Oliver Deussen is a Professor of Visual Computing at the University of Konstanz, recognized by the German Informatics Society (GSI) as a Fellow for his contributions to computer science. His research focuses on visualization, robotics, and environmental modeling, particularly in plant and landscape representation. He has pioneered methods in image manipulation and robotic painting, emphasizing digitalization's societal impacts. His work spans computational biology (e.g., schooling fish behavior) and AI-driven creative technologies. Research Interests: Visualization techniques, swarm behavior analysis, robotic creativity, and interdisciplinary applications of computer science. He explores how computational methods can model natural systems and enhance human-machine interaction. Awards: Fellow of the German Informatics Society (GSI) His research often bridges theory and practice, with contributions to SLAM frameworks, style transfer algorithms, and uncertainty visualization tools. Collaborations in robotics and biology reflect his commitment to applied computational research.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۱-۱۵ از ۴۳ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
- Design Automation for Microfluidic Biochips
- Nanometer Integrated Circuits
- Embedded Systems
- +۳ مورد دیگر
Tsung-Yi Ho is a Professor in the Department of Computer Science at National Tsing Hua University, Taiwan. He holds the Hans Fischer Fellowship at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). His primary research focuses on design automation for microfluidic biochips and nanometer integrated circuits, emphasizing reliability, optimization, and interdisciplinary applications in bioengineering. Ho received his Ph.D. in Electrical Engineering from National Taiwan University in 2005. He has held positions at National Cheng Kung University and National Chiao Tung University before joining National Tsing Hua University. His work bridges algorithmic design with practical biochip fabrication, addressing challenges like contamination control, routing optimization, and fault tolerance in microfluidic systems. His research interests span design automation for emerging technologies, including paper-based biochips and 3D microfluidic architectures. He has pioneered methods for integrating hardware-software co-design principles into biochip development, enhancing both functionality and reliability. His contributions include novel routing algorithms, contamination mitigation techniques, and reliability-aware synthesis frameworks. Ho has authored over 100 publications, including influential papers in IEEE Transactions on CAD and ACM journals. He serves on the editorial boards of multiple top-tier journals and chairs professional chapters for ACM and IEEE. His awards include the Humboldt Research Fellowship, Dr. Wu Ta-You Memorial Award, and Best Paper Awards at VLSI Test Symposium and IEEE Transactions on CAD. His current projects involve optimizing control-fluidic co-design for paper-based biochips and developing AI-driven frameworks for microfluidic functionality prediction. He collaborates widely, leading cross-disciplinary initiatives at TUM-IAS and Taiwan's academic institutions.
Marco Polverini is an active computer networking researcher with a prolific publication record spanning over a decade, with 59 publications documented from 2012 to 2025. His work primarily focuses on advanced networking technologies including Segment Routing, Software Defined Networking, and Network Function Virtualization. His research interests center around network routing optimization, traffic engineering, and network monitoring. He has made significant contributions to Segment Routing technology, developing novel behaviors for low-latency communication, black hole detection mechanisms, and traffic matrix assessment techniques. His recent work integrates artificial intelligence approaches, particularly reinforcement learning, with traditional networking protocols to create more adaptive and efficient network systems. He has also been exploring the application of Digital Twin technology for network management and optimization. Analysis of his publication trends shows a clear evolution from foundational work on energy-efficient networking and traffic engineering to more recent innovations in Segment Routing, in-band network telemetry, and AI-driven network optimization. His publications consistently appear in top networking venues including IEEE JSAC, IEEE Transactions on Network and Service Management, INFOCOM, and NOMS, demonstrating his standing within the networking research community. Throughout his career, Polverini has maintained strong collaborative relationships, particularly with Antonio Cianfrani (54 joint publications), Marco Listanti (33 publications), and Francesco Giacinto Lavacca (16 publications), suggesting he works within a well-established research group focused on next-generation networking technologies.
- Sustainable consumer behavior
- Customer-centric brand management
- Science communication in marketing
- +۵ مورد دیگر
Professor Tatjana Steusloff is currently a Professor of General Business Administration (especially International Marketing) at the Wiesbaden Business School of HSRM since 2021. Previously held roles include Professor of Economics/Visiting Professor of Marketing at Düsseldorf University of Applied Sciences (2016–2020) and lecturer positions at various HAW institutions (2009–2016). Her career combines academic leadership with industry experience in marketing roles at companies like McCain Foods (Senior Brand Manager, 2004–2008) and Unilever Bestfoods (Brand Manager, 2000–2004). Education: Earned a Dr. rer.oek. (Magna Cum Laude) in 2016 from Leipzig Graduate School of Management (HHL), with prior studies at TU Dresden (1996–1998) and a semester abroad in the MBA program at University of Illinois at Urbana-Champaign (1999). Research Focus: Specializes in sustainable consumer behavior, customer-centric brand management, and science communication in marketing. Recent work emphasizes eco-route choice behavior and digital nudging interventions. Has presented at ISMS Marketing Science Conference (2024), EMAC Annual Conference (2023), and KSFE Annual Conference (2023). Teaching: Leads courses in international marketing strategies, strategic marketing, and market entry case studies at both bachelor's and master's levels in International Management programs. Professional Activities: Serves on the advisory board of Marketing Club Mainz-Wiesbaden (since 2025) and as curator for wi3 Consulting e.V. (since 2023). Previously held board positions in academic organizations (2022–2024).
Umer Farooq is a Professor at Dhofar University's College of Engineering, specializing in Electrical and Computer Engineering. His research spans interdisciplinary areas including artificial intelligence, nanotechnology, educational technology, and cybersecurity. He has contributed to over 90 publications since 2002, focusing on topics such as neural networks, federated learning, IoT security, and biomedical applications. His work bridges theoretical advancements with practical implementations in fields like medical imaging, renewable energy systems, and smart education platforms. Research interests emphasize innovative solutions at the intersection of engineering and computing. Notable contributions include federated learning frameworks for education, neural network-based medical diagnostics, and secure IoT systems. Recent trends in his publications highlight advancements in machine learning for healthcare, nonlinear dynamics in electronic systems, and sustainable energy solutions. No scientific awards or grants are explicitly listed in the provided texts. Collaborations span global institutions, reflecting his active role in international academic networks.
Mitra Baratchiمشاهده پروفایل
دانشیار
Mitra Baratchi is an Associate Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University. She leads the Spatio-temporal data Analysis and Reasoning (STAR) research group, co-leads the Automated Design of Algorithms (ADA) group, and founded the Special Interest Group on Spatio-Temporal Data Mining (SIG-SDTM) . PhD from University of Twente (Mobility Data) Master’s/Bachelor’s in Computer Engineering, Iran Research Interests focus on automated pattern extraction from spatio-temporal data across urban, environmental, and industrial domains. Key applications include: Automated Machine Learning (AutoML) for Earth Observations Time-Series Forecasting for public health (e.g., pandemic modeling) Urban Mobility Optimization with ESA, Honda, and municipalities Reliable Vehicular Communication Systems Smart Garments for Health Risk Detection Geocast Protocols for Internet-wide Communication Grant Highlights include €120K NWO-Aspasia, €2.9M Marie Skłodowska-Curie, €350K NWO-KLEIN, and €135K Center for BOLD Cities funding. She has supervised 12 PhD students and 4 current Master’s students since 2011, with notable best paper award at WWIC'16. Teaching includes Machine Learning (2020-present) and Urban Computing (2018-present) at Leiden, plus past courses in Data Visualization, Software Engineering, and Research Methods.
Nitinder Mohanمشاهده پروفایل
استادیار
Nitinder Mohan is an Assistant Professor in the Faculty of Electrical Engineering, Mathematics, and Computer Science (EEMCS) at Delft University of Technology (TU Delft), where he leads the Systems and Protocols for Edge-Enabled Internet (SPEAR) Lab. His research focuses on edge computing, next-generation network protocols, and Internet-wide measurements. Previously, he was a senior researcher at Technical University of Munich and holds a PhD from University of Helsinki (awarded IEEE TCSC Outstanding Dissertation Award). Research interests span: Edge computing infrastructure and orchestration Next-generation network protocols (MPTCP, QUIC) Internet-wide measurements and performance analysis Satellite networking (Starlink/LEO networks) Distributed machine learning at edge His publications demonstrate strong focus on practical systems research in edge computing (container orchestration, Oakestra framework), network protocol innovation (segment routing, MPTCP), and empirical Internet measurements (Starlink/CDN analysis). Recent work shows growing emphasis on satellite networking and edge AI. Awards & Honors: IETF/IRTF Applied Networking Research Prize (2025) ACM EdgeSys Best Paper Award (2025) RIPE Academic Cooperation Fellowship (2025) ACM EuroSys Best Poster Award (2025) IEEE Future Networks Best Paper (2023) IEEE TCSC Outstanding PhD Dissertation (2020) Advises multiple PhD and master's students on edge computing, networking, and distributed systems. Secured significant funding including EU Horizon 2020 grant (€5.4M for EDGELESS project). Founded Oakestra - an open-source edge orchestration framework. Leads the SPEAR Lab at TU Delft focusing on edge-enabled Internet systems. Organizes conferences (TMA 2026) and workshops (LEO-NET). Active in IETF/IRTF standards community and industry collaborations with Microsoft Research, Airbus, and Siemens.
Eva Stukenbrockمشاهده پروفایل
پژوهشگر ارشد
Prof. Dr. Eva Stukenbrock leads the Max Planck Fellow Group Environmental Genomics at the Max Planck Institute for Evolutionary Biology in Plön, Germany. Her research focuses on the genomic evolution of plant-pathogenic fungi, particularly Zymoseptoria tritici , using population genomics and comparative approaches to unravel mechanisms of host specialization, virulence, and genome plasticity. Key Research Areas: Fungal plant pathogens, evolutionary genomics, population genetics, host-pathogen interactions, and microbiome dynamics Academic Leadership: Supervised 15+ PhD, Master’s, and Bachelor’s students in fungal pathogenesis and genomics Technical Innovation: Developed confocal microscopy pipelines for plant-fungal interaction analysis Her recent work reveals how domestication history shaped pathogen emergence, with studies on barley net blotch and oat crown rust in 2024. She has also uncovered roles of horizontal chromosome transfer in asexual pathogens and accessory chromosome loss leading to endophytic lifestyle shifts. Current projects include AI-assisted infection dynamics and tRNA composition analyses in fungal adaptation. Selected scientific trends from her 15 most recent articles include: Host specialization linked to vernalization requirements Segmental duplications driving accessory genome evolution Hybrid incompatibilities as speciation drivers Seed microbiome differences between wild and domesticated wheat Her lab collaborates with institutions like Christian-Albrechts-Universität zu Kiel and CRC Press , focusing on fungal effector biology , chromatin regulation , and agricultural disease management .
Xueguang Yuanمشاهده پروفایل
پژوهشگر
Xueguang Yuan is a researcher with expertise in optical communication systems, medical image segmentation, blockchain technology, and IoT networks. Their work spans 2009–2024, focusing on advanced sensor design, federated learning algorithms, and secure communication protocols. Key Research Areas : Optical Time-Domain Reflectometry, Graphene Metasurfaces, Thyroid Nodule Segmentation, and Federated Learning for Multi-Institutional Collaboration Recent Publications (2024): Wearable strain sensors using MXene composites, SNR optimization in Φ-OTDR systems, and polarization conversion metasurfaces for radar cross-section reduction Notable collaborations include Yangan Zhang (optical systems), Xiaohong Huang (medical AI), and Zhifang Deng (federated learning). Trends in their 2021–2024 articles highlight applications of transformers , compressed sensing , and blockchain in healthcare, 5G networks, and security. They have contributed to 5G broadcast services, satellite routing, and edge computing platforms, though no formal awards or student mentorship details are publicly listed in the provided sources.
Stefan Funkeمشاهده پروفایل
پژوهشگر
Stefan Funke is a researcher at the University of Stuttgart, Germany, with a focus on algorithms and computational geometry. His work spans wireless communication, route planning, and trajectory analysis. Research Interests: Algorithms, Computational Geometry, Wireless Communication, Route Planning, Trajectory Segmentation His recent publications (2024-2025) explore topics like 3D epithelial cell dynamics, graph radius computation, and polyline simplification, emphasizing scalability and efficiency. Earlier works (2017-2019) investigate contraction hierarchies, energy-efficient routing, and trajectory storage systems. Stefan collaborates frequently with Sabine Storandt, Claudius Proissl, and Tobias Rupp. He applies geometric methods to problems in wireless networks, road systems, and data structures, with a recurring emphasis on optimization and robustness.
Stefan Funke is a Professor at the University of Stuttgart's Institute for Formal Methods in Computer Science, part of the Faculty of Computer Science, Electrical Engineering and Information Technology. His work focuses on algorithm design and computational geometry with applications in road networks, trajectory analysis, and geographic information systems. He leads the Algorithmics Group, developing efficient algorithms for shortest path planning, network optimization, and privacy-preserving queries. Research interests include geometric algorithms, graph theory, and practical implementations of theoretical results in transportation and spatial data analysis. Notable contributions involve contraction hierarchies for fast shortest path queries, trajectory mining techniques, and methods for preserving privacy in network-based computations. Recent work emphasizes scalable solutions for large-scale road networks, including simplification methods that preserve topological features and energy-efficient routing strategies for electric vehicles. His research often bridges theoretical foundations with real-world applications in navigation systems and smart mobility solutions. Awards and grants are not explicitly listed in the provided data, but his extensive publication record indicates sustained recognition in algorithmic research. He advises on multiple interdisciplinary projects involving spatial data processing and algorithm engineering.
- Geoinformatics
- 3D City Modeling
- Remote Sensing
- +۷ مورد دیگر
Prof. Dr.-Ing. Youness Dehbi is a Professor for Computational Methods at HafenCity University Hamburg. His academic career includes roles as a postdoctoral researcher and scientific assistant at the University of Bonn's Institute of Geodesy and Geoinformation. He holds a Ph.D. in Computer Science from the University of Bonn (2016). His research focuses on geoinformatics, 3D city modeling, remote sensing, and applications in urban planning and disaster management. He has led projects such as VisioChick (enhancing animal welfare via mixed reality) and FPOplus (5G-based passenger flow management). Education: Ph.D. in Computer Science, University of Bonn (2016) M.Sc. and B.Sc. in Computer Science and Communication Research, University of Bonn (2008) Research Interests: Prof. Dehbi specializes in computational methods for spatial data analysis, including laser scanning, UAV missions, and semantic segmentation of historical maps. He explores applications in BIM, flood risk communication, and smart city technologies. His work bridges geoinformatics with urban sustainability and mixed reality. Awards: Best Paper Awards at multiple international conferences (2018–2024) Best Reviewer Award, ISPRS Congress (2021) Advising & Projects: He advises projects like NGCN (Next Generation City Networking) and collaborates with institutions like TU München and the University of Osnabrück. His team includes researchers like Dr. Son H. Nguyen and M.Sc. Lukas Arzoumanidis. Lab & Teams: His Computational Methods Lab at HCU develops tools for 3D city modeling and spatial data analysis, contributing to open-source geospatial software and collaboration with industry partners.
Xingang Shi is a Professor in the Department of Computer Science and Technology at Tsinghua University's School of Information Science and Technology. With over 126 publications spanning from 2006 to 2025, he maintains an active and influential research program in computer networking, with recent expansion into quantum network optimization. His work consistently appears in top-tier venues including INFOCOM, IEEE/ACM Transactions on Networking, and SIGCOMM. Dr. Shi's research focuses on network security, software defined networking, traffic engineering, and network anomaly detection. His recent work shows increasing emphasis on quantum network optimization and advanced security verification techniques. He has developed innovative approaches to routing protocols, congestion control, and inter-domain routing analysis, with practical applications in real-world network infrastructure. His publication trends reveal a steady evolution from traditional networking topics toward more sophisticated security and optimization frameworks. The 15 most recent publications demonstrate strong integration of machine learning techniques with networking fundamentals, particularly in anomaly detection and traffic engineering. His work increasingly addresses quantum networking challenges while maintaining strong contributions to conventional network security and performance optimization. As a leading researcher in his field, Dr. Shi has made significant contributions to network verification methodologies and security protocol testing frameworks. His recent papers on model checking-based security testing and proactive network policy verification represent important advances in ensuring network reliability and security. Through his extensive collaboration network (particularly with Zhiliang Wang, Xia Yin, and Han Zhang), Dr. Shi has built a productive research ecosystem that bridges theoretical networking concepts with practical implementation challenges. His work on quantum network optimization represents an emerging frontier in his research portfolio.
- Wholesale Innovation Ecosystems
- Digital Transformation
- Artificial Intelligence in Logistics
- +۱ مورد دیگر
Prof. Dr. Heiko Wrobel is a faculty member at Nuremberg Institute of Technology (TH Nürnberg), where he teaches Operations Management at the Bachelor's level and Supply Chain Services/Logistics Controlling at the Master's level. He concurrently serves as Business Unit Coordinator for Wholesale/B2B at the Fraunhofer IIS SCS working group in Nuremberg and holds advisory roles in the Research Association Wholesale eV (Berlin). His memberships include the Digitalization Working Group of BGA (Berlin), Federal Association of Logistics BVL (Bremen), and German Transport Forum DVF (Berlin). His research explores innovation ecosystems in wholesale, digital transformation of logistics, AI applications in supply chains, and service design for B2B commerce. Key investigations address autonomous logistics, blockchain integration, sustainability metrics, and lean management adaptations for wholesale environments. Wrobel's publications (2013-2024) predominantly analyze wholesale digitization, contract logistics optimization, and sustainable supply chains. Recurring themes include third-party logistics (3PL) business models, performance benchmarking methodologies, and technology-driven service innovation in B2B contexts. He actively supervises student theses on wholesale management, digital transformation, and logistics innovation, with 14 example projects completed. No scientific awards are documented in the provided materials.
Viridiane Fayمشاهده پروفایل
پژوهشگر
Viridiane Fay is a researcher in the Institute of Modern Languages and Romance Studies at the University of Würzburg , specializing in French language practice and applied computational methods. During lecture periods, she holds office hours every Tuesday from 1 p.m. to 2 p.m., with appointments available during semester breaks. Role: French Editor, Language Practice Location: Am Hubland, 97074 Würzburg Contact: viridiane.fay@uni-wuerzburg.de Her research spans two distinct domains: French language pedagogy and computer vision/AI . While her institutional affiliation focuses on Romance Studies, her publication record reveals expertise in: Medical and underwater image processing Transformer-based architectures Federated learning and network optimization Watermarking and security algorithms Multi-modal AI applications Neuroscience signal analysis Recent work includes lightweight segmentation models (e.g., ContextFormer), drone/aerial imagery detection frameworks (CH-YOLO-Lite), and privacy-preserving AI systems (Find). Despite limited biographical details in the scrape, her 30+ publications since 2017 suggest significant technical contributions.