جست‌وجوی استاد و پژوهشگر

Plamen Maldzhanskiمشاهده پروفایل

استاد

• Photogrammetry
• Digital Photogrammetry
• Image Processing
• +۵ مورد دیگر

Prof. Dr. Eng. Plamen Maldzhanski is a Professor in the Department of Photogrammetry and Cartography at the Faculty of Geodesy, University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria. He maintains office P228 and holds reception hours on Wednesday from 12-13. His academic career spans several decades, with significant contributions to photogrammetry, digital image processing, and geospatial technologies. Education Engineer in Geodesy, Photogrammetry and Cartography (1985), UACEG-Sofia Computer Engineering (1993), Technical University of Sofia Doctor of Photogrammetry and Remote Sensing Methods (1998), UACEG-Sofia Professor of Photogrammetry and Remote Sensing Methods (2012), UACEG-Sofia Research Interests Prof. Maldzhanski's research spans multiple areas within photogrammetry and geospatial technologies. His primary focus is on developing advanced methods for image processing and 3D modeling. He has made significant contributions to both theoretical frameworks and practical applications of photogrammetric technologies, particularly in architectural documentation and cultural heritage preservation. His expertise encompasses: Analytical and digital photogrammetry Close-range photogrammetry and laser scanning 3D modeling of surfaces and architectural structures Digital image processing and analysis Integration of photogrammetric data with GIS systems Development of specialized software for geodetic applications Publication Trends Prof. Maldzhanski's publication record demonstrates a clear evolution from traditional photogrammetric methods toward digital and computational approaches. His recent work (2017-2023) focuses heavily on photorealistic modeling, close-range photogrammetry applications for cultural heritage documentation, and integration of modern technologies like Google Maps API with geospatial data. His publications reveal a strong emphasis on practical applications in architectural documentation, precision measurement, and digital preservation of cultural sites. Awards and Professional Recognition Member of the Union of Geodesists and Land Surveyors Licensed professional for cadastral work (License No. 157) Full design capability license from KIIP Academic Leadership and Grants Prof. Maldzhanski has held significant administrative positions including Vice-Dean for Academic Affairs at the Geodesy Faculty and Vice-Rector for International Cooperation and Postgraduate Qualification. He has participated in multiple research projects funded by academic and government institutions, focusing on satellite imagery applications, architectural photogrammetry for cultural heritage documentation, and development of spatial data infrastructure. His grant activities include: "Използване на космически снимки за целите на регионалното и териториално планиране" (2007) "Възможности за създаване и обновяване на навигационни карти" (2008) "Използване на архитектурната фотограметрия при документиране паметници на културата" (2009) "Академичен център 'Дистанционни изследвания и мобилна инфраструктура на пространствени данни'" (2009) Software Development and Technical Contributions Prof. Maldzhanski has developed several significant software packages that bridge theoretical photogrammetry with practical applications: "PHOTO" software package for analytical photo processing and digital mapping "Geodesy" software for geodetic tasks, network adjustment, and terrain modeling "TEST_RGO" program for testing geodetic measurements according to Regulation 19 of the Cadastre Agency

• Virtual Reality
• Extended Reality
• Virtual Worlds
• +۷ مورد دیگر

Dr. Eleftherios Anastasovitis serves as a PostDoc Researcher at the Information Technologies Institute (CERTH-ITI), Adjunct Professor in Virtual Reality at the University of the Aegean's Department of Product and Systems Design Engineering, and visiting Adjunct Professor in Human-Computer Interaction at the International Hellenic University's M.Sc Strategic Product Design program. He is also Founder and CEO of Pyrseia Informatics since 2012. His academic credentials include: PhD in XR, Virtual Worlds, Storyliving, and Virtual Cultural Heritage from University of Macedonia (2024) M.Sc in Cultural Informatics and Communication from University of the Aegean (2014) M.Ed in Adult Education from Hellenic Open University (2017) B.Sc in Informatics from Aristotle University of Thessaloniki (2005) His research integrates immersive technologies for cultural heritage preservation and education, specializing in the Antikythera Mechanism through Storyliving Virtual Worlds. He develops XR applications for training using Serious Games and 3D Graphics, with strong emphasis on user-centered design principles in Human-Computer Interaction. Dr. Anastasovitis contributes to the academic community as Lead Guest Editor for MDPI Electronics' Special Issue "Shaping Human-Centered Virtual Worlds" and holds memberships in the Europeana Network Association and EuroXR Association's Advisory Board. As Technical Project Manager at CERTH-ITI since 2016, he executes EU and national research initiatives while leading XR development at Pyrseia Informatics. No formal advisees are documented in current records.

Bartosz von Rymon Lipinskiمشاهده پروفایل

استاد

• Media Informatics
• Game Engineering
• Interactive Computer Graphics
• +۲ مورد دیگر

Prof. Dr. Bartosz von Rymon Lipinski is a Professor of Computer Science specializing in Media Informatics at Nuremberg Technical University (since February 2014). He holds a doctorate in medical 3D visualization from the Technical University of Munich and a Computer Science degree (with Business Administration minor) from the University of Bonn. Previously, he served as a Professor for Game Engineering at Media Design Munich University of Applied Sciences and worked in software industry roles. Research Focus: His work spans interactive storytelling technologies , image and point-based computer graphics , and applied artificial intelligence , with applications in game development and interactive media systems. Teaching: Courses include Fundamentals of Computer Game Development 3D Real-Time Rendering C++ for C# Developers Software Engineering Programming II Contact: HW.203 Office | bartosz.vonrymonlipinski@th-nuernberg.de | +49 (0)911 5880 - 1756

Florian Werzinskiمشاهده پروفایل

استاد

• Visual Effects
• Computer Graphics
• 3D Animation
• +۳ مورد دیگر

Florian Werzinski serves as Professor at Flensburg University of Applied Sciences within the School of Information and Communication. He holds dual roles as faculty member and scientific employee at the Irgendwas-mit-Medien-Zentrum Flensburg (IMMZ), teaching Film & Media Arts and Media Informatics programs with office hours during lecture periods. His research centers on innovative Visual Effects methodologies, notably pioneering texture-projection techniques for high-resolution architectural modeling as demonstrated in the Louvre project. This work integrates 3D animation, motion capture, and real-time rendering within film production pipelines. Professor Werzinski received the Caligari Award 2014 for Amour Fou 3D , where he executed multidisciplinary roles from direction to compositing. His creative portfolio spans commercial projects ( Luigi's Pizzaride , Lada Niva Edition ) and student exhibitions like the 2023 Danewerk digital showcase. At IMMZ, he leads hands-on training in concept art, character/vehicle design, and pipeline development. Current initiatives include stereoscopic 3D production (24/48 FPS) and student portfolio development via Artstation, reflecting his commitment to bridging academic theory with industry practice.

Jonathan R. Senningمشاهده پروفایل

استاد

• High-performance computing
• Computational mathematics
• Queueing theory
• +۳ مورد دیگر

Jonathan R. Senning is a Professor of Mathematics and Computer Science at Gordon College, working within the Department of Mathematics and Computer Science in the School of Science, Technology and Health. He has maintained a dual focus on mathematical theory and practical computer applications throughout his academic career. Dr. Senning earned his educational credentials from prestigious institutions: Ph.D. in Applied Mathematics, University of Virginia, 1992 M.A.M. in Applied Mathematics, University of Virginia, 1989 B.S. in Physics and Mathematics, Gordon College, 1985 His research spans multiple interconnected domains with a strong emphasis on computational approaches. Senning has developed significant expertise in high-performance computing applications for solving complex mathematical problems, particularly in queueing network theory. His work bridges theoretical mathematics with practical computing solutions, creating tools that enable more efficient problem-solving in computational mathematics. He has maintained active membership in the Association of Christians in the Mathematical Sciences since 1993 and the Mathematical Association of America. Dr. Senning's scholarly output reveals a consistent trajectory from foundational mathematical research toward increasingly sophisticated computational implementations. His publications demonstrate expertise spanning theoretical queueing network analysis, high-performance computing implementations, and educational technology applications. The evolution of his work shows a progression from pure mathematical research to practical software development that makes complex mathematical concepts accessible. His professional activity includes significant software development projects that translate theoretical concepts into practical tools: QNetDP - for computing optimal policies in queueing networks QNet Approximator - NSF-funded project for computing cost bounds Numerical Solution of First Order Differential Equations - web-based educational tool LAVA (Linear Algebra Visualization Assistant) - interactive linear algebra learning platform As an educator, Senning has taught a comprehensive range of courses from introductory programming and calculus to advanced topics in machine learning and high-performance computing, demonstrating his ability to connect foundational mathematical concepts with cutting-edge computational applications.

James A Walkerمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Quantum Computing
• +۳ مورد دیگر

Dr. James A Walker is a Senior Lecturer in the Department of Computer Science at the University of York, UK. His primary affiliation is with the Artificial Intelligence research group within the department. He holds a permanent academic position and is actively involved in research and teaching. His research interests span multiple areas including artificial intelligence, machine learning, quantum computing, esports analytics, and constraint programming. He has contributed to high-impact studies on topics such as Bayesian frameworks for neural networks, SAT encoding techniques, and quantum error correction. Dr. Walker's work often intersects interdisciplinary fields, blending theoretical computer science with practical applications in gaming, healthcare, and aerospace. Department: Department of Computer Science University: University of York Research Group: Artificial Intelligence His recent publications highlight a focus on cutting-edge technologies such as quantum computing, esports strategy analysis, and advanced machine learning methodologies. He has consistently published in top-tier venues, demonstrating expertise in both foundational and applied computer science research. Dr. Walker's work on real-time 3D tracking and quantum phase correction underscores his ability to tackle complex technical challenges with innovative solutions. His contributions to esports analytics and game design parameters reflect an interest in applying AI techniques to dynamic, competitive environments.

Arthur Leskمشاهده پروفایل

استاد

• Genomics
• Structural Biology
• Protein Structure and Evolution
• +۳ مورد دیگر

Arthur Lesk is a Professor of Biology and Biochemistry and Molecular Biology at Pennsylvania State University, affiliated with the BMMB Graduate Program and Bioinformatics initiatives. His research focuses on genomics, protein structure evolution, and biological network analysis, with notable contributions to mammoth genome sequencing and alternative splicing studies. Collaborations include work with Profs. Miller and Schuster on comparative genomics of mammoths and elephants. Lesk has authored influential textbooks like Introduction to Protein Science and pioneered methods for protein folding pattern classification. His lab explores structural bioinformatics, regulatory network motifs, and systems-level biological organization, bridging computational and experimental approaches. Research Interests: Genomics: Comparative analysis of protein-coding genes, alternative splicing consequences, and evolutionary pressures Structural Biology: Protein folding patterns, evolutionary conservation, and functional implications of structural changes Biological Networks: Regulatory network motif connectivity, transcription pathways, and hierarchical network assembly principles Key Projects: Decoding mammoth/elephant genome differences to study protein evolution Developing MUSTANG structural alignment algorithms Mapping network motif combinations in yeast regulatory systems Advising & Grants: While no specific students are listed, Lesk’s work has been supported by grants enabling large-scale genomic projects and computational infrastructure development. His lab contributes to the UCSC Genome Browser and structural bioinformatics tools. Labs/Teams: Active in cross-disciplinary collaborations within PSU’s Biochemistry department and international genome sequencing consortia.

• Texture synthesis
• Deep learning
• Medical image segmentation
• +۳ مورد دیگر

Florian Allender is a PhD Student/Doctoral Candidate and ATER Lecturer in Computer Science at the University of Strasbourg. He is affiliated with the ICube Laboratory (UMR 7357) and the IGG Team (Geometric and Graphics Computing). His research focuses on texture synthesis, deep learning, and medical image segmentation. He holds a Master's degree in Computer Science (specializing in Images, Signals, and Data Sciences) and an engineering degree from Télécom Physique Strasbourg. Teaching responsibilities include courses such as Algorithms and Programming, Signal Processing, and Development Techniques. His academic work is conducted within the ICube laboratory's SDC and IGG teams, supervised by Jean-Michel Dischler, Cédric Wemmert, and Rémi Allègre. Current research publications are forthcoming, but his interests emphasize interdisciplinary applications of machine learning and computer vision in medical imaging. He contributes to the Laboratory of Engineering, Computer Science, and Imaging Sciences (ICube), focusing on projects related to 3D geometry, visualization, and graphics computing.

Kevin Verbeekمشاهده پروفایل

استادیار

• Computational Geometry
• Graph Drawing
• Information Visualization
• +۳ مورد دیگر

Kevin Verbeek is an Assistant Professor in the Applied Geometric Algorithms group at Eindhoven University of Technology (TU/e), affiliated with the EAISI Foundational research institute. His research focuses on computational geometry, information visualization, and algorithms for cartographic challenges. He holds a PhD from TU/e (2012) and conducted postdoctoral research at UC Santa Barbara (2012–2014). He coordinates the TU/e Honors Academy's 'Competitive Programming and Problem Solving' track and is a member of the Eindhoven Young Academy of Engineering. Education: PhD in Applied Geometric Algorithms, TU Eindhoven (2012) Postdoctoral Researcher, UC Santa Barbara (2012–2014) Research Interests: Algorithmic stability for dynamic data visualization Geometric algorithms for social networks and cartography Topological data analysis and computational topology Braided river network modeling Key Projects: NWO Veni Award-funded project on stable geometric algorithms (2015–present) GLAMMap: Interactive geo-visualization for cultural heritage metadata Teaching & Outreach: Coordinator of Honors tracks in Competitive Programming Instructor for courses like 'Heuristic Algorithms' and 'Computer Science Research Project' Awards: NWO Veni Award for 'Stable Geometric Algorithms' (2015) Labs/Teams: Active in EAISI Foundational, focusing on algorithmic spatial data analysis and foundational AI research.

• Artificial Intelligence
• Optimization
• Machine Learning
• +۳ مورد دیگر

Sebastian Pokutta is a Professor at Technische Universität Berlin, Vice President at Zuse Institute Berlin (ZIB), and Chair of the Cluster of Excellence MATH+ and MODAL. His research focuses on artificial intelligence, optimization, and machine learning, with emphasis on algorithmic development, decision-making systems, and real-world applications in areas like satellite data analysis, quantum computing, and combinatorial mathematics. He leads a research group exploring AI-driven methodologies and their interdisciplinary applications. He holds academic positions including leadership roles in major institutions and has contributed to numerous high-impact publications in optimization, machine learning, and quantum computing. His work has been recognized with awards such as the Science Prize of the Association for Pediatric Orthopedics (VKO). Pokutta actively engages in academic outreach, delivering talks on optimization and AI, and contributes to open-source projects like the FrankWolfe.jl library. His research bridges theoretical foundations with practical implementations, addressing challenges in computational efficiency, mathematical modeling, and AI ethics.

Carl Vondrickمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Robotics
• +۵ مورد دیگر

Carl Vondrick is an Associate Professor of Computer Science at Columbia University. He leads the Perception and Robotics research group focused on creating intelligent systems that understand and interact with the physical world through vision and robotics. His work emphasizes interpretable models, multimodal learning, and robustness. Education: PhD in Computer Science from MIT (2017), advised by Antonio Torralba BS in Computer Science from UC Irvine (2011), advised by Deva Ramanan Research Interests: Generative models for physical intelligence Interpretable machine learning Robotics and embodied AI Large-scale video understanding AI for scientific discovery Article Trends: Recent work focuses on neuro-symbolic methods , generative AI safety , and robot learning . Notable contributions include DIFFusion for subtle visual learning, DiSciPLE for scientific discovery, and differentiable robot rendering frameworks. Awards: 2024 PAMI Young Researcher Award 2021 NSF CAREER Award Advising & Grants: Current PhD students (9) and former advisees (4). Active grants from NSF, DARPA, Toyota Research Institute, and Amazon. Program chairs for ICLR 2025/2026. Labs/Teams: Leads Columbia's Perception Lab and collaborates with industry partners like Google, Cruise, and TRI.

Derek Nowrouzezahraiمشاهده پروفایل

استاد

• Computer Graphics
• Machine Learning
• Physics-based Simulation
• +۶ مورد دیگر

Derek Nowrouzezahrai is a Full Professor at McGill University's Faculty of Engineering, holding positions in the Department of Electrical & Computer Engineering, Desautels Faculty of Management (Associate), and School of Computer Science (Associate). He holds prestigious chairs including the CIFAR AI Chair and Mila-Ubisoft AI Chair. His research focuses on simulating physics for machine learning, Monte Carlo methods, light transport editing, and fluid simulation. Recent work includes neural implicit models, differentiable rendering, and reinforcement learning applications. He has supervised over 40 students across PhD, MSc, and undergraduate levels. Awards include the Best Paper Honourable Mention and CGF Cover Image Competition wins. His courses cover numerical methods, realistic image synthesis, and advanced computer graphics. Research contributions span 150+ publications with a focus on rendering, simulation, and AI integration. Research Interests: Physics-Based Simulation : Fluid dynamics, light transport, and material modeling Machine Learning Integration : Neural rendering, inverse problems, and generative models Real-Time Graphics : Efficient algorithms for global illumination and interactive visualization Multi-Agent Systems : Reinforcement learning for coordinated behavior Scientific Achievements: Developed scalable rendering techniques like Virtual Ray Lights and gradient-domain photon estimation Pioneered differentiable simulation frameworks for system identification Contributed to open-source datasets like Kubric for computer vision research Lab & Team: Leads a research group focusing on visual computing, with collaborations across computer science, engineering, and AI disciplines. Current focus areas include neural implicit representations and AI-driven physics simulations.

Raymond A Yehمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Raymond A. Yeh is an Assistant Professor in the Department of Computer Science at Purdue University since Fall 2022. Previously, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC) and completed his PhD in Electrical Engineering at the University of Illinois at Urbana-Champaign (UIUC) in 2021. His research focuses on machine learning and computer vision, particularly in developing algorithms for effective and explainable models across audio, vision, language, and multi-agent systems. Education: Ph.D., Electrical Engineering, UIUC (2021) M.S., Electrical Engineering, UIUC (2016) B.S., Electrical Engineering, UIUC (2014) Research Interests: His work bridges machine learning and computer vision, emphasizing equivariance in neural networks, robustness, and scalable algorithms. Key areas include: Generative models (diffusion models, inpainting) Equivariant deep learning architectures Multi-modal reasoning (vision-language) 3D reconstruction and simulation Recent Contributions: Recent work includes model immunization techniques, scale-equivariant networks, and novel datasets like Tree-D Fusion. His publications span top venues (CVPR, NeurIPS, ECCV) with 4,551 total citations (h-index 18 as of 2025). Awards: Google PhD Fellowship (2018) Best Paper Runner-up at CVPR Workshop (2024) National Science Foundation (NSF) Grant (2024) Purdue Seed for Success Award (2024) Teaching: Courses include Introduction to AI, Computer Vision with Deep Learning, and Foundations of Deep Learning. Student evaluations consistently score above 4.5/5.0. Labs: Leads the Purdue Vision and Learning Lab, focusing on advancing AI through robust, interpretable models with practical real-world applications.

Dieter Meillerمشاهده پروفایل

استاد

• Web Design
• Web Engineering
• Mobile Applications
• +۱۳ مورد دیگر

Prof. Dr. Dieter Meiller is a Professor at OTH Regensburg, specializing in the intersection of design and computer science. His research focuses on information visualization, human-computer interaction, and multimedia systems. Key areas include web engineering, mobile applications, aesthetics in computing, and 3D visualization. His work emphasizes making information accessible through engaging visual and interactive methods. Recent research explores topics like automated code evaluation, user response measurement, and virtual reality applications. He has contributed to Flutter-based app development frameworks and industrial data analysis through visual analytics. Dieter Meiller actively collaborates on projects involving digital education tools and immersive technologies. He maintains professional networks via LinkedIn and Xing, reflecting his commitment to interdisciplinary innovation.

• Computer Graphics
• Computational Geometry
• Visualization
• +۲ مورد دیگر

Dr. Sara Sheehan is Assistant Professor of Computer Science at Smith College, teaching courses in computer graphics and algorithm design. Her curriculum covers fundamental concepts including line drawing algorithms, Bézier curves, OpenGL programming, and 3D animation techniques. Course development features project-based learning in: 2D/3D transformation mathematics Graphics pipeline implementation Lighting and texture mapping Ray tracing fundamentals 3D modeling with Blender Her pedagogical approach integrates theoretical foundations with practical implementation through scaffolded programming assignments and 3D visualization projects.