جستجوی استاد راهنمای دانشگاهی

Dr. Zhidong Xiao serves as Principal Academic (Associate Professor) at Bournemouth University's National Centre for Computer Animation within the Faculty of Media and Communication. With over ten years of leadership experience including roles as Programme Leader, Head of Education, and Deputy Head of Department, he drives academic strategy and research innovation in computer animation and digital media. His work bridges technical excellence with creative industry applications through extensive collaborations across the UK and China. Dr. Xiao's educational foundation includes a PhD in Computer Graphics (2010) and postgraduate certificates in Education Practice (2010) and Research Degree Supervision (2011) from Bournemouth University, complemented by a BEng (Hons) in Thermodynamics from Taiyuan University of Technology, China (1994). PhD in Computer Graphics, Bournemouth University (2010) PGCE in Education Practice, Bournemouth University (2010) PGCE in Research Degree Supervision, Bournemouth University (2011) BEng (Hons) in Thermodynamics, Taiyuan University of Technology (1994) His research spans Computer Graphics, Motion Capture, Artificial Intelligence, and Virtual Reality with focus on physics-based simulation, sign language recognition, and motion synthesis. Recent work integrates partial differential equations with machine learning to solve animation challenges in facial realism, deformation simulation, and 3D reconstruction. His interdisciplinary approach connects computer science with creative industries, healthcare applications, and educational technology while advancing core techniques in neural rendering and motion analysis. Analysis of his 15 most recent publications reveals consistent innovation in physics-based animation techniques (40%), motion capture processing (25%), and neural approaches to 3D reconstruction (35%). Key trends include the fusion of analytical physics models with deep learning architectures, development of efficient real-time simulation methods, and expansion into accessibility applications through sign language recognition systems. Scientific recognitions include: Fellow of British Computer Society (2023) Fellow of Higher Education Academy (2011) Best Poster Award at Pacific Graphics 2014 He maintains active peer review roles for EPSRC, ESRC, IEEE Transactions on Multimedia, and ACM SIGGRAPH conferences. Dr. Xiao has supervised seven PhD students to completion while currently guiding Alexandra Sergeeva Alexdottir's research on Phantom Touch phenomena. His grant portfolio demonstrates strong industry-academia collaboration: Principal Investigator Capturing and representing sign language (British Council, 2025) VE Communication Programme (Erasmus+, 2020) Co-Investigator Rehabilitation Enhancement via Motion Capture (BU Fusion Fund, 2013) Cross-Channel Film Lab (Interreg, 2012) Digital Beijing Opera Project (2010) As a core member of Bournemouth's Computer Graphics and Visualisation Research Group and Centre for Digital Entertainment, he leads initiatives in motion capture technology through AccessMocap Studio. His international outreach includes invited lectures across China on computer animation education and visual effects techniques, strengthening global partnerships in creative technology development.

• Computer Graphics
• Motion Capture
• Artificial Intelligence
• +۹ مورد دیگر

Hélder Filipe Oliveira is a Senior Researcher at INESC TEC and an Invited Assistant Professor at the University of Porto's Computer Science Department. He holds a Ph.D. in Electrical and Computer Engineering from FEUP. His roles include leading the Visual Computing and Machine Intelligence Area at INESC TEC and coordinating the Data Science Hub. He has extensive experience in research projects, including leading the LuCaS and MICOS initiatives, and has supervised 6 current PhD students, 1 concluded PhD, and 56 MSc students. Education: B.Sc. (2004), M.Sc. (2008), and Ph.D. (2013) in Electrical and Computer Engineering from FEUP. Research focuses on medical image analysis, bio-image processing, computer vision, and machine learning applications in healthcare. His work includes developing AI models for TBI patient prediction and lung cancer diagnosis, with notable contributions to interpretable deep learning systems. Publications span over 80+ peer-reviewed works, 1 patent, and datasets. He actively participates in academic events, organizing the VISUM summer school and serving as a keynote speaker. Labs/Groups: Visual Computing and Machine Intelligence Area, Breast Research Group, and Centre for Telecommunications and Multimedia.

• Medical Image Analysis
• Bio-image Analysis
• Computer Vision
• +۵ مورد دیگر

Michael Adjeisah is a Research Fellow at Bournemouth University's CfACTs Research Centre, focused on interdisciplinary research in machine learning and artificial intelligence. His work spans computer vision, natural language processing, health informatics, and data science, with applications in cultural heritage technology, low-resource language processing, and medical systems. Notable research areas include Adinkra symbol recognition using deep learning, graph neural networks for classification tasks, and sentiment analysis models leveraging attention mechanisms. He has contributed to advancements in neural machine translation for low-resource languages and blockchain-enabled privacy solutions for electronic health records. Adjeisah's publications reflect a strong emphasis on practical applications of AI, with recent work addressing challenges in spoken digit recognition for Amharic and respiration-based biometric systems. His research often integrates multi-sensor fusion and data augmentation techniques to enhance model performance in real-world scenarios.

• Machine Learning
• Neural Networks
• Computer Vision
• +۳ مورد دیگر

Dr. John Chiverton is a Senior Lecturer at the University of Portsmouth within the Faculty of Technology, School of Electrical and Mechanical Engineering and affiliated with the Institute of Life Sciences and Healthcare and Portsmouth AI and Data Science Centre . He specializes in signal and image processing with applications across biomedical engineering, computer vision, and assistive technologies. Research Interests : Automated 3D Imaging Analysis Physiological Signal Processing (Blood Pressure Forecasting) Computer Vision for Human Activity Recognition Machine Learning in Medical and Industrial Applications Multi-modal Sensor Data Integration Scientific Contributions include 49 research outputs (17 articles, 28 conference contributions) and 15 projects funded by entities like Google and Mitsui Sumitomo Insurance Welfare Foundation . His work spans biomedical imaging, robotics, and smart environment systems. Awards : IEEE Award IPEM Award Collaborations include institutions like University of Surrey, University of Bristol, and cross-disciplinary teams in medical imaging and smart material analysis . He supervises PhD students in areas like 3D Imaging and Physiological Signal Analysis .

• Signal Processing
• Medical Imaging
• Computer Vision
• +۴ مورد دیگر

Aamir Ahmad is a Tenure-track Professor (Flugrobotik) and Deputy Director (Research) at the Institute of Flight Mechanics and Control, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart. He also leads the Robot Perception Group (RPG) at the Max Planck Institute for Intelligent Systems in Tübingen. His research focuses on aerial robotics, multi-robot systems, deep reinforcement learning, formation control, and perception-driven navigation. He leads the Flight Robotics Group (FRG) and Robot Perception Group (RPG), which are part of the Cyber Valley and IMPRS-IS initiatives. His work includes developing autonomous aerial systems for tasks like motion capture, environmental monitoring, and cooperative target tracking. Key projects include AirCap (aerial human motion capture) and GRADE (generating dynamic environments for robotics). Research interests span reinforcement learning for autonomous systems, SLAM algorithms, and bio-inspired robotics. Notable contributions include autonomous multi-rotor landing on moving platforms, viewpoint-driven airship formations, and synthetic data-driven wildlife tracking. Ahmad has secured grants such as the EU H2020-funded DeepField project. He advises PhD students through the IMPRS-IS program and offers postdoc and research positions. His groups collaborate with institutions globally and engage in open-source software development for robotics.

• Aerial Robotics
• Multi-Robot Systems
• Deep Learning
• +۷ مورد دیگر

Dr. Dimitris Tzionas is an Assistant Professor at the University of Amsterdam leading research at the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on modeling human appearance, motion, and interactions within physical environments. His research explores: 3D reconstruction of humans and objects from images/video Modeling whole-body interactions with scenes Developing novel representations for articulated motion Creating realistic digital avatars for AR/VR applications Recent publications demonstrate consistent focus on human-object interaction modeling, 3D reconstruction under challenging conditions, and the development of novel datasets. Work frequently appears in top-tier venues like CVPR, ICCV, and ECCV. Awards & Recognition: Outstanding Reviewer - CVPR 2021 Outstanding Reviewer - CVPR 2023 Best Paper Finalist - CVPR 2022 Current PhD students include George Paschalidis and Dimitrije Antic. Research is supported by grants including BMBF funding for 'Machine Learning for Interacting Human Avatars'. The lab maintains collaborations with MPI-IS Tübingen and develops novel capture systems for human motion analysis.

• Computer Vision
• Computer Graphics
• Machine Learning
• +۲ مورد دیگر

Jan Eric Lenssen is a Senior Researcher at the Max Planck Institute for Informatics leading the Geometric Representation Learning Group , and a Founding Engineer at Kumo.ai . He holds a Dr.-Ing. in Computer Science from TU Dortmund University (2022) and has conducted research internships at Facebook Reality Labs and Nnaisense. Affiliations: ELLIS Unit Faculty Member and Saarland Informatics Campus Fellow Education: PhD under Prof. Heinrich Müller, TU Dortmund (2022) His research focuses on differentiable algorithms , neural fields , and graph-based methods for 3D perception and generative modeling. Key contributions include frameworks like SplineCNN , PyTorch Geometric , and methods for scalable 3D reconstruction, human-object interaction modeling, and relational deep learning. Publications span top venues ( CVPR, ECCV, ICCV, NeurIPS ) with highlights including Best Paper Honorable Mention (ECCV 2022) and Best Paper Award (BIOSIGNALS 2018) . He co-founded the RelBench benchmark for relational database learning and leads development of geometric deep learning tools. Key Labs/Teams: Geometric Representation Learning Group (MPI), Kumo.ai Research Team, and the Computer Vision and Machine Learning department at MPI.

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +۴ مورد دیگر

Dr. Chun-Hao Paul Huang is a research scientist at Adobe Research London, previously a postdoctoral researcher at the Perceiving Systems department of the Max Planck Institute for Intelligent Systems. He holds a Ph.D. from Technische Universität München (TUM) and degrees from National Cheng Kung University (NCKU). His research focuses on 3D visual perception, human body reconstruction, and marker-less motion capture, with contributions to computer vision and machine learning. Notable awards include Best Paper Finalist at CVPR 2022 and a Summa cum Laude doctoral distinction. Education: Ph.D. (TUM, 2016), M.Sc. (NCKU, 2010), B.Sc. (NCKU, 2008) Collaborations: Disney Research Zurich, Microsoft Research Redmond, INRIA Morpheo Team Labs: Perceiving Systems Lab (MPI-IS), CAMP Group (TUM) His work spans 4D modeling, spatio-temporal analysis, and cross-domain applications in medical and augmented reality systems.

• 3D Visual Perception
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Dan Berlin is an Assistant Professor in the Sport Media program at the RTA School of Media, Toronto Metropolitan University. He holds a BJourn from Toronto Met and an MA in Coaching and Athletic Administration from Concordia University Irvine. With 20 years of professional experience, he has worked as a sports analyst, producer, and broadcaster for major networks including CBC, CTV, Sportsnet, TSN, and Yahoo Sports, covering major events like the Olympics, Super Bowls, and UFC events. Education: Master’s in Coaching and Athletic Administration, Concordia University Irvine Bachelor of Journalism, Toronto Metropolitan University Research Focus: Examines emerging technologies' impact on live sports viewing, consumer behavior across multi-platform experiences, and the social implications of integrating sports betting into live broadcasts. Promotes equitable and inclusive learning environments in education. Teaching & Roles: Popular instructor in RTA's Sport Media and Journalism programs, emphasizing foundational skills for lifelong success. Previously taught in both departments. Grants/Awards: No specific grants or awards mentioned. His professional achievements include extensive live production and reporting experience at major events.

• Emerging Technology in Live Sport Experience
• Consumer Behavior in Multi-Platform Media
• Social Impact of Sport Betting Integration
• +۳ مورد دیگر

Yakun Ju is a Lecturer in Computer Science at the University of Leicester's School of Computing and Mathematical Sciences. His research develops AI-driven methods for 3D reconstruction in challenging environments including underwater and medical imaging contexts. Research focuses on photometric stereo techniques combining physics-based vision with deep learning for dense geometry recovery. Applications include ocean exploration, HDR imaging, and spine segmentation for medical assessment. Recent work improves efficiency in text-to-3D generation through Fourier-based neural operators. Key recognitions include national scholarships and best paper awards. He holds multiple patents for deep learning-based 3D reconstruction systems with industrial applications.

• 3D Reconstruction
• Computational Imaging
• Underwater Vision
• +۲ مورد دیگر

Aggelos Pikrakis is an Associate Professor in the Department of Informatics at the University of Piraeus, with research focus on Signal Processing with emphasis on Sound and Voice . He serves as an affiliate member of the Institute for Language and Speech Processing (ILSP). Specializes in machine learning algorithms for audio analysis Expertise in Hidden Markov Models and Bayesian architectures Supervises doctoral research in audio processing and machine learning His work spans music information retrieval, voice pathology classification, and mobility pattern analysis. With over 50 publications and 1150 citations (h-index=16), he has received best paper awards and first place in algorithm competitions . He has participated in research programs funded by GGET and European Union as part of research teams. Scientific Awards Best Paper Award First Place in Algorithm Competition Active on editorial boards (EURASIP Journal on Advances in Signal Processing since 2008) and conference committees, he contributes to advancing audio processing methodologies.

• Machine Learning
• Signal Processing
• Hidden Markov Models
• +۳ مورد دیگر

Rudi Villing is an Associate Professor and Programme Director for Robotics & Intelligent Devices at Maynooth University's Department of Electronic Engineering, Faculty of Science & Engineering. He is actively affiliated with the Hamilton Institute and the Assisting Living and Learning (ALL) Institute at Maynooth University. Dr. Villing holds a first class honours B.Eng. in Electronic Engineering from Dublin City University and a PhD in Engineering from NUI Maynooth. Prior to his academic career, he spent 10 years working in the telecommunications software industry, specializing in Telecommunications Management Networks and software systems architecture. His primary research focuses on autonomous mobile robotics , systems for health and wellbeing , and applications of real-time intelligent systems . With expertise spanning system design, real-time embedded software, machine learning, autonomous behavior, signal processing, communications, and psychoperception, his work bridges theoretical research with practical applications. His recent publications demonstrate strong activity in robot vision, assistive robotics for elderly care, and computational healthcare applications, particularly in Parkinson's disease rehabilitation through the BeatHealth project. Dr. Villing's scientific contributions have been supported by funding from: Science Foundation Ireland Enterprise Ireland Irish Research Council European Commission As Programme Director, he plays a key leadership role in robotics education while maintaining an active research program. His work consistently translates theoretical concepts into practical implementations, particularly evident in his research on gait rehabilitation systems and quality control applications in food engineering. His recent publications show increasing interdisciplinary work at the intersection of robotics, healthcare, and food science. Dr. Villing is deeply involved with the Hamilton Institute and the ALL Institute, contributing to interdisciplinary research initiatives focused on intelligent systems with real-world impact. His laboratory work emphasizes practical robotics applications that address tangible human needs, especially in healthcare contexts where technology can improve quality of life for vulnerable populations.

• autonomous mobile robotics
• systems for health and wellbeing
• applications of real-time intelligent systems
• +۷ مورد دیگر

Pierre-Henri CONZE is an Enseignant-Chercheur (Lecturer-Researcher) at IMT Atlantique, part of the Data Science Department (DSD). His research focuses on medical image segmentation, deep learning applications in healthcare, and AI-driven solutions for clinical decision support. He holds a PhD in Signal and Image Processing from INSA de Rennes (2014) and an HDR (Accreditation to Supervise Research) from Université de Bretagne Occidentale (2024). Roles: Academic researcher, developer of AI tools for medical imaging. Affiliations: IMT Atlantique, LaTIM (Medical Information Processing Lab), collaboration with hospitals like CHRU Brest. Research Interests: Medical image analysis, deep learning for tumor segmentation, longitudinal disease progression prediction, and AI in oncology. His work bridges computer vision techniques with clinical needs, addressing challenges like imperfect annotations, sparse datasets, and multi-modal fusion. Publications: Recent articles focus on liver resection planning, cerebrovascular segmentation, and uncertainty quantification in lung cancer. His work emphasizes practical clinical impact, with applications in treatment response assessment and image quality enhancement. Labs/Teams: Active in LaTIM and collaborates with institutions like the Centre Hospitalier Régional Universitaire de Brest (CHRU Brest). His research often involves interdisciplinary teams combining engineering, medicine, and data science.

• Medical Imaging
• Deep Learning
• Computer Vision
• +۳ مورد دیگر

Dr. Hao Liu is a Researcher in the Department of Tissue Technology and Biofabrication at ETH Zurich's Institute for Biomechanics. His work intersects tissue engineering, biofabrication, and advanced computational techniques such as computer vision and 3D reconstruction. He focuses on interdisciplinary applications, including robotics and neural radiance fields (NeRF) for biomedical and robotic systems. Institution: ETH Zurich Role: Researcher (Staff of Professorship for Tissue Engineering and Biofabrication) Research interests span tissue engineering, biofabrication, and computational methods like 3D reconstruction, visual localization, and neural networks. His recent work emphasizes robust 3D scene understanding, camera pose estimation, and deep learning for multi-view stereo. Publications highlight advancements in relative pose estimation, neural radiance fields, and line-based geometric analysis, contributing to both robotics and biomedical engineering fields. He has no listed scientific awards, but his research demonstrates significant innovation in computational imaging and biofabrication. No advising or grant details are provided in the available texts. His affiliation with the Institute for Biomechanics suggests involvement in labs focused on biomechanical systems and biofabrication technologies.

• Tissue Engineering
• Biofabrication
• Computer Vision
• +۳ مورد دیگر

Monroe Kennedy III is an Assistant Professor of Mechanical Engineering at Stanford University with a courtesy appointment in Computer Science. He directs the Assistive Robotics and Manipulation Lab (ARMLab), focusing on collaborative robotics, human-robot interaction, and assistive technologies. His research integrates machine learning, computer vision, and control theory to enhance robotic autonomy for service tasks requiring dexterity and situational awareness. His primary research areas include robotic perception for dynamic environments, adaptive control systems for human-robot collaboration, and wearable assistive devices. Recent work emphasizes tactile sensing, prosthetic interfaces, and safety in human-robot interaction, with applications in healthcare and rehabilitation. His publications demonstrate strong emphasis on multimodal sensing (visual-tactile fusion), human-centered robotics, and assistive technology validation. Article keywords frequently include rehabilitation engineering, haptic feedback, and robotic learning, showing consistent focus on bridging theoretical robotics with practical human needs. Scientific awards include the NSF CAREER Award for his work on collaborative robotics and multiple fellowships recognizing his contributions to assistive technology development. Mentoring includes doctoral and master's students in robotics and mechanical engineering, with research spanning mobile manipulation, tactile perception, and human-robot teaming. His lab collaborates with clinical partners for translational applications.

• Collaborative Robotics
• Machine Learning
• Computer Vision
• +۴ مورد دیگر