جست‌وجوی استاد و پژوهشگر

Nan Yuمشاهده پروفایل

مدرس ارشد

• Precision Engineering
• Plasma Technologies
• Additive Manufacturing
• +۳ مورد دیگر

Dr. Nan Yu is a Senior Lecturer/Associate Professor at the University of Edinburgh's School of Engineering, serving as Deputy Director of the MSc Digital Design and Manufacture program. He holds visiting appointments at University College Dublin (2021-2026) and Osaka University (2022-2024). Dr. Yu's expertise spans precision manufacturing, plasma technologies, and additive manufacturing, with over £1M in grant funding as PI, 50+ peer-reviewed publications, and multiple awards including the Marie Curie Fellowship (2018-2020) and Royal Academy of Engineering Industrial Fellowship (2023-2024). He earned a PhD in Precision Engineering (Cranfield University, 2017), MSc in Mechanical Manufacturing (Harbin, 2013), and BSc in Mechanical Engineering (Harbin, 2011). His professional qualifications include Fellowships from the Royal Society of Art (2022) and Higher Education Academy (2023), alongside memberships in the European Society for Precision Engineering and CIRP. Research focuses on plasma-based precision machining, additive manufacturing sustainability, and digital twin frameworks. Key contributions include innovations in plasma polishing for optics, UAV swarm strategies, and edge computing sensors. Teaching includes courses on digital manufacturing, metrology, and mechanical design projects. He chairs the 12th CIRP Global Web Conference (2024) and has delivered 10 invited/keynote talks globally. His work emphasizes interdisciplinary collaboration, bridging advanced manufacturing with emerging technologies.

Helge Rhodinمشاهده پروفایل

استاد

• 3D Computer Vision
• Machine Learning
• Computer Graphics
• +۳ مورد دیگر

Helge Rhodin is a full professor at Bielefeld University (since March 2024) and an affiliate at the University of British Columbia (UBC). His research focuses on advancing 3D computer vision, machine learning, and computer graphics to enable non-intrusive human-computer interaction, particularly in augmented reality (AR) and virtual reality (VR) environments. He previously held positions as an Assistant Professor at UBC, a postdoctoral researcher at EPFL, and a PhD candidate at the Max-Planck-Institute for Informatics under Christian Theobalt. Education & Career: PhD in Computer Science, Max-Planck-Institute for Informatics (2016) Postdoctoral Researcher, EPFL (2016–2020) Assistant Professor, UBC (2020–2024) Full Professor, Bielefeld University (2024–present) Research Interests: Rhodin’s work spans 3D human pose estimation, neural rendering, AR/VR applications, and generative models. Key contributions include real-time motion capture systems (e.g., XNect), self-supervised learning frameworks, and synthetic biomarker development for movement disorders. Publications: His work has been published at top venues like CVPR, ICCV, and SIGGRAPH, with notable achievements like the Best Paper Award at CRV 2023 and an IEEE VR Honorable Mention in 2019. Research trends emphasize human-centric computer vision and interdisciplinary applications in healthcare and sports analytics. Awards & Recognition: Best Paper Award at CRV 2023 IEEE VR Best Journal Paper Honorable Mention (2019) Advising & Labs: He leads a multidisciplinary team at Bielefeld, previously mentoring over 30 students at UBC. His group focuses on developing open-source tools and frameworks for 3D vision and AR. Current research directions include mirror-aware neural humans and scalable neural rendering techniques.

Siddhartha Dattaمشاهده پروفایل

پژوهشگر ارشد

• Distributed Machine Learning
• Model Adaptation
• Cybersecurity
• +۴ مورد دیگر

Siddhartha Datta is a Researcher at the University of Oxford's Department of Computer Science, specializing in distributed machine learning and adaptive systems. His research develops end-to-end solutions for model training, security, and deployment. Key research areas include: Adaptive learning algorithms for dynamic environments Defense mechanisms against adversarial attacks Human-centered AI interfaces and tools Cross-reality systems blending digital/physical spaces Efficient model compression techniques Current projects investigate prompt engineering for generative models, online learning under data drift, and 3D object detection refinement. His work combines theoretical frameworks with practical implementations, resulting in tools like GreaseTerminator for digital sovereignty and DeepObfusCode for source protection. Datta has collaborated with Google and Cornell University during his doctoral studies. His open-source contributions include neurocogpy (ECoG processing) and Polysemy Word Tagging Tool, demonstrating commitment to accessible research tools.

Gabriele Petersمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Vision
• Computational Neuroscience
• +۵ مورد دیگر

Prof. Dr. Gabriele Peters is a Professor of Computer Science and Chair for Human-Computer Interaction at FernUniversität in Hagen since 2010. She previously held a Research Professor position and led the Visual Computing Group at Dortmund University of Applied Sciences (2007-2010) and served as Visiting Professor at Caltech's Computational Vision Group (2004, 2005). Her research spans computer vision, computational neuroscience, cognitive systems, and new media art.

Martina Peuserمشاهده پروفایل

استاد

• Agile Business Management and Organizational Structures
• Project Management and Agile Methodologies
• Marketing Management and Digital Transformation
• +۲ مورد دیگر

Professor Martina Peuser serves as Professor of General Business Administration with specialization in Organization and Project Management at Leibniz University of Applied Sciences in Hannover, where she also heads the Business Administration program. With over a decade of academic leadership since 2014, she has established herself as a prominent figure in business education and applied research. Education Background: Diplom-Ökonomin in Business Administration and Economics, University of Hannover (2002) Doctorate (Dr. rer. pol.) from University of Hannover with dissertation on "Competency-Oriented Brand Cooperations of Energy Suppliers in the B2B Sector" (2007) International Business Administration studies at Maastricht University (1999-2000) Industrial Management apprenticeship at Stadtwerke Hannover AG (1995-1998) Her research focuses on three interconnected domains: Agile Business Management and Organizational Structures , examining how companies can develop flexible frameworks for digital transformation; Project Management and Agile Methodologies , particularly in complex organizational contexts; and Marketing Management and Digital Transformation , with special attention to energy sector applications. Her work consistently bridges theoretical frameworks with practical business applications, demonstrated through numerous industry collaborations. Analysis of her recent publications reveals a clear trajectory toward practical applications of agile methodologies across diverse sectors. Her 2022-2024 work shows increasing focus on generational workforce dynamics, digital signage optimization in retail, and decision-making patterns across international contexts. The consistent theme across her publication history is the adaptation of traditional business frameworks to digital and agile environments, with particular emphasis on energy, retail, and manufacturing sectors. Professional Recognition: Professional Scrum Master I certification (2020) Longstanding jury membership for Startup Competition at hannoverimpuls GmbH (2017-present) Former member of the Presidential Council of the German Project Management Association (GPM) (2017-2019) Professor Peuser actively bridges academia and industry through her extensive program management activities and student support initiatives. Her research projects frequently involve direct collaboration with major German corporations including E.ON, Continental AG, and Deutsche Messe AG. She has developed specialized curricula in agile project management and digital marketing that directly respond to industry needs, particularly in the energy and retail sectors. Her leadership extends to program development for both dual-study and full-time business administration tracks. While not explicitly mentioning dedicated laboratories, her work demonstrates strong connections to industry innovation ecosystems through her extensive project management activities and corporate collaborations. Her research approach emphasizes practical application within real business contexts rather than isolated laboratory settings.

Lindsay Sohمشاهده پروفایل

دانشیار

• Sustainability
• Green Solvents
• Biomass Processing
• +۳ مورد دیگر

Lindsay Soh is an Associate Professor of Chemical and Biomolecular Engineering and Department Head at Lafayette College. Her research focuses on sustainability, green solvents, biomass processing, and bio-based materials. She holds a Ph.D. from Yale University and a B.S. from UC Berkeley. Her research emphasizes reducing environmental impact through solvent optimization, recyclable solvents, and novel bio-based materials. She explores applications in biofuel production, birch bark valorization, and CO₂-mediated processes. Her work bridges academic research with undergraduate mentorship, emphasizing hands-on student involvement in engineering solutions for sustainability challenges. Dr. Soh’s teaching philosophy prioritizes foundational chemical engineering education and student engagement, reflecting her commitment to mentoring. She has collaborated on NSF-funded projects advancing green chemistry and biorefinery technologies. Her lab investigates solvent systems, biopolymer synthesis, and CO₂ process intensification for biodiesel production. She leads Lafayette’s Chemical and Biomolecular Engineering department, fostering innovation and sustainability in curricula and research. Her outreach includes K-12 education initiatives on energy sustainability through partnerships like the Nurture Nature Center. Key research themes include solvent lifecycle analysis, bio-based thermoset development, and scalable biomass conversion methods. Her work aims to balance industrial feasibility with environmental stewardship in chemical engineering processes.

Juan A. Fraireمشاهده پروفایل

استاد مهمان

• Space Networking
• Deep-Space Informatics
• Satellite Communications
• +۴ مورد دیگر

Dr. Juan A. Fraire is a researcher at INRIA (France) and serves as a guest professor at Saarland University (Germany) and CONICET-UNC (Argentina). His core research focuses on near-Earth and deep-space networking, with over 100 publications in top journals and conferences. He co-founded and chairs the Space-Terrestrial Internetworking Workshop (STINT) and collaborates with space agencies (NASA, ESA, CONAE) and companies (D3TN, Skyloom). Key projects include STEREO (ANR PRCE coordinator), MISSION (MSCA RISE national coordinator), and AI4LFNM (ESA ITT coordinator). His work spans non-terrestrial networks (NTN), satellite IoT, and interplanetary routing. Research interests emphasize scalable space networking protocols, delay-tolerant networks (DTN), and optical/satellite communication systems. He leads initiatives in autonomous laser link scheduling for Mars exploration, constellation design for global IoT coverage, and hybrid RF/optical terminals for improved pointing accuracy. Over a decade of funding includes European and national grants, focusing on network emulation, edge computing orchestration, and resilient space communication. Dr. Fraire supervises multiple PhD candidates, co-supervising with experts like Prof. H. Hermanns and Prof. H. Rivano. His advising emphasizes interdisciplinary approaches to space informatics challenges. Recent work explores AI-driven congestion control, LoRaWAN scalability for direct-to-satellite IoT, and integrated space-terrestrial cloud latency optimization.

• Spectral Shape Analysis
• 3D Computer Vision
• Geometric Deep Learning
• +۴ مورد دیگر

Riccardo Marin is a Postdoctoral Researcher at the Technical University of Munich (TUM) within the Computer Vision Group. His research focuses on Spectral Shape Analysis, Geometric Deep Learning, and 3D Human Modeling. He holds affiliations with ELLIS Society and is an alumni of the Alexander von Humboldt Foundation and Marie Skłodowska-Curie Actions. Marin's work bridges computational geometry and deep learning, addressing challenges in 3D human registration (NICP), avatar creation (Human-3Diffusion), and neural surface modeling (NSF). He has contributed to open-source tools for spectral shape analysis and maintains active GitHub repositories showcasing his research implementations. His research interests span 3D reconstruction, neural fields, and implicit representations, with applications in virtual humans and human-object interaction analysis. Marin's recent work emphasizes scalable registration pipelines and diffusion models for 3D generation. Awards: ELLIS Member, Alexander von Humboldt Alumni, Marie Skłodowska-Curie Fellow Key Contributions: NICP, Human-3Diffusion, NSF framework Education: PhD background (implied from postdoc status), involvement in a Spectral Shape Analysis course at University of Verona

Nashid Alamمشاهده پروفایل

مدرس

• Medical Imaging
• Machine Learning
• Computer Science
• +۴ مورد دیگر

Nashid Alam is an Honorary Lecturer in the Department of Computer Science at Aberystwyth University. His research focuses on medical imaging, particularly breast cancer detection through automated analysis of mammograms. He specializes in machine learning techniques like convolutional neural networks, ensemble learning, and graph topological features to classify microcalcification clusters and improve diagnostic accuracy. Alam's work contributes to UN Sustainable Development Goals related to health and well-being (SDG 3). His research spans topics including automatic segmentation of microcalcifications, 3D modeling of breast tomosynthesis data, and interpretable deep learning models for mass classification in mammography. He has collaborated on international workshops and conferences, such as the International Workshop on Breast Imaging (IWBI) and Medical Image Understanding and Analysis (MIUA). His research has been published in journals like Knowledge-Based Systems and Journal of Imaging, with notable attention to open-access contributions. Alam completed his doctoral thesis titled 'Classification of Mammographic Microcalcification Clusters' under supervision at Aberystwyth University. His studies emphasize improving early detection of breast cancer through advanced computational methods.

• 3D Computer Animation
• Virtual Human Modelling
• Physics-Based Animation
• +۳ مورد دیگر

Professor Jian Jun Zhang is a leading academic in 3D Computer Animation at the National Centre for Computer Animation (NCCA) , Bournemouth University. He has held academic positions at institutions including University of Bristol , University of Newcastle upon Tyne , Chongqing University , Queen's University Belfast , and Brunel University . Research focus: Physics-based animation , Virtual human modelling , Medical visualisation , and Conversational AI Funding: £10 million+ grants from EPSRC , AHRC , EU FP7 , and EU Horizon 2020 Co-founder: Centre for Digital Entertainment (CDE) with Professor Phil Willis Recent publications emphasize 3D reconstruction , SPH simulation , and Transformer-based architectures for graphics and medical data. He received the CGI Outstanding Career Award (2021) . His work bridges computational mathematics and real-time visual systems , impacting virtual reality , train collision dynamics , and character animation through partial differential equation (PDE) modelling and machine learning integration.

Krassimir Dotchevمشاهده پروفایل

مدرس ارشد

• Mechanical Engineering
• Additive Manufacturing
• CAD/CAM Systems
• +۳ مورد دیگر

Dr. Krassimir Dotchev is a Senior Lecturer in Mechanical Engineering Design and CAD/CAM/CAE at the University of Portsmouth's School of Electrical and Mechanical Engineering within the Faculty of Technology. He specializes in teaching Engineering Design, CAD/CAM systems, Computer-Aided Engineering, and Advanced Modelling. His research focuses on Additive Manufacturing, CAD/CAM systems, Rapid Product Development, and Manufacturing Processes. Key areas include laser sintering, powder bed fusion, and the application of these technologies in filtration systems and automotive engineering. Dr. Dotchev has contributed to 11 peer-reviewed articles since 2001, with notable work on polyamide powder recycling, laser sintering processes, and additive manufacturing planning. He collaborates on projects like the 'KBS for electronic component transport tapes' funded by the Technology Strategy Board. He is affiliated with the Portsmouth Centre for Advanced Materials and Manufacturing and contributes to the UN Sustainable Development Goals through his research in sustainable manufacturing and material efficiency.

Boris S. Pervanمشاهده پروفایل

استاد

• GNSS Integrity Monitoring
• Anti-Spoofing Technologies
• Inertial Navigation Systems
• +۲ مورد دیگر

Dr. Boris S. Pervan is Professor of Mechanical and Aerospace Engineering at Illinois Institute of Technology's Armour College of Engineering, where he holds the Frank Gunsaulus Faculty Fellow position and directs the CARNATIONS research center. Education: Ph.D. in Aeronautics and Astronautics from Stanford University (1996) M.S. in Aeronautics from California Institute of Technology (1987) B.S. in Aerospace Engineering from University of Notre Dame (1986) His research develops assured navigation technologies for transportation systems, focusing on GNSS integrity monitoring, spoofing/jamming resistance, and multi-sensor fusion for autonomous vehicles. Current projects address resilient positioning for driverless cars and aircraft through USDOT-funded initiatives. Publications demonstrate leadership in navigation security, with recent advances in INS monitoring against spoofing, lidar integrity verification, and interference-resistant signal processing. Research consistently bridges theoretical innovation with real-world validation in urban environments. Awards highlight exceptional contributions: Johannes Kepler Award (2022) AIAA Associate Fellow ION Fellow Multiple best paper awards from IEEE and ION Guggenheim Fellowship He leads the $10M CARNATIONS UTC developing anti-spoofing technologies for transportation infrastructure. Professional memberships include IEEE, AIAA, and Institute of Navigation where he influences technical standards.

• Computer Animation
• Virtual Reality
• Physics Based Modeling
• +۸ مورد دیگر

Professor Jian Chang is a leading academic at Bournemouth University with over 15 years of research experience in computer animation. He works at the National Centre for Computer Animation (NCCA), recognized as the UK's No.1 educational and research base for computer animation. His affiliation spans multiple research projects and collaborations with international institutions, NHS surgeons, and organizations like RNLI. His research interests focus on physics based modelling (deformation & fluid), motion synthesis, virtual reality (surgery simulation), and novel HCI (eye tracking, gesture control and haptic). He actively exploits computer animation techniques for cross-disciplinary applications, resulting in significant international research collaborations. His work bridges computer science, engineering, and medical fields through innovative virtual reality applications. Professor Chang's recent publications (2021-2024) demonstrate a strong focus on physics-based fluid simulation, facial animation techniques, surgical instruction generation, and advanced rendering methods. His work shows a consistent trajectory toward more sophisticated physics modeling, particularly in fluid dynamics using SPH methods, and expanding applications in medical training and virtual reality environments. International Travel Grant (TG091783) from The Royal Society (2009) FP7 MC-IIF project 'AniM' - 623883 (Principal Investigator) FP7 MC-IRSES project 'AniNex' - 612627 (Chief Scientist) FP7 funded 'Dr Inventor' project - 611383 (€2.65M) InterReg VA France (Channel) England investment of €5.3M Professor Chang has secured substantial funding from diverse sources including the Royal Society, EU FP7, InterReg VA France (Channel) England, and HEIF. He has taken project management and supervision roles in prestigious EU-funded research projects. His research has directly contributed to innovative developments like the 'virtual surgery theatre' with NHS surgeons and 'virtual lifeboat launching' with RNLI, demonstrating significant cross-sectoral impact potential. His work bridges academic research with practical applications in healthcare, heritage preservation, and maritime safety.

Scott Budgeمشاهده پروفایل

دانشیار

• 3D Image Reconstruction
• LiDAR Technology
• Signal Processing
• +۲ مورد دیگر

Scott Budge is an Associate Professor in the Department of Electrical and Computer Engineering at Utah State University. His research develops methods for 3D scene reconstruction using fused LiDAR and imagery technologies. Research focuses on texel imaging techniques that combine lidar and digital photography for applications in remote sensing, obstacle detection, and 3D visualization. Recent work includes dynamic visualization systems and automatic registration techniques for multi-sensor data. Budge teaches courses in signals/systems and digital image processing, earning teaching recognition including the 2012 Outstanding Teacher of the Year award. He mentors graduate students working on sensor fusion and scene reconstruction projects.

• Autonomous Systems
• Robotics
• Computer Vision
• +۵ مورد دیگر

Asanka Perera is a Lecturer in Mechatronic Engineering at the University of Southern Queensland. His research focuses on robotics, autonomous systems, computer vision, and adversarial learning. He is affiliated with the Centre for Agricultural Engineering and the Centre for Future Materials, and holds an ORCID ID: https://orcid.org/0000-0003-4021-3943. Education: BScEEEng, University of Peradeniya (2008) MScience Industrial Automation, Moratuwa University (2015) PhD, University of South Australia (2020) Professional Memberships: Engineers Australia, Australian Computer Society (ACS), IEEE, Australian Association of Uncrewed Systems (AAUS) His research interests span autonomous vehicles, field robotics, intelligent robotics, and computer vision applications. He has supervised doctoral and master's students on topics like swarm robot localization, adversarial machine learning, and biomedical robotics. His work includes developing algorithms for robust perception in autonomous systems and non-invasive medical monitoring using drones and thermal imaging. Key contributions include reviews on UAV-UGV collaboration, adversarial robustness in LiDAR systems, and biomimetic navigation techniques inspired by celestial orientation. His research bridges robotics, computer vision, and healthcare technologies, emphasizing real-world applications in autonomous systems and medical diagnostics.