جست‌وجوی استاد و پژوهشگر

Amir Khajepourمشاهده پروفایل

استاد

• Mechatronics
• Autonomous Vehicle Systems
• Vehicle Control and Safety
• +۴ مورد دیگر

Amir Khajepour is a Professor at the University of Waterloo and holds prestigious positions as a Tier 1 Canada Research Chair in Mechatronics Vehicle Systems and a Senior NSERC/General Motors Industrial Research Chair in Holistic Vehicle Control. His research focuses on autonomous vehicle systems, mechatronics, and advanced control methodologies. Key areas include autonomous driving safety, sensor fusion, vehicle dynamics, and energy management. He leads the Mechatronic Vehicle Systems Lab, pioneering innovations in connected and automated vehicles. His work integrates machine learning, robotics, and mechanical engineering to address challenges in real-world autonomous systems, including path planning, perception reliability, and multi-agent coordination. Recent projects involve 5G-enabled mobility systems, robust tire force estimation, and game-theoretic decision-making frameworks. Khajepour’s contributions span both theoretical advancements and practical implementations, such as the WATonoBus autonomous shuttle technology. Research Highlights: Autonomous vehicle safety, sensor fusion algorithms, adaptive control systems, and energy-efficient powertrains. Grants & Awards: Canada Research Chair, NSERC/GM Industrial Chair, and multiple industry collaborations. Labs & Teams: Directs the Mechatronic Vehicle Systems Lab at the University of Waterloo. His publications emphasize real-world deployment, safety validation, and interdisciplinary approaches to advancing intelligent mobility solutions.

William Melekمشاهده پروفایل

استاد

• Artificial Intelligence
• Intelligent Control
• Mechatronics
• +۱۱ مورد دیگر

William Melek is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He serves as Director of the Laboratory of Computational Intelligence and Automation and RoboHub. His research focuses on intelligent systems, modular robotics, autonomous vehicles, and bioinformatics. He holds a B.A.Sc. in Electrical & Computer Engineering (Zagazig University, 1994), M.Sc. and Ph.D. in Mechanical Engineering (University of Toronto, 1998/2002), and a Post-Doctorate in Computer Science (Ryerson University, 2004). Education: Bachelor's: B.A.Sc in Electrical & Computer Engineering, Zagazig University (1994) Master's: Mechanical Engineering, University of Toronto (1998) Doctorate: Mechanical Engineering, University of Toronto (2002) Post-Doctorate: Computer Science, Ryerson University (2004) His research interests span artificial intelligence, intelligent control, mechatronics, automotive design, and computational intelligence. Recent work includes autonomous vehicle navigation, predictive maintenance in manufacturing, and bioinformatics-driven clinical decision support systems. He teaches courses such as ME 360 (Control Systems), ME 780 (Mechatronics), and MTE 100 (Intro to Mechatronics). Articles from 2023–2025 highlight advancements in autonomous driving decision-making, modular robotics, and 5G-enabled teleoperation systems. His lab develops algorithms for urban autonomous systems and industrial automation. He currently oversees graduate student applications in mechatronics and robotics. Labs/Teams: Laboratory of Computational Intelligence and Automation, RoboHub.

Renata Raidouمشاهده پروفایل

دانشیار

• Medical Visualization
• Visual Analytics
• Uncertainty Visualization
• +۳ مورد دیگر

Renata Raidou is an Associate Professor in Biomedical Visualization and Visual Analytics at the Research Unit of Computer Graphics, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria. She previously held positions at the University of Groningen and TU Wien as a postdoc. Her research focuses on medical visualization, uncertainty visualization, and data physicalization for healthcare applications. Raidou has received prestigious awards including the Dirk Bartz Prize (2017) and EuroVis Young Researcher Award (2022). She coordinates TU Wien's BSc in Digital Health and MSc in Medical Informatics. Education: PhD in Medical Visualization (Eindhoven University of Technology, 2017), MSc in Biomedical Engineering (TU Delft), Diploma in Electrical and Computer Engineering (NTUA). Professional Roles: Editorial Board member of Computer & Graphics , Steering Committee member of EG VCBM, and member of EASAC's AI in Healthcare working group. Research Interests: Medical visualization strategies for P4 medicine, anatomical edutainment through physicalization, and uncertainty-aware visual analytics in radiotherapy. Her work bridges visual computing, machine learning, and medical applications, emphasizing clinical decision support and public health education. Awards: Over 10 awards including Best Paper recognitions at IEEE Vis and EuroVis, and the EuroVis Best PhD Award. Her contributions span visualizing anatomical variability, ensemble data exploration, and interactive medical training tools. Grants & Projects: Leads the Health Virtual Twins project (2024–2028) for personalized stroke management. Active in interdisciplinary collaborations, including the Shonan Meeting on Formalizing Biological Visualization. Labs/Teams: Head of the Visualization Group at TU Wien, developing tools like Vologram (holographic medical data physicalization) and Slice and Dice anatomical crafts. Collaborates on edutainment systems and AI-driven healthcare visualization.

• Computer Vision
• Assistive Technologies
• Healthcare Informatics
• +۳ مورد دیگر

Irene Ballester Campos is a Researcher at TU Wien's Faculty of Informatics, affiliated with the Department of Computer Graphics and Algorithms. Her work focuses on applying computer vision and AI to develop assistive technologies for healthcare contexts, particularly in dementia care and clinical applications. She is involved in the visuAAL project (2020–2026) and previously contributed to the DIANA project (2020–2023). Her research emphasizes privacy-sensitive systems, 3D sensor technologies, and human-centered design for assistive applications. Key areas include dementia behavior monitoring through depth sensors, action recognition in privacy-sensitive scenarios, and ethical implications of assistive systems. She also explores clinical applications such as Parkinson's disease severity estimation through motion analysis. Publications highlight contributions to 3D human pose estimation, dynamic object tracking in robotics, and vision-based solutions for toileting assistance. Her work bridges computer science with healthcare, emphasizing practical deployment in real-life clinical settings.

Ullrich Kötheمشاهده پروفایل

دانشیار

• Machine Learning
• Neural Networks
• Explainable AI
• +۶ مورد دیگر

Prof. Dr. Ullrich Köthe is an Associate Professor and group leader in the Visual Learning Lab Heidelberg at the University of Heidelberg . He focuses on Explainable Machine Learning , leveraging Invertible Neural Networks to enhance transparency and utility in image analysis and medical applications . He also maintains the widely used VIGRA image analysis library. Education: PhD in Informatics, University of Hamburg, 2000 Habilitation in Informatics, University of Hamburg, 2008 His research interests center around machine learning , image analysis , and scientific computing , particularly the development of robust algorithms for medical imaging , computer vision , and life sciences . His work on invertible neural networks and parameter-free segmentation has led to significant advancements in the field. Recent publications highlight his contributions to Bayesian inference , neural network interpretability , and stochastic modeling , with applications ranging from disease outbreak dynamics to connectomics . Key trends include generative models , parameter-free segmentation , and likelihood-free inference . Scientific Awards: DAGM 2003 Main Prize DAGM Best Paper Award 2008 He has supervised numerous Master and Bachelor theses in machine learning and image analysis , with teaching roles in Advanced Machine Learning and Explainable AI . His collaborative research grants include funding from HARMAN International (2024). He leads the Explainable Machine Learning subgroup and has contributed to open-source software projects like ilastik and VIGRA , which are critical tools in bioimage analysis .

Nicolas Charonمشاهده پروفایل

استادیار

• Morphological Shape Analysis
• Medical Imaging
• Computational Anatomy
• +۷ مورد دیگر

Nicolas Charon is an Assistant Professor in the Department of Mathematics at the University of Houston. He holds a PhD in Mathematics from École normale supérieure de Cachan (2013) and completed postdoctoral research at the University of Copenhagen. His research focuses on geometric methods for medical imaging and computational anatomy, including diffeomorphic registration, functional shape analysis, and Riemannian metrics on curves/surfaces. He has been supported by the NSF DMS-1945224 CAREER Award and has developed software tools like fshapesTk , h2metrics , and ShapeGraph_H2match . Key research areas include varifold-based shape registration, metamorphoses of functional shapes, and sparse methods for diffusion MRI compression. Charon has advised three PhD students and contributed to over 50 publications. His work bridges theoretical mathematics with applications in healthcare, including stroke risk assessment via left atrial appendage morphology analysis and 4D human shape synthesis. Recent projects involve scalable frameworks for PDE solution operators, self-supervised learning of human body scans, and data-driven elastic shape analysis with topological constraints. Charon’s interdisciplinary approach integrates geometry, optimization, and machine learning to advance computational anatomy and medical imaging technologies.

Pablo Martinez Rodriguezمشاهده پروفایل

استادیار

• Industrialized Construction
• Robotics and Automation
• Computer-aided Process Planning
• +۴ مورد دیگر

Dr. Pablo Martinez Rodriguez is an Assistant Professor at Northumbria University's Architecture and Built Environment Department. He specializes in multi-disciplinary engineering, focusing on Industry 4.0 integration in low-digitalized sectors like construction and agriculture. His research emphasizes industrialized construction, robotics automation, lean manufacturing, and precision farming. Education: BEng in Electromechanical Engineering (Comillas Pontifical University), MSc in Mechanical Engineering (University of Alberta), and PhD in Civil and Environmental Engineering (University of Alberta). Previously held roles include NSERC post-doctoral fellow and International Visiting Professor at Tecnologico de Monterrey. Research Interests: Industrialized Construction (Modern Methods of Construction), Robotics & Automation, Computer-aided Process Planning, Lean Manufacturing, Waste Management, and Precision Farming Automation. His work addresses challenges in smart safety systems, digital twins, and sustainable construction practices. Key Projects: Developed an IALF-certified learning factory, created ontology-based safety management tools, and advanced aquaponics 4.0 systems. Recent articles highlight digital twin applications, gamified safety training, and AI-driven generative design. Grants & Collaboration: Active in organizing international conferences like the Modular and Offsite Construction Summit. Supervises PhD students and collaborates on projects aligning with UN Sustainable Development Goals, particularly education and sustainable cities. Labs/Teams: Leads the AllFactory transdisciplinary educational facility focusing on aquaponics 4.0 and smart manufacturing systems. Engages in cyber-physical systems research for zero-defect production.

Snehesh Shresthaمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Human-Robot Interaction
• Robotics
• +۴ مورد دیگر

Snehesh Shrestha is a researcher at the University of Maryland College Park (UMD), pursuing a PhD in Computer Science under advisors Prof. Yiannis Aloimonos, Dr. Cornelia Fermuller (UMIACS), Dr. Irina Muresanu (School of Music), and Dr. Ge Gao (iSchool). He is affiliated with the Perception and Robotics Group (PRG) and collaborates with UMD's Culture Lab in Psychology. Currently, he works at NIST developing standards for human-robot interaction (HRI) research. His work bridges AI, robotics, arts, and culture, with a focus on human-centered design, music education, and interpretable HRI systems. Research interests include human-AI interaction, multimodal learning, and ethics-driven robotics. Notable projects involve neuropsychological feedback systems (NeuResonance), violin performance analysis (VioPose), and gamified HRI data collection (CrowdHRI). He advocates for reproducibility and accessibility in robotics research, as seen in 'The Road to Reliable Robots.' His interdisciplinary collaborations span music, psychology, and information science. At NIST, he contributes to HRI guidelines for ethical and transparent human-subject studies. He has published extensively in HRI, AI ethics, and music technology, with a focus on bridging technical and artistic domains.

Robert Willeمشاهده پروفایل

استاد

• Design Automation
• Quantum Computing
• Computer Science
• +۷ مورد دیگر

Prof. Dr. Robert Wille is a Full Professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology and Chief Scientific Officer at the Software Competence Center Hagenberg GmbH . He leads the Chair for Design Automation , focusing on automatic methods for complex system design in conventional and future technologies. Studied Computer Science (Diploma) at the University of Bremen (2002-2006) Doctorate (summa cum laude) from the University of Bremen (2009) His research spans quantum computing , microfluidic biochips , field-coupled nanotechnologies , and reversible circuits , with applications in machine learning , artificial intelligence , and cyber-physical systems . Recent work includes quantum circuit verification, radar-camera fusion, and silicon dangling bond logic optimization. Robert Wille has received prestigious awards such as the ERC Consolidator Grant , Google Research Award , and Distinguished Professor appointment . He serves as Associate Editor for journals like IEEE TCAD and Springer LNCS, and has chaired conferences including DATE and ICCAD.

Federico Thomasمشاهده پروفایل

استاد پژوهشی

• Robotics
• Kinematics
• Distance Geometry
• +۶ مورد دیگر

Federico Thomas is a Professor of Research at the Spanish National Research Council (CSIC), based at the Institut de Robótica i Informàtica Industrial (IRI), affiliated with the Technical University of Catalonia (UPC), Barcelona, Spain. He has held visiting and invited professorships at the University of Massachusetts, Oxford University, École Centrale de Nantes, and the University of Ferrara. Telecommunications Engineering Degree, 1984, UPC Ph.D. in Computer Science, 1988, UPC NATO Postdoctoral Fellow, University of Massachusetts, 1991 His research lies at the intersection of Geometry and Kinematics , with strong applications in Robotics , Computer Vision , and Computer Graphics . He specializes in Distance Geometry and Clifford Algebras , developing mathematical frameworks for solving complex robotic motion and configuration problems. His work enables precise modeling of mechanisms such as lobster-inspired arms and parallel robots. His recent publications (2022–2025) reveal a deep engagement with geometric computation, focusing on rotation matrices, sphere tangents, ellipse intersections, and singularity analysis in parallel robots. These works consistently apply advanced algebraic and geometric methods to practical robotic challenges, demonstrating a trajectory of theoretical rigor with engineering relevance. His scientific honors include the NATO Postdoctoral Fellowship. He has served as an Associate Editor for IEEE Transactions on Robotics (2005–2009, and currently), ASME Journal of Mechanisms and Robotics (2009–2012, and currently), and The International Journal of Mechanics and Control . Federico Thomas was the former director of IRI. He advises students in robotics and geometry, as indicated by the 'Students' section on his homepage. He has not received major grants explicitly listed, but his sustained publication record and editorial roles suggest continuous research support. His 'Art and Science Tapas' initiative reflects an interdisciplinary outreach effort, blending history, art, and science. He leads research activities within the IRI, particularly in computational robotics and geometric methods. His team likely includes collaborators such as J.M. Porta, S. Sarabandi, and B. Bongardt, with whom he co-authors frequently. The 'Kinematics Virtual Library' and 'Tapas' projects suggest an educational and cultural component to his lab’s mission.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +۶ مورد دیگر

Prof. Dr. Didier Stricker is a distinguished Professor of Computer Science at Rhineland-Palatinate University of Technology Kaiserslautern-Landau (RPTU) and serves as Scientific Director and Head of the Augmented Reality Research Department at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern. He leads the Augmented Vision Group, which comprises approximately 30 researchers working across various domains of computer vision and augmented reality. His work bridges academic research with industrial applications through collaborations with major companies including Sony, Google, and John Deere. His educational background includes electrical engineering studies at the Polytechnic Institute of Grenoble and the Technical University of Karlsruhe. He earned his doctorate from the Technical University of Darmstadt in 2002 with a dissertation on "Computer Vision-Based Calibration and Tracking Methods for Augmented Reality Applications." Prof. Stricker's research spans virtual and augmented reality, computer vision, human-computer interaction, cognitive interfaces, and on-body sensor networks. His work focuses on developing practical applications that enhance human capabilities through advanced visual computing technologies. He has pioneered approaches in video and sensor analytics, particularly in creating cognitive interfaces that respond intelligently to user needs and environmental contexts. His recent publications reveal a strong emphasis on 3D scene understanding, real-time processing for augmented reality applications, and the integration of large language models with spatial reasoning capabilities. There's a clear trend toward more sophisticated multimodal approaches that combine vision, language, and spatial understanding to create more natural and intuitive human-computer interactions. Among his notable achievements: Innovation Prize of the German Society of Computer Science (2006) Organized the first IEEE & ACM International Symposium on Mixed and Augmented Reality (ISMAR) in 2002 Member of the ISMAR steering committee from 2000-2007 Multiple best paper and demonstration awards at major conferences Several registered patents in tracking and augmented reality technologies Prof. Stricker has supervised numerous PhD and Master's students through his leadership of the Augmented Vision Group. His research is supported by significant funding from both European and national research organizations, as well as through industrial partnerships. He serves as an expert reviewer for various research funding bodies and contributes to the academic community through editorial roles for journals and conferences in VR/AR and computer vision. The Augmented Vision Group under his direction maintains strong connections with industry partners and participates in numerous collaborative research projects including LUMINOUS, SHARESPACE, I-Nergy, BIONIC, and VIDETE. These projects span applications in language-augmented XR systems, social experiences in hybrid spaces, AI for energy systems, personalized body sensor networks, and 4D scene analysis.

Ranxiao Wangمشاهده پروفایل

استاد

• Emotional Neuroscience
• Cognitive Psychology
• Spatial Cognition
• +۵ مورد دیگر

**Roles & Affiliations**: Professor of Psychology and Beckman Institute for Advanced Science and Technology at the University of Illinois Urbana-Champaign. Holds dual appointments in Psychology and interdisciplinary research through the Beckman Institute. **Education**: PhD from Massachusetts Institute of Technology (MIT). **Research Interests**: Focuses on the neurobiological basis of emotion regulation, cognitive-emotional interactions in psychopathology (anxiety/depression), and spatial cognition. Explores brain lateralization, spatial memory distortions, and higher-dimensional spatial reasoning. Recent work includes human safety perception with UAVs, mind-wandering dynamics, and non-Euclidean spatial learning in virtual environments. Uses virtual reality, behavioral experiments, and computational models to study spatial navigation, attention, and human-computer interaction. **Article Trends**: Research spans spatial cognition (e.g., curved/non-Euclidean spaces), safety perception with drones, cognitive fluctuations in mind-wandering, and cross-modal effects (auditory-visual interactions). Integrates neuroscience and robotics to advance human-robot collaboration models. **Advising & Collaborations**: Supervised over 20 graduate students. Collaborates with experts in robotics (Naira Hovakimyan), vision science (Paul Kwiat), and cognitive neuroscience (Diane Beck, Sepideh Sadaghiani). Projects include Beckman Institute initiatives on spatial cognition and interdisciplinary AI-human interaction. **Labs & Teams**: Leads research at Beckman Institute’s Spatial Cognition and Human-Computer Interaction labs. Active in UIUC’s interdisciplinary programs on robotics, perception, and computational neuroscience.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۳ مورد دیگر

Julia Constanze Hockenmaier is a Professor at the University of Illinois Urbana-Champaign with cross-disciplinary appointments in the Siebel School of Computing and Data Science, Coordinated Science Laboratory, Linguistics Department, Center for Digital Agriculture, and National Center for Supercomputing Applications (NCSA). Her research bridges computational linguistics, artificial intelligence, and domain-specific applications. Her primary research interests include Natural Language Processing, Computational Linguistics, Machine Learning, and Construction Informatics, with notable expertise in parsing, statistical language models, and transformer architectures. Recent work demonstrates innovative applications of large language models in code summarization and construction project management. Analysis of her 2023-2024 publications reveals a strong interdisciplinary focus: 60% target NLP/LLM advancements (code analysis, morphological inflection), while 40% address construction informatics challenges through NLP-based schedule analytics and activity classification. Key trends include bidirectional decoding frameworks, transformer model optimization, and cross-domain adaptation of language technologies. Honors include the prestigious NSF CAREER Award (2011) , recognizing exceptional early-career research potential. Professor Hockenmaier leads externally funded research initiatives including her NSF CAREER project, with collaborative grants spanning computer science and civil engineering domains. She mentors graduate researchers in natural language processing and AI applications, supervising work published in top-tier conferences like EMNLP and COLING. She maintains active research affiliations with the Coordinated Science Laboratory (focusing on AI systems), NCSA (leveraging supercomputing resources), and Center for Digital Agriculture (applying NLP to agricultural data systems), facilitating cross-departmental innovation in computational linguistics.

Ren Ngمشاهده پروفایل

استاد

• Imaging Systems
• Computational Photography
• Optics
• +۵ مورد دیگر

Ren Ng is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He is affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR) and the Visual Computing Lab (VCL). His research focuses on imaging, graphics, computer vision, human vision, and artificial intelligence, with notable contributions to computational photography, light field cameras, and neural radiance fields (NeRF). Ng previously founded and served as CEO of Lytro, Inc., which commercialized his Ph.D. research in light field photography. Ng holds a Ph.D., M.S., and B.S. in Computer Science and Mathematical Sciences from Stanford University. His awards include the ACM Doctoral Dissertation Award, Sloan Research Fellowship, and multiple industry recognitions such as MIT Tech Review's TR35 and Fast Company's 100 Most Creative People in Business. His research spans cutting-edge topics like color vision modeling, neural rendering, and lensless 3D imaging. Recent work explores stimulating photoreceptors for novel color perception and developing frameworks for human brain-based color vision emergence. Ng advises students in advanced imaging and computational techniques, with publications in top venues like Science Advances , ACM Transactions on Graphics , and NeurIPS . Key Contributions: Pioneered the Lytro light field camera technology Co-developed the NeRF framework for 3D scene representation Advanced computational imaging techniques (e.g., DiffuserCam) Grants & Labs: Active in NSF-funded projects and collaborates with institutions like Stanford and UC Berkeley labs. His research impacts fields from medical imaging to consumer electronics.

• Medical Robotics
• Magnetic Actuation Systems
• Soft Robotics
• +۳ مورد دیگر

Salvador Pane is a Professor at ETH Zurich's Department of Mechanical and Process Engineering within the Institute of Robotics and Intelligent Systems. His research focuses on developing advanced medical robotics systems, particularly magnetic navigation technologies for minimally invasive procedures. His research expertise spans Medical Robotics , Magnetic Actuation Systems , and Shape Memory Polymers , with emphasis on targeted drug delivery, catheter navigation, and variable stiffness mechanisms. Key innovations include electromagnetically guided microcatheters, human-scale clinical navigation systems, and programmable magnetic cilia for fluid control. His publication portfolio demonstrates strong trends in translational medical robotics with 8 high-impact publications between 2020-2024 in journals including Advanced Science , Nature Communications , and IEEE Transactions on Robotics . Work frequently addresses clinical implementation challenges in electromagnetic navigation and biomaterial integration. Pane leads collaborative research with significant clinical relevance, evidenced by news coverage of multiple publications. His team has developed clinically ready systems for magnetic particle injection and human-scale navigation, with research picked up by multiple news outlets and demonstrating strong Mendeley readership. Current work centers on the Robotic Materials Lab at ETH Zurich, focusing on electromagnetic navigation systems, variable stiffness catheters, and magnetic swarm control. The lab maintains strong industry and clinical partnerships for translating robotic technologies into medical practice.