and GEAR , which leverage gaze data and machine learning for object retrieval and activity recognition. Key article trends include: Integration of Eye Tracking with AR/MR systems Development of Context-Aware Interfaces Investigations into Responsible Personalization and privacy in MR Applications in Industrial Processes and remote living (Telelife) His work often involves interdisciplinary collaborations with researchers such as Simon Mayer and Jannis Rene Strecker, and has been published in venues including ACM, PLOS ONE, and Frontiers.

Corentin Dumeryمشاهده پروفایل

پژوهشگر

• Computer Vision
• Computer Graphics
• 3D Reconstruction
• +۴ مورد دیگر

Corentin Dumery is a Doctoral Assistant at École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the Computer Vision Laboratory (CVLAB) and Machine Learning and Optimization Laboratory (MLO) within the School of Computer and Communication Sciences . His research bridges Computer Vision and Computer Graphics , focusing on 3D scene reconstruction, garment modeling, and neural rendering techniques. Previously, he interned at Meta Redmond , worked at CEA Paris-Saclay on polycube mapping, and was a visiting researcher at ETH Zurich under Prof. Olga Sorkine-Hornung . Corentin holds dual MSc degrees in Computer Science from National University of Singapore (NUS) and Télécom Paris . His work emphasizes 3D content creation for AR/VR Diffusion models for garment reconstruction Neural radiance field optimization Polycube mapping for hexahedral meshing His recent publications (2022–2025) span top venues like SIGGRAPH , ICCV , and CVPR , addressing challenges in 3D Gaussian splatting, view-consistent NeRF training, and single-view garment recovery. He also contributes to academic service as an Outstanding Reviewer at CVPR25 and co-organizes workshops like OpenSUN3D . At EPFL, he serves as Head Teaching Assistant for courses CS433 Machine Learning (2023–2024) and CS442 Computer Vision (2023–2024). Additionally, he is the VP/Treasurer of EPIC , EPFL's computer science PhD association.

• Photonics
• Optical Engineering
• Computer Graphics
• +۳ مورد دیگر

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 Arrigoniمشاهده پروفایل

دانشیار

• 3D Computer Vision
• Geometric Synchronization
• Motion Segmentation
• +۵ مورد دیگر

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

Nicolas Courtyمشاهده پروفایل

استاد

• Optimal transport
• Statistical learning
• Machine learning
• +۷ مورد دیگر

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.

• Machine Learning
• Data Science
• Mathematical Physics
• +۳ مورد دیگر

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.

Christina Tsalicoglouمشاهده پروفایل

پژوهشگر

• Computer Science
• Computational Robotics
• Computer Graphics
• +۷ مورد دیگر

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.

• Automatic Speech Recognition
• Conversational User Interfaces
• Human-Computer Interaction
• +۶ مورد دیگر

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.

• Machine Learning
• Computer Vision
• Statistical Mechanics
• +۳ مورد دیگر

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.

• Computer Graphics
• Geometry Processing
• 3D Reconstruction
• +۳ مورد دیگر

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.

Alexander Ilicمشاهده پروفایل

مدرس

• Artificial Intelligence
• Computer Vision
• Entrepreneurship
• +۳ مورد دیگر

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.

• Aerothermodynamics
• Mechanical Engineering
• Process Engineering
• +۳ مورد دیگر

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.

• Robotics
• Human-Computer Interaction
• Machine Learning
• +۳ مورد دیگر

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.