جستجوی استاد راهنمای دانشگاهی

Tobias Schreck is a Professor at the Institute of Visual Computing (formerly Computer Graphics and Knowledge Visualization) at Graz University of Technology, affiliated with the Faculty for Computer Science and Biomedical Engineering. His research focuses on Visual Data Analysis, 3D Object Retrieval, and Immersive Analytics, with applications in engineering and industrial contexts. He holds a Dr.rer.nat. from the University of Konstanz and has held academic positions including Assistant Professor at the University of Konstanz and Head of the Visual Search and Analysis Group at TU Darmstadt. Education: Dr.rer.nat., University of Konstanz (2006) M.Sc. in Information Engineering, University of Konstanz (2002) Dipl.-Volkswirt (M.Sc. Economics), University of Konstanz (1999) His research interests include visual analytics for high-dimensional and spatial-temporal data, digital libraries, and collaborative analysis tools. He leads funded projects like HEREDITARY (EU Horizon Europe) and VR4CPPS (FFG), and has served as a program chair for IEEE VAST and EuroVis. His work emphasizes user interaction, eye-tracking integration, and immersive visualization techniques. He supervises a research team including postdocs, PhD students, and student assistants, and collaborates on projects like CrossSAVE-CH and the Joint PhD Programme with Nanyang Technological University. His contributions span publications in IEEE Transactions, EuroVis, and ACM conferences, addressing challenges in data exploration, anomaly detection, and visualization design.

• Visual Data Analysis
• 3D Object Retrieval
• Visual Analytics
• +۵ مورد دیگر

Shen Heng Tao is a Distinguished Professor and Dean of the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC). He is also the Executive Dean of the AI Research Institute and Chief Scientist of Vision Intelligence at the Peng Cheng Laboratory. His academic journey includes a BSc (First Class Honours) and PhD from the National University of Singapore (2000 and 2004), followed by roles at the University of Queensland, where he became a Professor in 2011. His research focuses on artificial intelligence, multimedia computing, and computer vision, with notable contributions to cross-media intelligent analysis and real-time video retrieval systems. He has published over 400 peer-reviewed papers, including 160+ IEEE/ACM Transactions, and holds an H-index of 78. His work has been recognized with awards such as the IEEE Fellow, ACM Fellow, OSA Fellow, and Clarivate Highly Cited Researcher. He has led 15 major research grants, including projects from the Ministry of Science and Technology of China and National Natural Science Foundation. His service includes roles as Associate Editor for journals like ACM Transactions of Data Science and IEEE Transactions on Multimedia, and conference chairs like ACM Multimedia 2021. His lab, the Center for Future Media, explores advanced topics like multimodal learning, trustworthy AI, and human-robot interaction. Current research emphasizes cross-modal reasoning and real-world applications in metaverse, autonomous systems, and smart cities.

• Artificial Intelligence
• Multimedia Computing
• Computer Vision
• +۳ مورد دیگر

Dacheng Tao is a Professor of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2010 and holds an ARC Future Fellowship since 2013. His work bridges statistics, mathematics, and advanced data analytics, with a focus on machine learning, computer vision, and multimedia technologies. Research Interests : Deep learning, computer vision, image processing, data mining, pattern recognition, geoinformatics, and video surveillance. Academic Contributions : Author of one monograph and over 400 publications in prestigious journals and conferences, with multiple best paper awards, including the 2014 ICDM 10 Year Highest Impact Paper Award. Honors and Recognition : 2015 ESI Highly Cited Researchers in Engineering and Computer Science. 2015 Australian Scopus-Eureka Prize, ACS Digital Disruptors Award (Gold Disruptor), and UTS Vice-Chancellor’s Medal for Exceptional Research. Fellowships in IEEE, IAPR, SPIE, OSA, IET, and BCS. Leadership and Service : Guest editor for 10+ special issues, editor for 10+ journals (including 7 IEEE Transactions), 4 conference keynote speeches, 60+ conference chairmanships, and service on 150+ major conferences and 60+ international journals.

• Deep learning
• Multimedia
• Applied statistics and mathematics
• +۸ مورد دیگر

Carme Torras is a Research Professor at the Spanish Council of Scientific Research (CSIC) since 1991, with a distinguished academic career spanning robotics, artificial intelligence, and neurocomputing. She holds a Ph.D. in Computer Science from Universitat Politècnica de Catalunya (UPC) and M.Sc. degrees in Mathematics and Computer Science from Universitat de Barcelona and the University of Massachusetts, respectively. Her research focuses on: Robotics (kinematics, motion planning, vision algorithms) Artificial Intelligence (machine learning, geometric reasoning) Neurocomputing (neural networks, computational biology) Computer Vision (pattern recognition, image processing) She has led major European projects like CLOTHILDE and SOFTENABLE, securing prestigious grants such as the ERC Advanced Grant. Her work bridges technical innovation with ethical discourse, including science fiction novels addressing robotics' societal impact. Scientific Awards and Honors: Narcís Monturiol Medal (2000) Fellow of IEEE, EurAI, and ELLIS (2019) Catalan and Spanish National Research Awards (2020) Robotics Professional Career Award (2022) She has supervised 20 PhD theses, with students achieving prominence in academia and industry, and served on editorial boards and conference committees globally. Her technology transfer includes patents and software for aerospace and robotics companies.

• Robotics
• Artificial Intelligence
• Neurocomputing
• +۳ مورد دیگر

Horst Bischof is a Professor at the Institute for Computer Graphics and Vision at Graz University of Technology, Austria, and serves as Vice Rector for Research. He holds an M.S. and Ph.D. from Vienna University of Technology and a Habilitation (venia docendi) in applied computer science. His research focuses on computer vision, medical image processing, and robot vision, with over 750 peer-reviewed publications. He has organized major conferences like CVPR 2015 and ECCV 2018, and serves on editorial boards of prestigious journals. Key awards include the Most Influential Paper over the Decade Award (MVA 2019), Jan Konderink Award (ECCV 2018), and the 29th Pattern Recognition Award (2002). His work spans object recognition, medical computer vision, and visual learning. He leads research teams in robot vision and collaborates with industry partners like Infineon Technologies. Current projects include LiDAR-based sensing systems, autonomous vehicle technologies, and medical imaging solutions like MedEyeTrack for eye tumor treatment. His research emphasizes practical applications in robotics, automotive, and healthcare sectors.

• Computer Vision
• Medical Computer Vision
• Object Recognition
• +۴ مورد دیگر

Jiebo Luo is a Professor of Computer Science at the University of Rochester, where he has held this position since 2014. He earned his BS and MS in Electrical Engineering from the University of Science and Technology of China (1989 and 1992) and a PhD in Electrical Engineering from the University of Rochester (1995). Prior to academia, he spent 15+ years at Kodak Research Laboratories as a Senior Principal Scientist. His research focuses on computational social science, natural language processing, digital health, computer vision, data mining, and multimedia. Dr. Luo’s work has been recognized through numerous awards, including the ACM SIGMM Technical Achievement Award (2021), Fellowships from ACM, AAAI, IEEE, IAPR, and SPIE. He has authored over 500 peer-reviewed papers, holds 90+ patents, and serves as Editor-in-Chief of the IEEE Transactions on Multimedia. He actively contributes to conference organization (e.g., ACM Multimedia, CVPR) and editorial roles for top journals. Key contributions include pioneering work in social media analytics, sentiment analysis, and digital health, as well as foundational research in multi-label classification and action recognition datasets like UCF 101. His labs and collaborations span the Goergen Institute for Data Science and the Greater Rochester Data Science Industry Consortium.

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Xiaoxiang Zhu is a Full Professor for Data Science in Earth Observation at Technical University of Munich (TUM) and Director of the International AI Future Lab (AI4EO). She leads interdisciplinary research on signal processing and machine learning applied to Earth observation (EO) data, addressing global challenges like urbanization and climate change. Her work focuses on extracting geoinformation from big EO datasets using innovative AI techniques. Education & Positions: Professor (W3) since 2019, TUM Former Head of EO Data Science Department at German Aerospace Center (DLR) Adjunct Teaching Professor (2013–2015) Research Interests: Deep learning in SAR and multispectral imagery Global urban morphology mapping Uncertainty quantification in AI models EO data fusion and big data analytics Climate change monitoring via satellite data Articles Trends: Her publications emphasize AI-driven solutions for EO challenges, including SAR tomography, benchmark datasets (e.g., So2Sat LCZ42), and uncertainty estimation in neural networks. Over 220 journal papers and 173 conference papers highlight her contributions to geosciences and remote sensing. Awards: IEEE Fellow (2021) ERC Grants (Starting & Proof of Concept) Heinz Maier-Leibnitz-Preis (2015) Member of German and Bavarian Academies of Sciences Advising & Grants: Supervised PhD students (e.g., Mou) Secured €10M+ in research funding Co-led Helmholtz AI Research Field MASTr (2019–2022) Labs & Teams: Founder of AI4EO Lab Co-leader of Munich Data Science Research School (MUDS) Member of ELLIS Society and IEEE committees

• Synthetic Aperture Radar
• Remote Sensing
• Global Urban Mapping
• +۴ مورد دیگر

Assoc. Prof. Ozan Özdenizci is a faculty member at the Institute of Machine Learning and Neural Computation, TU Graz, Austria. His research focuses on robustness, safety, and efficiency in machine learning, particularly in adversarial robustness, spiking neural networks, and privacy-aware learning. He holds a PhD from Northeastern University (2016), and MSc/BSc degrees from Sabancı University (2010/2008). Previously, he served as a postdoc at TU Graz (2016–2020) and a research group leader at Montanuniversität Leoben (2020–2023). Affiliations: TU Graz (2023–present), Montanuniversität Leoben (2020–2023), TU Graz Postdoc (2016–2020) Education: PhD (Northeastern University, 2016), MSc/BSc (Sabancı University, 2010/2008) Research Interests: Developing ML systems with robustness guarantees, efficient deep learning (e.g., spiking networks), and privacy-aware mechanisms. Key areas include adversarial defense mechanisms, sparse network design, and neuromorphic computing applications. His work bridges theoretical foundations with practical implementations in computer vision and autonomous systems. Recent Contributions: Advances in privacy-aware lifelong learning (ICLR 2025), robust spiking networks (TMLR 2024), and weather-resistant vision models (TPAMI 2023). His research emphasizes trade-offs between model efficiency, robustness, and scalability. Awards: Top Reviewer at NeurIPS 2023, Outstanding Reviewer at ICML 2022/ICLR 2022 Labs/Teams: Member of Graz Center for Machine Learning (GraML) and ELLIS Unit Graz

• Artificial Intelligence
• Machine Learning
• Robustness and Safety in ML
• +۴ مورد دیگر

Pascal Schöttle is a Professor for IT Security and Machine Learning at the Department of Digital Business & Software Engineering at MCI - The Entrepreneurial University in Innsbruck. He previously held roles including Associate Professor (2020-2022), University Lecturer (2018-2020), and Post-Doc positions at the University of Innsbruck and University of Münster. His academic journey includes a PhD in Computer Science from the University of Münster (2014), and prior studies in IT Security and Mathematical Engineering. Research focuses on adversarial machine learning, IoT security, blockchain applications, and game-theoretic approaches to cybersecurity. Notable projects include leading the Josef Ressel Center for Security Analysis of IoT Devices (2023-present) and managing the SMiLE project on encrypted machine learning (2021-2023). Awards include the IEEE Best Student Paper (2012) and CAST IT Security Runner-Up (2008). Education: PhD (Computer Science, 2014), MSc (IT Security, 2011), BSc (Mathematical Engineering, 2008) Teaching: Courses include IT Security, Machine Learning, Algorithms & Data Structures, and Blockchain Grants: FFG (2021-2023), FWF (2019-2023), University of Innsbruck (2017-2019) Labs/Teams: Research Center CDG, Josef Ressel IoT Security Group

• IT Security
• Machine Learning
• Adversarial Examples
• +۶ مورد دیگر

Monika Dörfler is a Professor in the Department of Mathematics at the University of Vienna. Her research focuses on applied harmonic analysis, audio signal processing, and the mathematics of machine learning. She specializes in time-frequency analysis, nonstationary Gabor frames, and deep learning applications in audio processing. Dörfler has contributed significantly to methods like the invertible constant-Q transform and has explored the intersection of convolutional neural networks with signal representation theory. Affiliations: Department of Mathematics, University of Vienna Roles: Professor, Privatdozent, Principal Investigator (PI) in grants including WWTF Hertha Firnberg and SALSA projects Teaching: Courses such as Applied Analysis and Bachelor seminar Her research interests emphasize both theoretical foundations and practical applications of signal processing techniques. Notable contributions include work on Gabor frames in deep scattering networks and orthogonal projections for dimension reduction in learning problems. Dörfler has received awards for her papers, including Best Paper Awards at ISMIR19 and DAFx-11, and has organized international conferences like SAMPTA19 and DAFx2020. Awards: Best Paper Gold (DAFx-11), ISMIR19 Award, WWTF Grant Leadership Grants: Co-PI in aMOBY (Acoustic Monitoring of Biodiversity), PI in Audio-Miner and Hertha Firnberg grant Her work addresses challenges in audio denoising, music information retrieval, and algorithmic biases in recommendation systems. Ongoing projects include "Filter them all! Gabor theory for image quality assessment" submitted to FWF in 2023.

• Applied Harmonic Analysis
• Audio Signal Processing
• Machine Learning
• +۳ مورد دیگر

Manfred Gronalt is a Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), within the Department of Economics and Social Sciences. He leads research in Production Management and Logistics, with a focus on the wood industry, industrialized housebuilding, and sustainable supply chains. He is based at Feistmantelstraße 4, 1180 Vienna, and can be contacted via email at manfred.gronalt@boku.ac.at. His research interests include Production Management , Logistics , Operations Research , Supply Chain Management , Simulation and Optimization , and Sustainable Resource Management , particularly in the forest-wood and construction sectors. His work emphasizes process improvement, performance measurement, and digital resilience in industrial contexts. The recent publications highlight a strong trend in applying simulation-optimization techniques to construction logistics, industrialized housebuilding, and disaster resilience. His work spans from discrete event simulation of prefab production lines to system dynamics modeling of internet outages in healthcare. A recurring theme is the integration of advanced modeling methods with real-world logistics and production challenges. His scientific awards include: Best Paper Award at HMS 2015 Austrian State Prize for Transport (2007) Prof. Gronalt has supervised numerous university theses and is actively involved in academic service as a reviewer for journals such as the International Journal of Production Research and the International Journal of Simulation and Process Modelling . He has collaborated on various research projects focusing on intermodal logistics, disaster relief, and sustainable wood supply chains, although no currently ongoing projects are listed. His work is deeply integrated with industry applications and policy-relevant issues in transport and resource management.

• Production Management
• Logistics
• Operations Research
• +۷ مورد دیگر

Harald Burgsteiner is a Professor for Media Didactics and Media Informatics at the Pädagogische Hochschule Steiermark (University College of Teacher Education Styria). His research focuses on integrating media technologies into educational practices, including artificial intelligence (AI), internet of things (IoT), and computational thinking in K-12 curricula. He leads projects exploring the synergy between educational technologies and self-regulated learning, as well as AI literacy among educators. His work addresses pandemic-related challenges in distance learning and digital transformation impacts on vocational training. Teaching areas include media education, computer science didactics, and AI integration in teacher training. He collaborates with the Institute for Digital Media Education to develop innovative teaching platforms like A2IoTS and AIoT solutions. Recent studies examine AI implementation in primary schools, AR-enabled IoT tools, and teacher preparedness for emerging technologies. His international research spans European SME digitalization and cross-cultural pandemic education responses. Publications highlight interdisciplinary approaches combining computational thinking with entrepreneurship and green skills. He has systematically reviewed teacher technology adoption, AI literacy gaps, and post-pandemic educational strategies. Current projects emphasize practical applications of machine learning in education and scalable digital solutions for schools. Key Research Themes: AI in Education, EdTech Innovation, Digital Transformation, Interdisciplinary Learning Collaborations: Institute for Digital Media Education, Styrian School Networks, EU-funded projects Public Engagement: Conference organization for doctoral researchers in education, policy advising on tech integration

• Media Didactics
• Media Informatics
• Computer Science Education
• +۴ مورد دیگر

Elmar Rückert is a Professor at the Chair of Cyber Physical Systems at Karlsruhe Institute of Technology. His work focuses on robotics, machine learning, and industrial automation with applications in environmental science and data-driven systems. Recent activities include invited talks on topics like Bayesian Optimization for control systems and deep learning in robotics. Research interests span tactile robot learning, privacy-aware AI, and sensor fusion for autonomous systems. He has published extensively in venues like IEEE International Conference on Robotics and AAAI Conference on Artificial Intelligence, with a strong emphasis on practical applications in industrial processes and environmental monitoring. Key contributions include the EnvoDat dataset for robotic spatial reasoning and methods for skill disentanglement in RKHS. His collaborative work extends to material science and environmental chemistry through partnerships on technology-critical element analysis.

• Robotics
• Machine Learning
• Industrial Automation
• +۳ مورد دیگر

Markus Steinberger is an Associate Professor at Graz University of Technology (Austria), leading the GPU Computing and Visualization Group at the Institute for Computer Graphics and Vision. He holds an MSc and PhD in Computer Science from TU Graz, with a postdoc and multiple leadership roles in academic and industry labs, including NVIDIA and the Max Planck Institute. His research focuses on GPU scheduling, parallel computing, and high-performance visualization techniques. He has led teams at TU Graz, Huawei Technologies (Cloud Rendering Lab), and the Max-Planck-Center for Visual Computing. Education 11/2020: Habilitation in Practical Computer Science at TU Graz 10/2013: PhD in Computer Science (Dynamic Resource Scheduling on Graphics Processors) 10/2010: MSc in Telematics 10/2005: BSc in Telematics Research Interests Steinberger’s work centers on optimizing GPU computing for real-time rendering and parallel processing. He explores efficient resource scheduling, dynamic graph management, and high-performance visualization techniques, with applications in cloud rendering, scientific visualization, and interactive graphics. His methods emphasize scalability and real-world applicability in both academic and industrial settings. Awards Heinz Zemanek Prize (2016) – First Austrian recipient GI Dissertation Prize (2014) – Best dissertation in German-speaking computer science Multiple Eurographics Best Paper Awards (2021, 2020, 2014) HPEC Best Student Paper (2017) ACM CHI Honorable Mention (2014) Advising & Grants Steinberger has advised numerous students and led projects funded by EU initiatives and industry partnerships. His research has been recognized through grants supporting GPU scheduling, cloud rendering, and parallel computing. Labs & Teams Leads the GPU Computing and Visualization Group at TU Graz and directed the Cloud Rendering Lab at Huawei, focusing on scalable rendering solutions for distributed systems.

• GPU Computing
• Computer Graphics
• Parallel Processing
• +۳ مورد دیگر

Ao.Univ.Prof. Margrit Gelautz is an Associate Professor at TU Wien's Computer Vision research department (E193-01), affiliated with the Institute for Software Technology and Interactive Systems (E188). Her work focuses on computer vision applications in autonomous driving, robotics, and 3D reconstruction. She leads projects on driver monitoring systems, vulnerable road user detection, and human-robot interaction. Recent research includes 3D bounding box prediction, synthetic data-driven pose estimation, and real-time sensor systems. She advises over 20 graduate students and collaborates on automotive platforms integrating vision-based safety systems. Her contributions span sensor fusion, stereo matching algorithms, and interactive video tools. Key projects include multimodal sensor-lighting systems for traffic safety, 3D scene completion, and intelligent workflow design for low-cost 3D film production. Her work emphasizes practical applications like in-cabin monitoring systems and adaptive lighting control. She develops semi-automatic annotation tools for traffic datasets and explores nonverbal communication in human-robot interaction using platforms like Pepper humanoid robots.

• Computer Vision
• Autonomous Driving
• 3D Reconstruction
• +۵ مورد دیگر