Find Academic Supervisors

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +5 more

Jing Zhao is a Professor at Beijing Institute of Technology's School of Automation, Department of Computer Science, with an extensive publication record spanning artificial intelligence, computer vision, medical imaging, and robotics. Their interdisciplinary research bridges theoretical computer science with practical applications in healthcare, agriculture, and engineering. Research interests focus on cutting-edge AI methodologies including deep learning architectures, neural rendering techniques, and multimodal systems. Notable work includes advancements in 3D reconstruction (Gaussian Splatting), medical image analysis for cancer diagnosis, and novel approaches to EEG-based emotion recognition. The research demonstrates strong interdisciplinary connections between computer science and domain-specific applications. Recent publications reveal a consistent trend toward practical AI implementations across diverse fields. Jing Zhao's work shows expertise in adapting theoretical machine learning concepts to solve real-world problems in medical diagnostics, agricultural monitoring, and robotics. The research portfolio demonstrates particular strength in developing novel neural network architectures for specialized applications. As a corresponding author on numerous high-impact publications, Jing Zhao appears to lead a productive research group with collaborations spanning multiple institutions and disciplines. The publication record indicates significant contributions to both theoretical computer science and applied AI solutions across various domains.

Neill CampbellView profile

Professor

• Visual Computing
• Machine Learning
• Computer Vision
• +13 more

Neill Campbell is a Professor of Visual Computing and Machine Learning in the Department of Computer Science at the University of Bath . He is the Director of the Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) and co-director of the Centre for Mathematics and Algorithms for Data (MAD) . He holds an external position as Honorary Associate Professor at University College London and is a Royal Society Industry Fellow. His research spans visual computing, machine learning, and their applications in graphics, vision, and healthcare. His educational background includes a Master of Engineering and a Doctor of Philosophy in Engineering from the University of Cambridge, with his PhD focusing on Automatic 3D Model Acquisition from Uncalibrated Images. Neill Campbell’s research interests lie at the intersection of shape modeling , machine learning , and computer vision . He develops probabilistic and deep learning models to understand and generate visual content, with applications in digital humans, virtual production, biomechanics, and medical imaging. His work emphasizes uncertainty quantification, generative modeling, and alignment learning using Gaussian processes and Bayesian nonparametrics. He leads interdisciplinary projects that bridge computer science and mathematical sciences. The recent publications reflect a strong trend in probabilistic modeling , geometric deep learning , and medical applications . Topics include Gaussian process-based shape modeling, anomaly detection in safety-critical systems, and sparse approximations for geometric representations. His work increasingly integrates theoretical machine learning with real-world applications in health, engineering, and creative industries. Royal Society Industry Fellow Neill Campbell actively supervises PhD students across multiple Centres for Doctoral Training (ART-AI, SAMBa, CDE) and leads significant research grants such as MyWorld (UKRI Strength in Places Fund) and REMODEL (EPSRC). His group collaborates with industry leaders like Rolls-Royce, NVIDIA, Adobe, and DNEG, and he supports student internships and industrial placements. He is also involved in spin-out activities, including contributions to Forceteck Ltd. He leads the Visual Computing Group and is deeply embedded in research centers including CAMERA , MAD , and MyWorld . His team includes postdoctoral researchers and PhD students working on 3D reconstruction, biomechanics, inverse problems, and generative models, fostering a collaborative and interdisciplinary research environment.

Markus GrossView profile

Professor

• Artificial Intelligence
• Machine Learning
• Computer Graphics
• +8 more

Markus Gross is a Professor of Computer Science at ETH Zurich, where he founded the Computer Graphics Laboratory in 1994. He also serves as the Chief Scientist of the Walt Disney Studios and Director of DisneyResearch|Studios, a position he has held since 2008. His work bridges academia and industry, with research that has been applied in Hollywood films, sports broadcasting, and medical applications. Professor Gross received his Master of Science in electrical and computer engineering and his Ph.D. in computer graphics and image analysis from Saarland University in Germany in 1986 and 1989. His research spans multiple domains of computer graphics and visual computing. Early in his career, he pioneered point-based graphics techniques that offered alternatives to traditional triangle-based rendering pipelines. More recently, his work has focused on digital humans, AI characters, and machine learning applications for visual computing. His research has led to significant practical applications, including the Medusa capture system used in Hollywood films, the blue-c immersive telepresence system, and the Liberovision technology now used by major sports broadcasters. Analysis of his recent publications reveals a strong focus on neural rendering techniques, particularly around Gaussian splatting and diffusion models. His work increasingly integrates AI with traditional computer graphics methods, with applications in digital humans, medical visualization, and video processing. Many papers demonstrate practical applications in film production, medical treatment planning, and interactive systems. Professor Gross has received numerous prestigious awards throughout his career: 2024 Eurographics Gold Medal 2021 Steven Anson Coons Award for outstanding creative contributions to computer graphics 2019 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences 2013 Karl Heinz Beckurts-Preis 2013 Konrad-Zuse-Medaille für Informatik 2013 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences 2012 Academy Sci-Tech Oscar award for Wavelet Turbulence Professor Gross has mentored numerous Ph.D. students throughout his career, with 20 Ph.D. students contributing to his blue-c project alone. His research has been supported by significant funding from both academic and industry sources, enabling the creation of multiple startups including Cyfex, Novodex, LiberoVision, Dybuster, and Animatico (acquired by Nvidia in 2022). He leads the Computer Graphics Laboratory at ETH Zurich and DisneyResearch|Studios, fostering collaboration between academic research and practical industry applications. His teams have developed groundbreaking technologies that have impacted film production, sports broadcasting, medical visualization, and educational technology.

Ivan TomasicView profile

Academic

• Mathematical Logic
• Model Theory
• Categorical Logic
• +7 more

Ivan Tomasic is a Reader in Pure Mathematics at the School of Mathematical Sciences, Queen Mary University of London, where he has been a faculty member since 2007. He is affiliated with the Centre for Combinatorics, Algebra and Number Theory, contributing to research in logic and algebraic geometry. His research lies at the intersection of mathematical logic and algebraic geometry, particularly in model theory, categorical logic, topos theory, difference algebra, and differential algebra. Tomasic's long-term programme focuses on developing Relative Algebraic Geometry over a base topos, with applications in dynamics and algebraic structures. His work bridges deep logical frameworks with geometric intuition, advancing foundational theories in difference and differential algebra. His recent publications show a strong trend toward categorical and topos-theoretic methods, especially in generalizing classical algebraic geometry to difference fields. Key themes include Galois stratification, cohomology, definable sets over finite fields, and zeta functions, reflecting a unified vision of logic, geometry, and arithmetic. Tomasic has secured multiple research grants from the EPSRC, including projects on stability in model theory and category theory, cohomology of theories, and model-theoretic views of difference algebra. These grants support his ongoing collaborations, such as with Behrang Noohi, and sustain his research programme. He is involved in a vibrant research environment at Queen Mary, particularly within the Centre for Combinatorics, Algebra and Number Theory, where he contributes to seminars, collaborative research, and mentoring of early-career researchers.

Jasmine Y. MaView profile

Associate Professor

• Equity in Mathematics Education
• Sociocultural Theories of Learning
• Embodied Cognition in Mathematics
• +3 more

Jasmine Y. Ma is an Associate Professor in the Department of Teaching and Learning at New York University’s Steinhardt School of Culture, Education, and Human Development. Her research focuses on equity and justice in mathematics education, emphasizing how marginalized populations engage with mathematical concepts across non-traditional settings like skateparks, archaeological studies, and documentary filmmaking programs. She critiques dominant educational structures that privilege Western mathematics and explores embodied cognition through whole-body learning activities like Walking Scale Geometry. Her work employs ethnographic and design-based methodologies to investigate learning in diverse environments. Current projects include studies of an afterschool documentary filmmaking program and collaborations with art crate design companies. She serves as President of the International Society of the Learning Sciences and is an Executive Editor at Cognition and Instruction . Key research themes include: deconstructing school-centric views of learning, leveraging interdisciplinary methods to understand mathematical activity, and designing inclusive instructional strategies that recognize multiple forms of mathematical knowledge. Her publications span educational anthropology, cognitive science, and sociocultural theory, with a focus on marginalized learners and innovative pedagogical frameworks.

• Computer Vision
• Human-Computer Interaction
• Optical Engineering
• +7 more

Professor Dariusz Sawicki is a faculty member at Warsaw University of Technology's Faculty of Electrical Engineering, affiliated with The Institute of the Theory of Electrical Engineering, Measurement and Information Systems. His research spans computer vision, optical engineering, and human factors with applications in virtual reality and occupational safety. His primary research interests focus on advanced optical systems including ray tracing methodologies, light source characterization, and image processing techniques. Specialized work in glare assessment at outdoor workplaces has established him as an expert in lighting ergonomics, while his development of Semi-Cave virtual reality environments demonstrates interdisciplinary innovation connecting computer graphics with human psychophysiology. Recent publications reveal expanding work in botanical reconstruction, fractal generation, and pandemic-era communication systems. Professor Sawicki has supervised 92 promoted theses and authored 80 publications with significant bibliometric impact (h-index 9 in Scopus). His work includes 1 patent and participation in multiple projects, with research funded through institutional support at Warsaw University of Technology. Current laboratory activities center on the Semi-Cave virtual reality facility for studying audiovisual environment impacts on human performance. 80 Publications with cumulative ministry score of 2,315 92 Supervised theses 1 Patent h-index (Scopus): 9 | h-index (WoS): 8 Total CiteScore: 63.19

• Sculpture
• Environmental Art
• Video Art
• +6 more

Stephanie Smith is a Lecturer in the Sculpture & Environmental Art department at The Glasgow School of Art . Her practice spans sculpture, installation, video art, and interdisciplinary projects often exploring the intersection of art, nature, and digital spaces. She frequently collaborates with Eddie Stewart on large-scale installations and conceptual works. Her research interests include environmental art , conceptual frameworks , and digital exhibitions . Recent projects like The Unseen Masterpiece (2020) and SMITH/STEWART PRESENT TENSE (2024) highlight her focus on site-specific installations and virtual art spaces . Publications such as Grey Gardens (2016) and Sprache / Language (2016) reflect her engagement with art-architecture dialogues and multilingual exhibitions . Smith’s collaborative exhibitions include Re-hang (2017) at Gray’s School of Art and Sharing a View: Contemporary Art from Glasgow (2020/21) in China, where her works Handheld and Round were presented across multiple institutions like Tsinghua University and Guangzhou Academy of Fine Arts.

• Representation theory of algebras
• Algebra
• Triangulated categories
• +4 more

Lidia Angeleri is a Full Professor in the Department of Computer Science at the University of Verona, specializing in Algebra (MATH-02/A). Her academic career spans multiple decades with significant contributions to representation theory of algebras and related fields. Her research interests include: Triangulated categories - studying abstract concepts and methods from homological algebra, including torsion pairs, t-structures, and localization theory Purity in representation theory - examining pure-injective modules, definable subcategories and the Ziegler spectrum Representation theory of algebras - investigating module categories and their derived categories Silting and tilting theory - developing universal methods for comparing and constructing equivalences between different categories Her work has important connections to geometry, topology, data science, and theoretical physics. She has authored approximately sixty publications in international journals and serves on the editorial boards of Journal of Pure and Applied Algebra, Annals of Representation Theory, and Applied Categorical Structures. Professor Angeleri currently leads significant research projects including FIS-2021 and PRIN-2022, with recent projects such as 'FIS - Large views of small phenomena: decompositions, localizations, and representation type - LAVIE' (starting 7/15/24) and 'Structures for Quivers, Algebras and Representations - SQUARE' (starting 9/28/23). Previously, she served as Vice-Rector for International Relations at the University of Verona from 2013 to 2019. She teaches multiple courses including Algebra, Linear Algebra and Elements of Geometry, Homological Algebra, and Methods in Representation Theory for both Bachelor's and Master's degree programs in Applied Mathematics and Mathematics.

Jianfei CaiView profile

Professor

• Computer Vision
• Multimedia
• Visual Computing
• +5 more

Roles and Affiliations: Jianfei Cai is a Professor at Monash University's Faculty of IT, leading the Department of Data Science & AI. Previously, he held roles including Head of the Data Science & AI Department, and was a Full Professor at NTU's School of Computer Science and Engineering. He is a co-recipient of multiple paper awards and an IEEE Fellow. Currently serves as General Chair for ACM Multimedia 2024 and on editorial boards of TPAMI and IJCV. Education: PhD in Electrical Engineering, University of Missouri Columbia (2002) MEng in Electrical Engineering, Southeast University (1997) BEng in Electrical Engineering, Nanjing University of Aeronautics and Astronautics (1994) Research Interests: Focuses on computer vision, deep learning, vision-language systems, 3D imaging, and medical imaging applications. His work spans generative AI, neural scene representation (e.g., Gaussian Splatting), and open-vocabulary semantic segmentation. He has published over 380 papers and led projects in trustworthy AI and 3D vision. Key Contributions: Developed MVSplat (3D Gaussian Splatting from sparse views) Pioneered open-vocabulary object detection via scene graph discovery Advanced diffusion models for multi-sensor fusion and panorama synthesis Awards and Recognition: Monash FIT Dean's Researcher of the Year Award IEEE Fellow ACCV/ICCM/IEEE ICIP paper awards Recipient of Google/Adobe research gifts Grants and Labs: Leading projects on trustworthy generative AI, 3D Gaussian splatting compression, and safe AI Former director of NTU's Data Science & AI Research Center

• Augmented Reality
• Virtual Reality
• Optical See-Through Head-Mounted Displays
• +5 more

Alexander Plopski is an Associate Professor in the Department of Information and Computer Science at Keio University's Graduate School of Science and Technology. His research focuses on advancing augmented reality technologies, particularly optical see-through head-mounted displays, eye tracking systems, and human-computer interaction paradigms for immersive environments. Dr. Plopski's research interests span multiple dimensions of augmented reality systems. He investigates fundamental challenges in optical see-through displays, including depth perception, occlusion handling, and visual comfort. His work on gaze interaction has significantly contributed to our understanding of how eye tracking can enhance AR experiences. He also explores spatial cognition in AR environments, examining how users perceive and remember spatial information when augmented content is present. His research bridges the gap between display technology, human perception, and practical applications across various domains including industrial assembly, music education, and accessibility. Analysis of his recent publications reveals a strong emphasis on improving the visual quality and usability of AR systems. His work addresses critical challenges such as focal modulation, text legibility in out-of-focus conditions, and creating indistinguishable AR experiences. He has also made significant contributions through comprehensive surveys that map the research landscape in gaze interaction and optical see-through displays. Dr. Plopski's collaborative approach is evident through his extensive network of co-authors across multiple institutions. His work demonstrates both theoretical depth and practical impact, with applications spanning from industrial settings to educational contexts.

• Machine Learning
• Computer Vision
• Natural Language Processing
• +3 more

Professor Andreas Geiger leads the Autonomous Vision Group (AVG) at the University of Tübingen , heading the Department of Computer Science and serving as core faculty at the Tübingen AI Center . He is Principal Investigator in the ML in Science cluster of excellence and CRC Robust Vision , while coordinating the ELLIS PhD program . Develops machine learning models for computer vision, NLP, and robotics Focus on 2D/3D representations, geometry/material reconstruction, and robust AI Applications in autonomous vehicles, VR/AR, and document analysis His research has produced hundreds of publications with significant impact, including multiple best paper awards at top venues. The Scholar Inbox platform he co-created revolutionizes academic paper discovery, winning business model awards at Tübingen AI Center spinoff events. Key research areas include: Neural rendering and 3D scene understanding Self-driving perception and planning systems Simulation frameworks for autonomous validation Efficient reinforcement learning architectures Recent awards include: CVPR 2024 Best Paper Sage 10-Year Impact Award 2024 IEEE PAMI Young Researcher Award 2018 Active in CyberValley and ELLIS Institute Tübingen , he maintains strong industry collaborations through initiatives like the ML ⇌ Science Colaboratory . His group's work appears in journals like TPAMI and conferences including SIGGRAPH 2025.

• Transport Meteorology
• Landscape Meteorology
• Cultural Climatology
• +7 more

Professor John Thornes is a Professor of Applied Meteorology at the School of Geography, Earth and Environmental Sciences, University of Birmingham. His research spans multiple interdisciplinary areas where meteorology intersects with human activities and cultural practices. He has established himself as a leading figure in transport meteorology, landscape meteorology, and the commodification of the atmosphere, with significant contributions to both theoretical frameworks and practical applications. Thornes' research interests encompass Cultural Climatology, Atmospheric Management, Road Weather Forecasting, Environmental Art, and Adaptation to Climate Change. His work uniquely bridges scientific meteorology with cultural studies, examining how weather and climate are represented in art (particularly in Constable and Monet's works) and how atmospheric conditions are increasingly commodified through weather derivatives and financial instruments. His research on road weather forecasting has led to practical applications in transportation safety, including the development of the XRWIS system for predicting severe weather impacts on roads and railways. Analysis of his publication record reveals a consistent focus on the intersection of meteorology with transportation systems, cultural representations of weather, and the economic dimensions of atmospheric phenomena. His work demonstrates a progression from technical meteorological studies toward more interdisciplinary explorations of how society interacts with and conceptualizes atmospheric conditions. Thornes has secured significant research funding including a KTP grant for £120k to develop road sensors and a £1.5m EPSRC grant for the CREW (Community Response to Extreme Weather) project. He has successfully translated research into practice through two university spin-off companies: Thermal Mapping International (1984-89) and Entice Technology (2002-06). He has supervised numerous doctoral students including S. Du (Climate Emissions Trading), S. Khan (Monet's London Series), S. Keeling (Public Perception of Weather Forecasts), Sam Randalls (Weather Derivatives), and Lee Chapman (Road Ice Prediction). His leadership extends to international organizations, having served twice as President of the Standing International Road Weather Commission (SIRWEC) and currently serving as Secretary. Thornes maintains active collaborations with industry partners including Campbell Scientific Ltd. and Weather Services International (WSI), where he works to develop OpenRoute weather forecast products for highway authorities. His research on Constable and Monet's paintings continues through collaboration with Jacob Baker, focusing particularly on Monet's 'London Series' depicting London fogs from 1899-1904.

Oliver BaumannView profile

Professor

• Applied and Technical Optics
• Experimental Physics
• Scientific Image Processing
• +3 more

Oliver Baumann serves as Professor of Mathematics and Physics at the Department of Industrial Engineering within the Faculty of Engineering and Computer Science at Hamburg University of Applied Sciences (HAW Hamburg). His office is located in Room 0.17b at Ulmenliet 20, 21033 Hamburg, with office hours held Wednesdays 10:00–11:00 by email appointment. His academic background includes a physics diploma from CAU Kiel, a diploma thesis in applied optics at JGU Mainz, and a doctorate in astronomy from MPIA Heidelberg. Prior to his professorship, he worked as a scientific employee at Carl Zeiss AG in Oberkochen. Baumann's research spans applied and technical optics , experimental physics , and scientific image processing , with emphasis on optical measurement technology and precision mechanical-optical systems. His work bridges theoretical physics with industrial applications in aerospace, medical technology, and optical instrumentation. Key projects include radar system optimization for field mouse detection, fluorescence imaging evaluation in medical contexts, and photovoltaic-heat transport system design. His publications reveal strong focus on optical engineering (75% of works), instrumentation patents (60%), and educational methodologies (20%). Recent trends show increasing specialization in medical optics applications since 2016, alongside consistent contributions to astronomical instrumentation. Graduates' award for particularly dedicated teachers: 'Golden Duck' 2023 Graduates' award for particularly dedicated teachers: 'Golden Duck' 2019 Graduates' award for particularly dedicated teachers: 'Golden Duck' 2018 Graduates' award for particularly dedicated teachers: 'Golden Duck' 2017 Graduates' award for particularly dedicated teachers: 'Golden Duck' 2016 Baumann actively supervises graduate theses while serving as Chairman of the Examination Board for HWI bachelor's and master's programs. He holds multiple institutional roles including BAFöG representative, Deputy member of Faculty Council LS, and DAAD reviewer for Nigeria (PTDF). His professional affiliations include the European Optical Society (EOS), German Society for Applied Optics (DGaO), German Physical Society (DPG), and University Teachers' Association (hlb). His research activities center around precision mechanical-optical systems development, with emphasis on imaging technologies and measurement instrumentation. Current projects focus on optical metrology applications in aerospace and medical technology sectors.

David DownesView profile

Senior Lecturer

• X-ray systems
• image processing
• interaction design
• +4 more

David Downes is a Senior Lecturer at the Nottingham School of Art & Design, Nottingham Trent University, where he teaches scripting for animators, procedural animation, and motion capture applications while supporting students across multiple courses. He actively supervises postgraduate research in his specialized domains. His research centers on X-ray systems and image processing for security applications, interaction design, interactive environments, computational creativity, procedural animation, and motion capture. A sustained focus involves developing X-ray imaging systems for security screening, conducted within the Imaging Science Group led by Prof. Paul Evans. This work bridges engineering, computer science, and creative design to solve real-world security challenges. Downes' recent publications (2023-2024) reveal two dominant research trajectories: advanced X-ray imaging techniques (conical shell beam tomography/diffraction for medical/security applications) and machine learning-driven virtual reality exposure therapy for mental health. His work demonstrates interdisciplinary innovation spanning physics, computer vision, and clinical psychology. Professional recognition includes: Fellow of the Higher Education Academy Downes supervises PhD students including Hogg (2024) on focal construct geometry for X-ray diffraction. His research is funded by Defence and Security Accelerator (DASA), EPSRC, US Department of Homeland Security (DHS), and Cranfield University, with collaborations extending to Roma Patel of The Society of British Theatre Design. Key collaborators: Roma Patel (The Society of British Theatre Design) Primary sponsors: DASA, EPSRC, DHS, Cranfield University As a core member of the Imaging Science Group, Downes contributes to internationally recognized research in security-focused X-ray systems. The group maintains active GitHub repositories and ResearchGate presence, with projects emphasizing human-centered design validated through ergonomics studies and real-world security implementations.

Akihiko ToriiView profile

Assistant Professor

• Computer Vision
• 3D Reconstruction
• Place Recognition
• +6 more

Akihiko Torii is an Assistant Professor (Research Associate) at the Okutomi & Tanaka Lab in Tokyo Institute of Technology. He holds a PhD from Chiba University and completed a postdoctoral fellowship at the Center for Machine Perception (CMP) at Czech Technical University in Prague. His research focuses on computer vision, with expertise in 3D reconstruction, place recognition, localization, and structure from motion. He has contributed to influential datasets like the 24/7 Tokyo, Pittsburgh (Pitts250k), SF Revisited, and InLoc datasets, advancing visual localization and feature matching techniques. **Education and Background:** PhD in Computer Science, Chiba University Postdoctoral Researcher, Czech Technical University (2014–2018) **Research Interests:** His work spans Computer Vision , including 3D Reconstruction , Place Recognition , Feature Matching , and Multi-View Stereo . He emphasizes practical applications such as indoor/outdoor localization under changing conditions. **Awards and Recognition:** 2017: CVPR Outstanding Reviewers Award 2016: IEEE Japan Chapter Young Author Award 2015: Tokyo Tech Young Investigator Award Multiple Best Paper Awards (2013–2014) **Key Projects:** Developed algorithms like Multi-View Inverse Rendering and NetVLAD , and contributed to benchmarking frameworks for visual localization accuracy. His work bridges theoretical advancements and real-world applications in robotics and autonomous systems.