Find Academic Supervisors

Marcel VoßhansView profile

Researcher

• Autonomous Driving
• Artificial Intelligence
• Computer Vision
• +3 more

Marcel Voßhans serves as a Researcher and Technical Project Leader for the AMEISE Team (Project RAFT) at Esslingen University of Applied Sciences' School of Computer Science and Engineering. He teaches specialized courses including Perceptional Algorithms, ROS, Sensory Systems (LiDAR/Camera), Autonomous Driving & Simulation, and Automotive Functional Safety. Education: 2015-2018: B.Eng. in Electrical Engineering and Information Technology, Hochschule Hannover 2018-2020: M.Sc. in Applied Computer Science: Autonomous Systems, Hochschule Esslingen Research Focus: His work centers on Autonomous Driving and AI-driven perception systems , with critical contributions to infrastructure reliability and sensor fusion for automated vehicles. He investigates how conventional road infrastructure interacts with autonomous systems through SLAM technology and deep learning-based environment detection. Publication Trends: His recent works demonstrate a cohesive research trajectory addressing real-world autonomous driving challenges, particularly in vehicle classification using stereo vision (2020), infrastructure-vehicle interaction requirements (2020), and conventional infrastructure reliability validation (2021). These studies emphasize practical implementation of AI in automotive contexts with strong safety considerations. Professional Background: Combines industry experience from Daimler AG (Steer-by-Wire development) and Continental Teves AG (testing rig automation) with academic leadership in the AMEISE research team. His international experience includes academic work in Sweden and China.

Christoph GlockView profile

Professor

• Supply Chain Management
• Production planning and control
• Warehouse management
• +3 more

Christoph Glock is Professor and Head of the Production and Supply Chain Management field at the Department of Law and Economics, Technical University of Darmstadt, a position held since 2018. He previously served as Dean (2020-2022) and Pro-Dean (2018-2020) of the department and maintains an Adjunct Professorship at Toronto Metropolitan University. His academic foundation includes a PhD (2009) and habilitation (2011) from Julius-Maximilians-Universität Würzburg, where his doctoral research focused on supply chain coordination models. Glock's research program centers on mathematical optimization of global supply chains, with six core pillars: Supply Chain Management, Production Planning and Control, Warehouse Management, Environmentally Oriented Production Management, Management of Trading Companies, and Human Factors in Logistics. His work uniquely integrates human behavioral elements into operational decision models while addressing sustainability constraints in production systems, often developing novel algorithms for inventory routing and warehouse automation under real-world uncertainties. His exceptional scholarly impact is evidenced by consistent top rankings in German business research evaluations, including 5th place overall and 1st among professors under 40 in the 2020 Wirtschaftswoche ranking. Key honors include the Bernard J. LaLonde Best Paper Award (2022) from the Council of Supply Chain Management Professionals and the International Journal of Production Research Best Paper Award (2018). Editorial leadership includes Subject Editor roles at Applied Mathematical Modelling and Area Editor for Logistics at Computers & Industrial Engineering . Ranked 5th in 2020 Wirtschaftswoche Business Research Ranking (1st under 40) Bernard J. LaLonde Best Paper Award (2022) Athene Award for Teaching Excellence (2020) Three MIM Conference Commended Paper Awards (2019, 2022) Multiple Best Reviewer Awards from top journals As a highly active academic citizen, Glock serves on 6 editorial boards and has reviewed for over 30 journals including European Journal of Operational Research and Journal of Operations Management , earning recognition as an Outstanding Reviewer. His research group at TU Darmstadt collaborates with industry partners on human-centric warehouse automation projects while advising doctoral candidates in supply chain optimization, though specific student names aren't documented in source materials.

• Cybersecurity
• Blockchain Technology
• Edge Computing
• +3 more

Yu Chen is a researcher affiliated with Binghamton University (College of Engineering and Applied Sciences, Department of Computer Science) and University of Southern California , with additional ties to institutions like Chinese Academy of Sciences and Tsinghua University. Their work spans cybersecurity, blockchain technology, edge computing, and IoT systems , focusing on decentralized architectures for public safety, privacy-preserving surveillance, and defense against deepfake attacks. Primary Affiliation: Binghamton University, NY, USA Previous Affiliation: University of Southern California, CA, USA Yu Chen’s research explores blockchain-enabled security frameworks for IoT networks, UAV systems, and smart cities. Recent projects include the Microverse metaverse model and ELOCESS smart grid management. They specialize in real-time data authentication using Electrical Network Frequency (ENF) signals and edge-based privacy solutions for video surveillance and personal drones. Their 15 most recent publications address digital twin security , decentralized data marketplaces, and lightweight protocols for IoT devices. Key areas include UAV network resilience , smart city surveillance , and metaverse classroom models . Yu Chen collaborates with researchers such as Erik Blasch , Ronghua Xu , and Genshe Chen . No student names or specific awards are listed in the provided data.

• Antenna Engineering
• Radar Technology
• Electromagnetic Fields
• +3 more

Prof. Dirk Heberling is a Universitätsprofessor at RWTH Aachen University, leading the Institute for High Frequency Technology. His research focuses on advanced antenna systems, radar technology, and electromagnetic field exposure assessment in 5G/6G networks. He specializes in high-frequency components, including leaky-wave antennas, reconfigurable intelligent surfaces, and robot-based antenna measurement systems. His work addresses challenges in antenna design, signal processing, and environmental compliance for next-generation communication infrastructure. Key research areas include: Development of wideband antennas for IoT and smart building applications Numerical analysis of near-field antenna measurements and phase recovery techniques Assessment of radio frequency exposure from massive MIMO base stations using digital twins Integration of radar systems with automotive technologies for self-localization and object detection Optimization of antenna arrays to mitigate grating lobes and phase synchronization issues His lab operates a state-of-the-art robot-based mm-wave test system capable of spherical near-field measurements and real-time auralization of aircraft noise. This infrastructure supports both fundamental research and industry collaborations in telecommunications, automotive radar, and environmental monitoring. Current projects emphasize: Exposure modeling for 6G networks considering increased base station utilization Generative adversarial networks for radar data synthesis Calibration techniques for polarimetric radar systems

Giorgio SangiovanniView profile

Professor

• Quantum Materials
• Condensed Matter Physics
• Theoretical Physics
• +3 more

Giorgio Sangiovanni is a Professor and Chair of Computational Quantum Materials at the University of Würzburg, affiliated with the Institute for Theoretical Physics and Astrophysics. His research focuses on theoretical and computational studies of quantum materials, topological phases, superconductivity, and strongly correlated electron systems. Key areas include the development of advanced computational methods for quantum impurity problems, electronic structure calculations, and analysis of correlated materials like kagome metals, topological insulators, and Weyl semimetals. His work explores phenomena such as charge order, van Hove singularities, electron-phonon coupling, and topological edge states. Recent studies highlight strain effects, phonon-driven phase transitions, and the interplay between spin, orbital, and lattice dynamics. He leads the Sangiovanni Group, which employs methods like density-functional theory (DFT) combined with dynamical mean-field theory (DMFT) to study complex electronic systems. Publications emphasize theoretical insights into novel quantum materials, with applications ranging from superconductivity to topological electronics. Advising PhD and Master’s students, his group contributes to advancing computational tools and understanding emergent phenomena in correlated materials.

Tim LandgrafView profile

Professor

• Machine Learning
• Robotics
• Computer Vision
• +4 more

Prof. Tim Landgraf is a Professor of Computer Science at Freie Universität Berlin, affiliated with the Dahlem Center for Machine Learning and Robotics. He specializes in artificial intelligence, robotics, and biohybrid systems, focusing on collective behavior, machine learning, and animal-robot interactions. His work bridges computational methods with biological systems, as seen in studies of honeybee communication and fish behavior. Key research interests include self-supervised learning algorithms, robotic swarm dynamics, and applications of AI in education and healthcare. Prof. Landgraf has led projects like the Biorobotics Lab and contributed to initiatives such as the H2020-funded HIVEOPOLIS. He has been honored with the 'Hochschullehrer des Jahres' (Professor of the Year) award in 2020. Recent publications emphasize biohybrid systems, explainable AI, and counterfactual explanations, reflecting his commitment to interdisciplinary innovation. His courses, such as 'Self-Supervised Learning,' highlight theoretical and practical aspects of cutting-edge machine learning techniques.

• RFID Technology
• Internet of Things (IoT)
• Wireless Sensor Networks
• +3 more

Luca Catarinucci is affiliated with the University of Salento in Lecce, Italy. His research focuses on RFID technology, IoT systems, wireless sensor networks, and antenna design. He has collaborated extensively with researchers like Riccardo Colella and Luciano Tarricone, producing impactful work in smart healthcare systems, energy-autonomous sensors, and 3D-printed electromagnetic devices. His contributions span theoretical advancements in circuit design and practical applications in fields like environmental monitoring and biomedical research. Recent work emphasizes energy-efficient solutions and integration of AI-driven microcontrollers. Key research interests include improving RFID tag performance, developing IoT-aware architectures for healthcare, and advancing additive manufacturing techniques for antenna prototyping. His publications reflect a deep engagement with both hardware innovation and system-level integration of smart technologies. Notable projects include energy-autonomous parking sensors and novel RFID-based medical monitoring systems. Collaborations involve cross-disciplinary efforts in electrical engineering, computer science, and biomedical engineering, with applications ranging from industrial automation to personalized healthcare solutions. While no formal awards are listed, his prolific publication record and repeated funding of experimental platforms indicate significant academic influence.

• Internet of Things
• RFID and antenna design
• Wireless sensor networks
• +5 more

Turke Althobaiti is an active researcher and faculty member whose recent work is concentrated in electrical and computer engineering, with strong interdisciplinary links to computer science and biomedical informatics. Based on co-author affiliations and publication scopes, he is associated with King Saud University, College of Engineering, Department of Electrical Engineering . Research Interests: Design of UHF RFID antennas and Internet-of-Things sensing systems. Localization and communication in smart cities, including non-line-of-sight mitigation and 5G/6G networks. Machine-learning-driven healthcare applications—ranging from COVID-19 detection via chest X-rays to arrhythmia and pneumonia screening. Assistive technologies for the visually impaired, employing contactless RF sensing and AI-based navigation aids. Cloud-security solutions, specifically ensemble intrusion-detection systems against flash-crowd attacks. Cross-disciplinary forays into metabolomics biomarkers and human-animal affective computing. Across 15 recent publications (2019-2025), Althobaiti demonstrates a clear trajectory toward AI-enabled sensing and communication . Workflows combine hardware-level innovations (antennas, RFID tags, USRP radios) with data-level advances (deep learning, ensemble methods, privacy-preserving techniques) to address real-world problems in healthcare, smart cities, and assistive living. Scientific Awards & Recognition: No specific awards are listed in the provided text. Advising & Grants: While no explicit list of students or funded projects is given, the high volume of multi-institutional collaborations and senior-author positions suggest active supervision of graduate researchers and participation in funded projects, most likely supported by the Deanship of Scientific Research at King Saud University or similar Saudi funding bodies. Laboratories & Teams: Though no formal laboratory names are provided, the breadth of hardware prototyping, RF experimentation, and AI model development implies access to well-equipped laboratories in RF/microwave engineering, embedded systems, and computational intelligence.

A. Lee SwindlehurstView profile

Professor

• Signal Processing
• Wireless Communications
• Biomedical Applications
• +3 more

A. Lee Swindlehurst is a Professor and Associate Dean for Research and Graduate Studies at the Henry Samueli School of Engineering of the University of California, Irvine . He is also a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study , where he collaborates on next-generation wireless communications research. Ph.D., Stanford University (Electrical Engineering, 1991) M.S., Brigham Young University (Electrical Engineering, 1986) B.S., Brigham Young University (Electrical Engineering, 1985) Swindlehurst's research focuses on sensor array signal processing for radar, wireless communications, and biomedical applications. His work addresses detection and estimation theory , system identification, and channel modeling, with recent emphasis on massive MIMO systems , low-resolution hardware, and physical layer security . His 2018-2017 publications demonstrate technical advances in precoding algorithms , channel estimation , and ADC/DAC optimization for emerging wireless architectures. IEEE Fellow (2004) IEEE Signal Processing Society Best Paper Awards (2010, 2006) Stephen O. Rice Prize in Communications Theory (2006) IEEE W.R.G. Baker Prize Paper Award (2000) Karl G. Maeser Research Award (2004) His research has produced foundational work on space-time block codes , vector-perturbation techniques , and blind equalization methods that continue influencing modern wireless system design.

Christian MeilickeView profile

Researcher

• Artificial Intelligence
• Knowledge Graphs
• Ontology Matching
• +5 more

Christian Meilicke is a Researcher at the Data and Web Science Group (DWS) within the School of Business Informatics and Mathematics at the University of Mannheim. His work focuses on artificial intelligence, ontology matching, and knowledge graph completion, with recent contributions to rule-based methods and their applications in business process modeling. He is heavily involved in teaching, coordinating courses such as 'Modeling Business Processes' and 'Artificial Intelligence.' His research interests include the integration of open and structured knowledge, probabilistic reasoning frameworks, and improving the efficiency of knowledge base systems. He has explored topics like inductive logic programming, automated debugging of ontologies, and the use of Markov Logic Networks for root cause analysis in IT systems. In terms of trends, his recent publications emphasize combining symbolic rule-based approaches with machine learning for knowledge graph tasks, such as activity recommendation and link prediction. He also investigates explainability in embeddings and temporal forecasting in knowledge graphs. His work often bridges theoretical advancements with practical applications in business informatics and data integration. No scientific awards have been explicitly mentioned. Christian has advised no formal students listed here but has contributed to teaching and mentoring through his courses and tutorials. His research and teaching are closely tied to the DWS Group, which focuses on data-centric AI and semantic technologies.

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

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

• Semantic Web
• Data Integration
• Ontology Matching
• +4 more

Dominique Ritze is a Research Fellow at the Data and Web Science Group of the University of Mannheim. Her research focuses on ontology alignment, semantic web technologies, linked open data integration, and knowledge organization systems. She collaborates with Prof. Dr. Christian Bizer and Prof. Dr. Kai Eckert on projects like InFoLiS II, aiming to advance data integration and semantic web applications. Education: MSc Computer Science (Diplom-Informatikerin) Research Interests: Dominique’s work bridges theoretical and applied aspects of semantic web technologies. Key areas include ontology evaluation frameworks, cross-domain data integration, and the development of tools for provenance tracking and data reuse. She has contributed to methodologies for aligning knowledge organization systems (KOS) and enhancing discovery systems with linked data. Publications Trends: Her articles from 2010-2015 emphasize ontology alignment (e.g., OAEI evaluations), semantic web applications, and data integration techniques. Notable contributions include the ICE-Map visualization for KOS evaluation and the Mannheim Search Join Engine for cross-website table integration. Awards: No scientific awards explicitly listed in the provided texts. Projects & Teams: Active in the Data and Web Science Group, leading projects on web table matching and semantic data integration. Collaborates with global research networks through initiatives like the Ontology Alignment Evaluation Initiative.

Maria SchweigelView profile

Professor

• Artificial Intelligence Algorithms
• Optimization Techniques
• Software Development
• +4 more

Professor Maria Schweigel Prof. Maria Schweigel is a Professor at the Department of Autonomous Systems, Schmalkalden University of Applied Sciences. Her teaching focuses on automation control, electronic control systems, robotics, and embedded systems. She leads the research group 'Eingebettete Diagnosesysteme' (Embedded Diagnostic Systems) and specializes in artificial intelligence algorithms, optimization using genetic and evolutionary methods, and biosignal analysis for anesthesia and sleep studies. Her research spans robotics, embedded systems, image processing, and software development with tools like C/C++, MATLAB/Simulink, and LabView. Key projects include real-time EEG classification for anesthesia monitoring, low-SNR biomedical signal extraction, and SVM-based classification on resource-constrained platforms. She has contributed to international conferences like ECT and IWK TU Ilmenau, focusing on interdisciplinary applications in medical technology and autonomous systems. No scientific awards were explicitly listed in the provided materials. Her advising and grants are not detailed here, but her extensive publication record (2009–2016) demonstrates active involvement in collaborative research with colleagues like Wenzel, Walther, and Baumgart-Schmitt. She co-developed tools such as the Multi-EEG-Viewer and explored wireless biomedical signal transmission for relaxation control systems.

Ingmar IckerottView profile

Professor

• Logistics Management
• Digitalization in Supply Chains
• Smart Glasses Applications
• +3 more

Prof. Dr. Ingmar Ickerott is a faculty member at Osnabrück University of Applied Sciences, affiliated with the School of Management, Kultur und Technik (MKT, Campus Lingen) under the University management department. His academic career spans over two decades, focusing on logistics management, digitalization in supply chains, and smart technology applications like Smart Glasses and Augmented Reality . Academic Background : Diplom-Kaufmann in Business Administration (2001), Ph.D. in Economics (2006). Professional Roles : Senior Project Manager at arvato (2008–2010), Professor since 2010, Dean of MKT since 2019, Vice President for Digitalization since 2019. His research emphasizes logistics innovation , Lean Management , and digital solutions in rural healthcare . Key projects include Land.Digital (2019–2022) and LEAN 4.0 (Erasmus+, 2019–2021). Publications since 2004 cover agent-based simulation , Smart Device economics , and AR in logistics . He actively lectures on topics like Logistics 4.0 and Digital Onboarding . Projects & Grants : Land.Digital : €165,000+ (Erasmus+), 2019–2021. Dorfgemeinschaft 2.0 : €1.46M (BMBF), 2015–2021. Glasshouse : €208,557 (BMBF), 2015–2019.

Oliver MischkeView profile

Researcher

• Side-Channel Cryptanalysis
• Efficient Cryptographic Implementation
• Hardware Security
• +3 more

Dr. Oliver Mischke is an academic researcher focusing on hardware security and cryptographic implementations. He was affiliated with the Chair for Embedded Security at the Horst Görtz Institute for IT Security, Ruhr-University Bochum. His research emphasizes side-channel cryptanalysis, efficient cryptographic algorithms, and secure hardware design. Mischke completed his PhD in Security in Information Technology at Ruhr-University Bochum (2011–2013), with a year abroad at Purdue University (2007–2008). He has held roles as a Security Engineer (ESCRYPT GmbH) and an intern at Qualcomm's Product Security Group. His research interests include FPGA-based cryptographic implementations, fault analysis, and countermeasures against side-channel attacks. Notable contributions involve dynamic logic reconfiguration for FPGA security, glitch-resistant masking schemes, and evaluation of AES countermeasures. Mischke's publications span conferences like HOST, CHES, and IEEE venues, focusing on cryptographic hardware security, timing attacks, and secure embedded systems. His work bridges theoretical cryptography with practical hardware implementations, addressing vulnerabilities in reconfigurable and embedded systems. He has contributed to projects such as the MicroACP crypto-processor and IPSec core designs. His collaborations include prominent institutions and industry partners, reflecting a strong emphasis on applied security solutions.