جستجوی استاد راهنمای دانشگاهی

Hao Gao is a Professor in the Department of Computer and Information Science at the University of Macau, Faculty of Science and Technology. His research spans computer vision, image processing, and machine learning with a particular focus on human pose estimation, 3D reconstruction, and optimization algorithms. He maintains strong collaborative ties with Nanjing University of Posts and Telecommunications in China, reflecting a dual institutional affiliation that enhances his research impact across Greater China. His research interests center on computer vision and artificial intelligence, with significant contributions in human pose estimation, 3D reconstruction, point cloud processing, and optimization algorithms. Dr. Gao's work on skeleton-based action recognition, scene flow estimation, and neural rendering techniques has established him as a leading researcher in these specialized areas. His recent work on GaussianHead for high-fidelity head avatars and lifespan age synthesis demonstrates his ability to bridge theoretical advances with practical applications in digital human representation. Dr. Gao's publication record shows a clear evolution from foundational work on artificial bee colony algorithms to cutting-edge research in neural rendering and 3D vision. His recent publications (2023-2025) demonstrate a strong focus on human-centric computer vision problems, including pose estimation, motion prediction, and medical applications for Parkinson's disease assessment. The interdisciplinary nature of his work connects computer vision with healthcare applications, autonomous systems, and virtual reality. Dr. Gao has mentored numerous graduate students who have become productive researchers in their own right, including Haolun Li, Jiucheng Xie, and Jian Xiong who frequently appear as co-authors on his publications. His research group has secured funding for projects related to human motion analysis, medical image processing, and autonomous driving perception systems. His laboratory focuses on advancing computer vision techniques for human understanding, with recent projects including skeleton-based action recognition systems, Parkinson's disease assessment tools, and high-fidelity digital avatar creation. The team maintains strong industry connections, particularly in applications related to autonomous vehicles and medical diagnostics.

• Computer Vision
• Image Processing
• Machine Learning
• +۵ مورد دیگر

Prof. Martin Skutella holds the Einstein Professorship in Mathematics and Computer Science at Technische Universität Berlin (TU Berlin), where he is part of Faculty II – Mathematics and Natural Sciences and the Department of Mathematics. His research focuses on combinatorial optimization, network flows, scheduling, and algorithmic game theory. He leads major initiatives such as the Berlin Mathematics Research Center MATH+ and previously served as Chair of MATHEON. Skutella is renowned for contributions to dynamic network flows, evacuation planning, and scheduling under uncertainty. His work bridges theoretical advancements with practical applications, including transportation systems, robotic welding, and gas network optimization. He has been recognized with awards like the Einstein Professorship (2015) and the Best Teaching Award (2004). Skutella advises numerous PhD students and collaborates internationally on projects funded by DFG, EU, and industry grants. Key roles include organizing the 2012 International Symposium on Mathematical Programming and editing the Notices of the German Mathematical Society. His lab focuses on discrete optimization and graph algorithms, with applications in logistics, transportation, and energy systems.

• Combinatorial Optimization
• Network Flows
• Discrete Mathematics
• +۶ مورد دیگر

Leonard Wörteler is a Researcher at the University of Konstanz's Department of Computer and Information Science, affiliated with the Database and Information Systems group. He joined as a PhD student in 2015 after completing his Bachelor's (2012) and Master's (2015) in Computer and Information Science at the same institution. His research focuses on query optimization, including architectures, parallel heuristic algorithms, and non-relational databases. He has contributed to teaching, including courses on database systems and computer science fundamentals. His research explores advanced optimization techniques, such as neural language models for cardinality estimation and landmark-based algorithms for graph databases. He has published in venues like IDA, DBPL, and SIGRAD, addressing topics ranging from XQuery optimization to real-time transportation visualization. Wörteler's work emphasizes practical implementations, such as optimizing Neo4j's performance through landmark embedding. His contributions bridge theoretical optimization frameworks with real-world applications in databases and data mining.

• Query Optimization
• Database Systems
• Parallel Heuristic Algorithms
• +۳ مورد دیگر

Dr.-Ing. Udo Feuerhake is a Researcher at the Institute of Cartography and Geoinformatics (IKG) within the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover. His work focuses on spatio-temporal data analysis, urban digital twins, and transportation engineering. He holds a M.Sc. in Computergestützte Ingenieurwissenschaften from Leibniz University Hannover (2010) and has been with IKG since 2011. Research interests include voxel-based urban modeling, trajectory analysis, and mobility patterns. Notable projects involve integrating 3D geodata for urban digital twins, smartphone-based vehicle detection, and developing interactive web applications for spatial visualization. He collaborates on projects like the USEfUL logistics tool and contributes to traffic analytics dashboards (TA-Dash). Feuerhake leads and co-leads multiple theses, including work on 3D navigation path planning, parking occupancy visualization, and AR/MR applications. His research emphasizes real-world applications in smart cities, emergency response systems, and sustainable urban logistics. Key Projects: Urban Digital Twin development, smartphone sensor platforms, trajectory pattern mining Teaching: Involved in thesis supervision and module development for spatial analysis and visualization Awards: None explicitly mentioned

• Spatio-temporal Data Analysis
• Geoinformatics
• Urban Digital Twin
• +۵ مورد دیگر

Professor Alexander Fay is a faculty member at Ruhr University Bochum, leading the Automation Engineering department within the Faculty of Electrical Engineering and Information Technology. His roles include Head of Department and a prominent researcher in automation technology, Industry 4.0, and cyber-physical systems. Educated at TU Braunschweig, he has extensive industry experience from ABB and academic leadership at HSU/UniBw Hamburg. His research focuses on automation systems, energy optimization, and autonomous robotics, with notable contributions in digital twin frameworks, agent-based control, and industrial data management. He has been honored with awards such as the MIT Review's 'Top 100 Young Innovators' and the Golden Badge of Honour from NAMUR. His work integrates interdisciplinary approaches, emphasizing practical applications in manufacturing, energy systems, and aerospace maintenance. Key collaborations include projects on modular electrolysis plants and U-space drone traffic management. His academic output spans over 70 publications in top-tier journals and conferences, reflecting expertise in automation theory and industry-relevant solutions.

• Automation Technology
• Industrial Automation
• Energy Systems
• +۶ مورد دیگر

Fabio Persia is a researcher affiliated with the University of Naples Federico II , with a focus on Semantic Computing , Multimedia Recommender Systems , and Event Detection in Video Surveillance . His work spans interdisciplinary applications in Healthcare , Robotics , and Social Network Analysis , often collaborating with co-researchers like Daniela D'Auria, Mouzhi Ge, and Giovanni Pilato. His research interests include leveraging Artificial Intelligence and Complex Event Processing to enhance patient monitoring and healthcare systems . He has contributed to frameworks for social sensing , surveillance , and personalized recommendations . Publications highlight his expertise in semantic indexing , multimedia analysis , and intelligent systems . Key works involve AI-driven patient monitoring , risk-aware route planning , and social network behavior modeling . As a co-author in numerous journals and conferences, he has co-edited special issues in the International Journal on Semantic Computing and contributed to Clinical and Collaborative Robotics advancements. His current role remains active, with recent 2025 publications indicating ongoing research.

• Semantic Computing
• Multimedia Recommender Systems
• Video Surveillance
• +۵ مورد دیگر

Dr. Birgit Schwartz-Reinken is a Lecturer at the University of Hamburg's Business School, affiliated with the Institute of Business Information Systems. She holds a Ph.D. in parallel computing and business planning from 1994. Her research focuses on Operations Research, Parallel Algorithms, Supply Chain Management, and E-Learning. She has authored or co-authored 8 publications since 1990, including works on Eclipse-based GUI design and adaptive virtual learning environments. Her work bridges computational optimization and business informatics. Education: Ph.D. in Parallel Processing and Business Planning (1994) Research Interests: Combines parallel algorithm design with business optimization challenges, particularly in supply chain and production planning. Explores E-Learning methodologies for adaptive instructional systems. Publications: Recent work emphasizes software tools like Eclipse for enterprise development, while earlier research addressed parallel computing applications in combinatorial optimization and manufacturing systems. Grants/Advising: No specific grants or advisee records noted in provided texts.

• Operations Research (Linear Programming, Mixed-Integer Programming)
• Parallel Algorithms
• Supply Chain Management
• +۲ مورد دیگر

Prof. Dr. Ute Schmid is Chair of Cognitive Systems and Executive Director of the Bamberg Center of Artificial Intelligence (BaCAI) at the University of Bamberg. She also leads the Fraunhofer IIS project group Comprehensible AI (CAI), serves on the Bavarian AI Council and the Bavarian Institute for Digital Transformation (bidt), and is a fortiss Research Fellow. Her interdisciplinary work bridges computer science, psychology, and education. Education: Diploma in Psychology, Technical University Berlin (TUB) Diploma in Computer Science, Technical University Berlin (TUB) Dr. rer. nat. in Computer Science, TUB (1994) Habilitation in Computer Science, TUB (2002) Ute Schmid's research centers on explainable and interpretable machine learning, with a focus on inductive programming, interactive human-in-the-loop learning, and neuro-symbolic integration. She investigates how human expertise—both explicit and implicit—can guide machine learning models to improve transparency and trust. Her work spans cognitive modeling, intelligent tutoring systems, and AI for education, especially in primary schools. Applications include medical diagnostics, industrial quality control, and AI literacy for non-experts. Her recent publications highlight a consistent trend toward human-centered AI, emphasizing explainability, interactivity, and cognitive plausibility. Topics include explanation generation in relational domains, hybrid learning systems, and educational tools for AI literacy. These reflect her commitment to making AI accessible, trustworthy, and educationally meaningful. Scientific Awards: EurAI Fellow (2022) GI Fellow (2023) Minerva Gender Equality Award (2018) Rainer-Markgraf-Preis (2020) fortiss Research Fellow Ute Schmid actively mentors students and leads multiple funded research projects, including DFG, BMBF, and BayVFP initiatives. She is deeply involved in public outreach, teacher training, and gender equality in computer science. She leads the FELI research group (Computer Science for Kids) and organizes Girls' Day and youth programs. Her leadership extends to national and international initiatives such as Plattform Lernende Systeme, KI Campus, and the Human-Like Computing Network+. Labs and Teams: Cognitive Systems Research Group, University of Bamberg Fraunhofer IIS Project Group Comprehensible AI (CAI) FELI: Elementary Computer Science Research Group Bamberg Center of Artificial Intelligence (BaCAI)

• Explainable Artificial Intelligence (XAI)
• Interpretable Machine Learning
• Inductive Programming
• +۱۲ مورد دیگر

Prof. Dr. Dirk Schweim is a Professor at the Department of Business Information Systems and Business Administration at Johannes Gutenberg University Mainz. His research focuses on machine learning, particularly neural networks and Estimation of Distribution Algorithms (EDAs) for combinatorial optimization. He is currently investigating EDAs using neural network models for variable-length encoding problems. Schweim has held roles including research assistant under Prof. Franz Rothlauf since 2016 and part-time project management at R+V Versicherung (2013–2016). Teaching responsibilities include lecturing 'Business Mathematics/Statistics I' at RheinMain University of Applied Sciences and coordinating tutorials for 'Internet Technologies and E-Business'. He has supervised numerous Bachelor’s and Master’s theses since 2016/17. His academic background includes a Master of Science in Management from Mainz University (2013–2016) and a Bachelor of Science in Business Informatics from HWR Berlin (2008–2011). Research interests span genetic programming, ERP systems, and decision support systems. Key publications include work on denoising autoencoder LSTMs in genetic programming and the influence of grammars in evolutionary algorithms.

• Machine Learning
• Artificial Neural Networks
• Estimation of Distribution Algorithms (EDAs)
• +۳ مورد دیگر

Prof. Dr.-Ing. Darius Burschka is a Professor of Robotics, Artificial Intelligence, and Embedded Systems at Technische Universität München (TUM), specifically within the TUM School of Computation, Information and Technology. He leads the Professorship of Robotics, Artificial Intelligence and Embedded Systems and collaborates closely with the German Aerospace Center (DLR). His academic career includes postdoctoral research at Yale University (1998), associate research scientist and assistant research professor roles at Johns Hopkins University (1999-2005), and has been at TUM since 2005. His research focuses on sensor systems in robotics, human-machine interfaces, video-based navigation, and 3D reconstruction. Notable contributions include advancements in laser-based map generation, monocular navigation algorithms, and endoscopic image registration for medical applications. Prof. Burschka has received awards such as the Airtec 2010 Silver Award and best paper awards from prominent conferences like IROS and MICCAI. His work spans robotics, autonomous systems, computer vision, and medical imaging, with a strong emphasis on real-world applications in automotive, healthcare, and industrial automation. Education: Bachelor/Master in Electrical Engineering at TUM Doctorate (Dr.-Ing.) in Electrical Engineering, TUM (1998) His research interests include: Autonomous navigation and control Multi-sensor fusion and 3D reconstruction Human-robot interaction and haptic systems Robotic perception in dynamic environments Recent articles highlight advancements in graph neural networks for action segmentation, hybrid tracking systems, and latency modeling in industrial robotics, reflecting his ongoing contributions to cutting-edge robotics and AI.

• Robotics
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Ramiz Qussous is a Researcher and doctoral candidate at the Chair for Control and Information Technology (CIG) within the Institute for Automation and Applied Informatics (INATECH) at the University of Freiburg. His work focuses on modeling and simulation of energy systems and electricity markets, with expertise in renewable energy integration, grid flexibility, and market dynamics. He holds a Master of Science in Energy Conversion and Management from the University of Applied Sciences Offenburg and a Bachelor of Science in Energy Engineering from the German Jordanian University. His research interests include agent-based modeling, reinforcement learning applications in energy systems, and the analysis of electricity market mechanisms. Notable contributions include the development of the ASSUME framework for simulating market dynamics and studies on the German steel industry's demand-side flexibility and battery storage potential. He has also explored policy impacts such as coal phase-outs and the integration of renewable energy constraints into modeling tools. Qussous has authored over 20 peer-reviewed publications since 2019, spanning journals like Energy and AI , Applied Energy , and Energy Informatics . His work frequently addresses interdisciplinary challenges at the intersection of energy systems, economics, and policy. He received the DAAD Prize for academic excellence during his studies in Germany. Professional experience includes roles as a research associate at INATECH since 2017, with prior industry experience in photovoltaic system design and energy planning. His current projects involve optimizing energy system scenarios, analyzing flexibility provision costs, and advancing agent-based simulation techniques for realistic market modeling.

• Energy Systems Modeling
• Energy Markets
• Renewable Energy
• +۳ مورد دیگر

Prof. Nico Christoph Clever holds a professorship in Digital Real Estate and Facility Management at Münster University of Applied Sciences (FH Münster), Germany. Previously, he served as a research assistant at the Chair of Information Systems and Information Management at the Westfälische Wilhelms-Universität Münster from 2011 to 2020. He earned his doctorate in Business Informatics from Münster University in 2016, focusing on the development of the icebricks process modeling framework. His research spans Business Process Management (BPM), digital transformation, ERP systems, and quality management. Notable contributions include the icebricks methodology for standardized process modeling, the VHB Textbook Award (2019), and a Best Paper Award at eKNOW 2013. He has taught at both FH Münster and the University of Münster's executive education programs. Recent work explores social media analysis, including automated detection of extremist propaganda on Instagram. He leads projects like the Mittelstand 4.0 Competence Center in Lingen, supporting SMEs in digital collaboration. His interdisciplinary approach bridges academic research and industry application, emphasizing practical BPM solutions. Education: PhD in Business Informatics, Westfälische Wilhelms-Universität Münster (2011–2016) M.Sc. Business Information Systems, WWU Münster (2009–2011) B.Sc. Business Information Systems, WWU Münster (2006–2009) Professional Highlights: Over 10 years of experience in BPM research and tool development Project leadership in digitalization for SMEs Co-designed the icebricks modeling tool and methodology His awards reflect impactful contributions to BPM and academic writing, while his teaching spans digitalization, process modeling, and facility management. Current research merges BPM with emerging technologies like blockchain and social media analytics.

• Business Process Management
• Information Systems
• Digital Transformation
• +۵ مورد دیگر

Prof. Dr. Fernando Buarque is a Visiting Professor at the University of Münster, affiliated with the School of Business and Economics and the Department of Business Information Systems and Logistics. His research focuses on swarm intelligence algorithms, evolutionary computation, parallel computing, and optimization techniques applied to supply chain management. He collaborates closely with Prof. Hellingrath's research group and holds a DIC PhD and AvH (likely Alexander von Humboldt) fellowships. Key research areas include parameter control for optimization algorithms, high-level parallelization strategies, and application of metaheuristics to real-world problems. His work emphasizes GPU-based parallelization, algorithmic skeletons, and sensitivity analysis of hyper-heuristics. Recent contributions address parameterless population size control and learning properties of reinforcement learning in algorithmic frameworks. Publications span journals like Applied Soft Computing and International Journal of Parallel Programming, with conference contributions at IEEE events and the Genetic and Evolutionary Computation Conference (GECCO). His research bridges theoretical advancements with practical implementations in logistics and supply chain optimization.

• Swarm Intelligence Algorithms
• Evolutionary Algorithms
• Parallel Computing
• +۳ مورد دیگر

PD Dr. Henning Füller is a Research Professor at the Humboldt University of Berlin, affiliated with the Department of Geographical Institute under the Faculty of Mathematics and Natural Sciences. His academic focus lies in cultural and social geography, with particular expertise in urban health, pandemic studies, spatial analysis, and critical urban theory. He actively contributes to interdisciplinary research at the intersection of geography, public health, and policy. His research explores spatial determinants of health in urban contexts, governance of public health interventions, and the socio-political dimensions of urban spaces. Notable themes include pandemic response strategies, biopolitical governance, and the interplay between urban planning and health equity. Füller's work critically examines how spatial structures influence social exclusion, health disparities, and urban transformation processes. Recent publications highlight his engagement with post-pandemic urbanism, digital health monitoring systems, and theoretical advancements in spatial analysis. He has authored methodological guides for academic research and collaborates internationally on projects such as the Alexander von Humboldt Professorship for Sustainability Science. His contributions span empirical studies in Berlin, Ghana, and Los Angeles, reflecting a globally oriented research agenda. While no formal awards or grants are explicitly listed in the provided materials, his prolific publication record and institutional roles underscore his scholarly impact. Füller’s work is characterized by its critical approach to spatial power dynamics and its application to contemporary urban challenges.

• Urban Geography
• Public Health
• Spatial Analysis
• +۳ مورد دیگر

Carlos Medina Sánchez is a Researcher at the Networked Embedded Systems group of the University of Duisburg-Essen . His work focuses on robotics, particularly in multi-robot deployment, semantic mapping, and human-aware navigation. Education: Ph.D. candidate (since 2018), Master in Electronics/Robotics/Automatics (2017), Mechatronics Engineering (2013) Research Interests include: Multi-Robot Systems Social Navigation Semantic Mapping Human-Robot Interaction Publication Trends show expertise in point-cloud processing, path planning, and human-centric navigation. Recent works address 3D scene graphs, group detection, and real-time room classification for improved robot perception.

• Multi-Robot Systems
• Autonomous Navigation
• Social Robotics
• +۲ مورد دیگر