Find Academic Supervisors

• Surgical Robotics
• Surgical Intelligence
• Surgical Mechatronics
• +3 more

Prof. Mohammad Ali Nasseri is a Professor of Surgical Robotics at the Technical University of Munich (TUM) and Founding Director of the Medical Autonomy and Precision Surgery (MAPS) research group within the TUM School of Medicine and Health. He holds an adjunct professorship in the Department of Medical Engineering at the University of Alberta. His research focuses on surgical robotics, surgical intelligence, and medical AI, with key contributions in surgical mechatronics, medical imaging, and visualization. Nasseri leads the MAPS group, which develops advanced technologies for precision surgery and robotic systems. Notable achievements include coordinating the ForNeRo project (~EUR 2M) and receiving awards such as the Best Medical Robotics Paper Award (ICRA 2024 finalist), Best Short Paper (Medical Visualization VCBM 2019), and the Robot Dalen Innovation Award (2015). His work on robot-assisted microsurgery and real-time surgical monitoring systems has advanced medical robotics safety and precision. Education: Ph.D. in Engineering (details not specified). Affiliations: TUM School of Medicine and Health, MAPS Research Group, University of Alberta (adjunct). Research emphasizes interdisciplinary innovations at the intersection of robotics, AI, and healthcare, with a focus on translating technical advancements into clinical applications. Recent projects include Envibroscope for environmental motion monitoring and Colibri5 for vitreoretinal surgery tracking. Grants & Projects: Bavarian Research Foundation (ForNeRo), TUM excellence programs. Nasseri’s labs and teams collaborate internationally on surgical autonomy, precision surgery tools, and medical AI integration. His work bridges fundamental engineering research with clinical practice in minimally invasive procedures.

Jan KretinskyView profile

Professor

• Verification
• Synthesis
• Probabilistic Model Checking
• +7 more

Jan Kretinsky is a full professor at the Faculty of Informatics, Masaryk University, Brno, Czech Republic, and holds an affiliated professorship at the Chair for Foundations of Software Reliability and Theoretical Computer Science at Technical University of Munich (TUM), Germany. He specializes in formal methods, focusing on verification and synthesis of probabilistic systems, applications of machine learning in verification, and explainable AI. His research bridges theoretical foundations with practical tools, including the Automata Tutor teaching platform and the Rabinizer tool for LTL-to-automata translation. Education: PhD from TU Munich (advisor: Javier Esparza) and Masaryk University (advisor: Antonín Kučera), both with distinction. Previously an IST Fellow at IST Austria and a tenure-track assistant professor at TUM. Research interests span verification of neural networks, probabilistic model checking, temporal logics, and automata theory. He leads the LiVe Lab and collaborates on EU projects like the ERC grant InOVationCS. Active in organizing workshops (LiVe series, Dagstuhl seminars) and serves on program committees for conferences like CONCUR, LICS, and TACAS. Teaching includes courses on complexity, automata theory, and quantitative verification at both institutions. Supervised numerous PhD and master's students, with notable projects in decision tree controllers, runtime monitoring, and attack-defense analysis. Key grants include DFG projects (e.g., GOPro, ConVeY) and EU initiatives. Tools developed: Automata Tutor, Rabinizer series, dtControl, SeQuaiA, and QUADTool. Research highlights include PAC guarantees for MDPs, semantic abstraction for motion planning, and formal methods for cybersecurity.

• Neuromorphic Computing
• Reservoir Computing
• Reinforcement Learning
• +3 more

Prof. Abigail Morrison is a Professor and Group Leader of the Computation in Neural Circuits group at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich. Her work focuses on advancing neuromorphic computing, reservoir computing, and spiking neural network simulations. She leads development of the NEST simulator and NESTML modeling language, tools critical for large-scale brain modeling. Key research areas include: Neuromorphic hardware-software co-design Biophysically plausible neural network models GPU-accelerated simulation frameworks Multi-scale brain co-simulation techniques Applications in embodied AI and neuroscience Her lab contributes to the European EBRAINS infrastructure and has pioneered methods for parallel GPU-based network construction. Recent work explores topographic neural circuit architectures for signal processing and reinforcement learning in neuromorphic systems. Notable achievements include: Development of NESTML (v8.0+) ODE-toolbox for ODE solver selection Co-design of HNC neuromorphic compute nodes Advances in dendritic computation modeling Current efforts emphasize exascale computing readiness, neuromorphic system validation, and bridging biological plausibility with computational efficiency in neural network simulations.

• AI for Networking
• Edge Computing
• Federated Learning
• +4 more

Prof. Xiaoming Fu is a Professor at the Institute of Computer Science, University of Göttingen, and Head of the Computer Networks Group. He also holds a secondary membership in the Center for Statistics. His research focuses on AI-driven networking, edge computing, federated learning, and video analytics. He teaches courses such as 'AI-Empowered Networking and Mobile Communications' and oversees multiple seminars and internships on topics like smart cities and network optimization. His work spans technical innovations in multi-agent systems, low-latency services, and resource-efficient machine learning. Recent articles highlight contributions to neural-optimized video streaming, privacy-preserving MARL, and cross-modal social media analysis. He collaborates on interdisciplinary projects involving mobility data, socioeconomic analysis, and quantum networks. Prof. Fu’s research integrates reinforcement learning, network architecture design, and distributed systems to address challenges in 5G/6G, IoT, and smart cities. His lab develops solutions for edge-cloud orchestration, video quality adaptation, and resilient resource allocation, with applications in both academia and industry.

• Software Engineering
• Distributed Systems
• Cloud Computing
• +4 more

UnivProf. Dr. Jens Grabowski is a full professor at the Institute of Computer Science at Georg-August-Universität Göttingen, leading the Software Engineering for Distributed Systems group. His primary roles include teaching advanced courses on software engineering, software testing, and parallel computing, as well as supervising practical internships in these domains. His research focuses on software engineering methodologies, cloud computing architectures, static analysis tools, and model-driven approaches to system design. Education details are not explicitly listed, but his academic position implies a PhD in Computer Science. His work spans both theoretical contributions (e.g., defect prediction models, developer behavior studies) and applied systems (e.g., cloud resource management frameworks, testing tool development). He is actively involved in open-source software research, particularly analyzing Apache projects and Python ecosystems. Key research themes include: Model-driven cloud orchestration using standards like TOSCA and OCCI Static analysis tool evaluation and warning management Empirical studies on software evolution and developer practices Simulation-based approaches for system validation His recent publications (2021-2025) demonstrate sustained contributions to cloud computing infrastructure, static analysis tool efficacy, and software testing methodologies. Notable frameworks developed include MoDMaCAO for cloud application management and the SmartShark ecosystem for mining software repositories. Grants and advising activities are not explicitly detailed in the provided texts, but his leadership in multiple research groups implies significant involvement in academic funding and PhD supervision. He maintains collaborations in distributed systems, cloud computing, and software engineering education.

Kalman GraffiView profile

Professor

• Cybersecurity
• Peer-to-Peer Networks
• Opportunistic Networks
• +4 more

Prof. Kalman Graffi is a Professor of Networks, Communication Systems, and Cybersecurity at Bingen University of Applied Sciences. He holds a Dr.-Ing. from TU Darmstadt and has held academic roles at institutions like the University of Düsseldorf and University of Paderborn. Previously, he was a Principal Scientist at Honda Research Institute Europe GmbH (2019–2022). His research focuses on secure, scalable networks (e.g., overlay networks, robot swarms) and privacy-preserving computing. Notable contributions include work on peer-to-peer frameworks (LibreSocial), threat modeling, and fog computing optimizations for IoT. Awards include the 'Young Scientist of the Year 2014' (Academics.de) and memberships in AGYA and Germany's Young Academy of Sciences. He has authored over 90 publications and supervised 175+ student theses. Key projects include BMBF-funded initiatives on decentralized communication platforms and DFG-supported research on opportunistic networks. His work also bridges technical innovation with societal impact, including collaborations with activists in the Arab world.

• Artificial Intelligence
• Networked Systems
• Distributed Computing
• +1 more

Dr. Federico Mancinelli is a researcher at the University of Bonn, affiliated with the CAIAN (Center for Advanced Intelligence and Networked Systems) team. He is based at Am Propsthof 49, 53121 Bonn, and can be reached via email at fmancine@uni-bonn.de or by phone at +49 228 73695-30. His office is located in Room 4.03. His research is centered on advanced intelligence and networked systems, suggesting strong involvement in interdisciplinary areas combining artificial intelligence with distributed and cyber-physical infrastructures. The CAIAN team likely operates at the intersection of computer science and engineering, focusing on next-generation intelligent systems. Although no specific publications or projects are detailed in the provided text, the thematic focus indicates engagement with cutting-edge research in scalable AI architectures and networked computation. Dr. Mancinelli has not been listed with any scientific awards in the available information. There is no public information provided regarding student supervision, grants, or formal educational background within the scraped content. The research group CAIAN appears to be an active academic team at the University of Bonn, potentially involving collaboration across departments or institutes focused on intelligent systems and networking technologies.

Martina KlausnerView profile

Professor

• Digital Anthropology
• Science and Technology Studies (STS)
• Ethnographic Methods
• +11 more

Professor Dr. Martina Klausner is a full-time faculty member at the Institute for Cultural Anthropology and European Ethnology, Goethe University Frankfurt am Main, within the Faculty of Linguistics, Cultures and Arts. She holds the professorship in Digital Anthropology and Science and Technology Studies, leading major interdisciplinary research initiatives including the Research Training Group Fixing Futures. Technologies of Anticipation and the Center for Critical Computational Studies. Her educational background includes studies in European Ethnology and Cultural Studies at Humboldt University in Berlin, where she also completed her PhD. Her research agenda centers on digital transformation processes in governance, healthcare, and urban environments, with a strong methodological focus on digital and collaborative ethnographic methods. Her research interests span Digital Anthropology , Science and Technology Studies (STS) , datafication in urban governance , AI regulation , digital health technologies , and participation rights of people with disabilities . She investigates how digital data infrastructures shape political processes, such as in the Verkehrswende (transport transition) in Frankfurt, and how AI is regulated across sectors like finance. Her work emphasizes the political dimensions of data production and the ethical, legal, and infrastructural challenges of digital technologies. Her recent publications from 2022–2024 reveal a strong trend toward critical data studies , digital ethnographic methods , and interdisciplinary governance of AI . Articles such as 'A More-than-digital Anthropology' and 'Digitalität und Ethnografie' advocate for methodological innovation in ethnography, while others analyze AI in financial systems and data politics in urban mobility, reflecting a cohesive research trajectory at the intersection of technology, power, and participation. She is actively involved in scientific leadership, serving as PI of major research groups and as an ERC Panel Member for Social Sciences & Humanities. She also contributes to academic discourse through editorial roles and collaborative publications. Martina Klausner supervises doctoral researchers, including Matthias Kloft, whose dissertation builds on her research on AI regulation in finance. She has secured significant research funding, including DFG and ZEVEDI grants, and leads collaborative projects involving law, computer science, and philosophy. Her work is deeply embedded in interdisciplinary networks, including the Laboratory: Anthropology Environment | Human Relations. She is affiliated with the Laboratory: Anthropology Environment | Human Relations , a long-standing research collective she was part of during her early career, and continues to engage in collaborative and co-laborative research models. Her current DFG-funded project on data politics in Frankfurt exemplifies her ongoing commitment to ethnographic inquiry into digital governance and civic participation.

• Digital Piracy
• Information Security
• Computer Security
• +6 more

Rahul Telang is a Professor of Information Systems and Management at the H. John Heinz III School of Public Policy and Management at Carnegie Mellon University. His work spans digital piracy , computer security , and the economics of information systems , with a focus on policy implications of technology. His research examines the interplay between online piracy and cybersecurity , including how malware propagates through infringing sites. He also investigates privacy regulation (e.g., app privacy labels ), search engine advertising , and the economics of software vulnerabilities . Recent papers analyze artificial intelligence in copyright policy and workforce analytics using occupational skill embeddings . While Telang’s articles frequently use empirical methods and natural experiments , no formal scientific awards are listed in the available data. His collaboration network includes scholars from Carnegie Mellon, Emory, Chapman University, and Indian School of Business, covering topics like ride-hailing congestion and data breach impacts . No student advising or lab affiliation details are explicitly mentioned.

• Signal Processing
• Medical Imaging
• Computer Vision
• +4 more

Benoît Macq is a distinguished professor at the ICTEAM Institute , Université catholique de Louvain, Belgium. With over 350 publications spanning 1990–2025, his work bridges signal processing , medical imaging , machine learning , and data security . Key collaborators: Christophe De Vleeschouwer Simon K. Warfield Jean-François Delaigle Mathieu De Craene Research interests include: Adaptive algorithms for real-time model deployment and domain adaptation 3D reconstruction and medical image segmentation for radiation therapy Security in blockchain-based distributed learning systems Transformers for EEG classification and proton radiography Recent publications focus on foundation models in cytology and remote sensing, holonic multi-agent systems for VR, and secure codestreams for UAV object detection. His work emphasizes scalable architectures and privacy-preserving techniques in dynamic environments. Advising: Dani Manjah Antoine Aspeel Maxime Zanella

• GNSS (Global Navigation Satellite Systems)
• Indoor Positioning Systems
• Pseudolite Technology
• +7 more

Baoguo Yu is a Professor at the Department of Navigation Science and Technology within the School of Geodesy and Geomatics at Wuhan University. He has established himself as a leading researcher in the field of navigation and positioning systems, with over 70 publications spanning from 2016 to 2025 across prestigious journals including IEEE Transactions on Instrumentation and Measurement, Sensors, and IEEE Access. His research interests primarily focus on GNSS (Global Navigation Satellite Systems), indoor positioning technologies, pseudolite systems, and signal processing for navigation applications. Professor Yu's work demonstrates a strong emphasis on practical implementations, particularly in challenging environments where traditional GNSS signals are degraded or unavailable. His recent publications reveal a growing integration of machine learning techniques with traditional navigation approaches, reflecting the evolving nature of the field. Analysis of his 15 most recent publications shows a clear research trajectory toward high-precision positioning solutions, with particular attention to indoor navigation challenges, LEO satellite navigation augmentation, and robust positioning under interference conditions. His work spans theoretical algorithm development to practical implementations for smartphones, unmanned vehicles, and specialized navigation equipment. Professor Yu maintains extensive collaborations with researchers across China, particularly with scholars from Wuhan University and other prominent Chinese institutions. His frequent co-authors include Lu Huang, Xingli Gan, Heng Zhang, and Chuanzhen Sheng, suggesting well-established research teams working on complementary aspects of navigation technology. His research has significant applications in autonomous vehicles, pedestrian navigation, emergency response systems, and any domain requiring precise positioning where GPS signals are unreliable. The consistent publication output in high-impact journals demonstrates his active research program and continued contributions to advancing navigation science.

• Software Engineering
• Agile Methods
• Embedded Systems
• +3 more

Adilson Marques da Cunha is a Professor at the Brazilian Aeronautical Institute of Technology (ITA), with a focus on software engineering and computational systems. His career spans academic research and development in embedded systems, real-time applications, and machine learning methodologies. Affiliation: Brazilian Aeronautical Institute of Technology Research Interests: Dr. da Cunha's work centers on agile software development , embedded system optimization , and numerical integrator frameworks . He has contributed to deep reinforcement learning for robotics and recommender systems for news, while also exploring climate prediction models using big data. Publication Trends : 2025 papers focus on universal numerical integrators and Python testing frameworks; 2024 work involves autonomous air navigation; 2022 studies include humanoid robotics and climate modeling

• Machine Learning
• Cloud Computing
• Fault Diagnosis
• +3 more

Chao Yin is a researcher at Shanghai University , Department of Computer Engineering and Science. His work spans multiple domains including Machine Learning, Cloud Computing, Fault Diagnosis, and Supply Chain Optimization. Key research areas: Machine Learning , Cloud Computing , Quantum Computing , Supply Chain Systems , Network Security Scientific Contributions (2024-2025): Developed heterogeneous graph neural networks for automotive supply chain analysis Created MSDF-VAE cloud-edge fault diagnosis framework using transfer learning Proposed quantum metrology methods with Heisenberg-limited precision Designed LARP pseudonym protocol for V2X communication Optimized fog computing resource scheduling with hybrid metaheuristics Prior Work (2012-2023): Contributed to fluid animation feature preservation from single images Developed label distribution learning for facial age estimation Designed erasure coding storage systems for big data Created multi-agent manufacturing networks in cloud environments

Henry HoffmannView profile

Professor

• Self-aware Computing
• Adaptive Computing
• Computer Systems
• +5 more

Henry Hoffmann is Professor and Liew Family Chair of the Department of Computer Science at the University of Chicago. He serves as Chair of the department and leads research in self-aware and adaptive computing systems. His work bridges traditional computer systems areas with control theory and machine learning to create systems that automatically adapt to meet high-level goals. Hoffmann received his Ph.D. from MIT in 2013 under advisors Anant Agarwal and Srinivas Devadas, with his dissertation titled "SEEC: a framework for self-aware management of goals and constraints in computing systems." He earned an S.M. from MIT in 2003 and a B.S. with highest honors and distinction from UNC-Chapel Hill in 1999. Hoffmann's research focuses on developing self-aware computing systems that understand high-level goals and automatically adapt their behavior to meet those goals optimally. His recent work has shifted toward applying these techniques to control machine learning and AI systems, building learning systems that dynamically adapt their internal structure and resource usage to meet accuracy, energy, performance, and security goals at inference time. His interdisciplinary approach combines operating systems, computer architecture, control theory, and machine learning. Analysis of Hoffmann's recent publications reveals a clear trajectory toward increasingly sophisticated applications of self-aware computing principles. His work has evolved from foundational resource management to cutting-edge applications in AI/ML systems, quantum computing, and security. The publications demonstrate a consistent theme of using control theory and machine learning to create adaptive systems that optimize multiple competing objectives like performance, energy efficiency, and reliability. Recent papers show expanding applications into large language models, quantum algorithms, and privacy-preserving techniques. Presidential Early Career Award for Scientists and Engineers (PECASE) 2019 DOE Early Career Award 2015 Samsung Security Hall of Fame recognition IEEE Micro Top Picks Honorable Mention awards FSE Test of Time Honorable Mention ASPLOS Hall of Fame recognition Hoffmann has mentored numerous PhD and Master's students who have gone on to successful careers in academia and industry. His research has secured over $19 million in funding for the University of Chicago. He co-founded Config Dynamics in 2019 to commercialize aspects of his self-aware computing research. His work has practical applications across data centers, edge computing, AI systems, and quantum computing. Hoffmann leads the SEEC (Self-aware, Energy-Efficient Computing) research group at the University of Chicago. The group focuses on developing frameworks and techniques for building self-aware computing systems that can dynamically adapt to changing conditions and requirements. The group maintains strong collaborations with industry partners and other academic institutions, particularly in the areas of quantum computing, AI systems, and energy-efficient computing.

Martina ZitterbartView profile

Professor

• Multimedia Communication Systems
• Mobile and Ubiquitous Communication
• Ambient Technologies
• +7 more

Martina Zitterbart is a Professor of Computer Science at the Karlsruhe Institute of Technology (KIT) , with a career spanning over 30 years in telematics research. She leads the Institute of Telematics , focusing on multimedia communication systems , mobile networking , and wireless sensor networks . Current C4 Professor at KIT since 2001 PhD in Computer Science (University of Karlsruhe, 1990) Visiting scientist at IBM Research (USA/Switzerland, 1989-1992) Her research now integrates artificial intelligence into network security and 6G automation . Key projects include: KIWI : Federated machine learning for cross-domain attack detection Open6GHub : 6G infrastructure development (€66.8M BMBF grant) 6G-ANNA : Network automation for next-gen mobile systems Recent publications focus on: DDoS attack detection through machine learning QUIC protocol performance in long-term use energy packet transmission for smart grids autonomic network management She has received multiple awards including: Alcatel SEL Research Prize (2002) Best Paper Awards (EI.A 2024, NoF 2023) Teaching Excellence Recognition (2003, 2008) As a member of IEEE, ACM, and the German Society for Informatics, she actively contributes to academic discourse through conferences like SIGCOMM and workshops on blockchain technology.