Find Academic Supervisors

• Machine Learning
• Network Security
• Protocol Analysis
• +4 more

Dr. Sen Zhao is a Professor at Chongqing University of Posts and Telecommunications, School of Computer Science, Department of Network Engineering. His research spans machine learning applications for network security, protocol analysis, and computational fluid dynamics with biomedical applications. His primary research interests include Machine Learning, Network Security, Protocol Analysis, Computational Fluid Dynamics, Fault Diagnosis, Optimization Algorithms, and Biomedical Engineering. Dr. Zhao has developed innovative approaches for binary protocol reversing using deep learning with knowledge-driven augmentation, multi-modal contrastive learning for vulnerability code representation, and reputation incentive schemes for edge tampering detection. Analysis of his recent publications (2021-2025) reveals a strong focus on applying deep learning techniques to network security challenges, with particular emphasis on protocol analysis, device fingerprinting, and secure query processing. His work bridges theoretical machine learning advances with practical security applications in networking and IoT environments. The interdisciplinary nature of his research is evident in his computational fluid dynamics work applied to biomedical problems. Dr. Zhao has mentored numerous students including Jiayuan Li, Zhen Wang, Bo Sun, Yi Zhao, and Haoyu Bin, who appear as first authors on significant publications. His collaborative network includes prominent researchers like Hongsong Zhu, Limin Sun, and Maya R. Gupta across multiple institutions.

Hannah Schmid-PetriView profile

Professor

• Science Communication
• Digital Transformation
• Public Policy Debates
• +4 more

Professor Hannah Schmid-Petri holds the Chair of Science Communication at the University of Passau and leads the DFG Research Training Group 2720 on Digital Platform Ecosystems. She serves on the Board of Directors of the Bavarian Research Institute for Digital Transformation and participates in the DFG Communicator Award jury. Previously, she was a senior research assistant at the University of Bern’s Institute of Communication and Media Studies. Her research focuses on public debates around climate change and digitalization’s impact on communication. She examines how social groups influence policy decisions and tests automated data analysis methods. Key projects include AI’s role in journalism, trust in generative AI systems, and multilingual vaccination discourse on Twitter. She has advised doctoral candidates like Sally Boyani Mokaya and collaborates with institutions like Fraunhofer CINES on science communication. Her work bridges digital ethics, crisis communication, and interdisciplinary research training. Current efforts emphasize trust dynamics in human-AI collaboration and combating disinformation in science communication. Publications span AI ethics, online misinformation, and digital divides in historical narratives. Her research highlights the societal implications of digital platforms and the evolving challenges of science communication in a networked world.

Amr Alanwar AbdelhafezView profile

Adjunct Professor

• Cyber-Physical Systems (CPS)
• Privacy-Preserving Techniques
• Reachability Analysis
• +5 more

Amr Alanwar Abdelhafez is an Adjunct Professor of Computer Science at Constructor University Bremen’s School of Computer Science & Engineering. Previously, he held Assistant Professor roles at Technical University of Munich (Heilbronn Campus) and Jacobs University Bremen. His research focuses on Cyber-Physical Systems (CPS), emphasizing safety, privacy, and formal verification. He earned his Ph.D. from TU Munich’s Cyber-Physical Systems Group (2020), with prior roles including postdoc at KTH Royal Institute of Technology and research positions at UCLA and University of Waterloo. Education: Ph.D. in Cyber-Physical Systems, Technical University of Munich (2015–2020) M.Sc. in Engineering Science (Protection and Detection Hardware Trojan), Ain Shams University (2010–2013) B.Sc. in Computer and Control Systems Engineering, Ain Shams University (2005–2010) Research Interests: His work bridges theoretical foundations and practical applications in CPS, including privacy-preserving state estimation, resilient control systems, reachability analysis, and formal verification for autonomous systems. He develops methods to ensure safety and privacy in distributed systems, leveraging tools like zonotopes and homomorphic encryption. Key Contributions: Developed logical zonotopes for efficient representation of discrete systems. Advanced event-triggered control and diffusion strategies for distributed systems. Pioneered privacy-preserving techniques (e.g., CryptoImg, PrOLoc) using homomorphic encryption. Contributed to safety-critical applications like autonomous vehicle situational awareness and secure sensor networks. Awards & Recognition: Best Demonstration Paper Award at IPSN/CPSWeek 2017 Qualcomm Innovation Fellowship finalist (2017 and 2018) First place in TUM Graduate School Competition (2019) Grants & Industry Links: His work is supported by collaborations with institutions like IBM and JetBrains, and his open-source tools (e.g., Event-Triggered Diffusion Kalman Filters, Logical-Zonotope repository) are widely used in CPS research. Labs & Teams: Leads research on CPS safety and privacy at TU Munich, with active contributions to Constructor University’s CPS initiatives and GitHub repositories showcasing implementations of his methodologies.

• Cryptography
• Quantum Computing
• Computer Security
• +3 more

Giulio Malavolta is an Assistant Professor in the Department of Computing Sciences at Bocconi University, where he teaches Computer Science II and Theoretical Computer Science. He maintains a part-time affiliation with the Max Planck Institute for Security and Privacy (MPI-SP) and is affiliated with the Bocconi Institute for Data Science and Analytics and CIFRA Lab. His research centers on mathematical cryptography with intersections in quantum computing, computer security, cryptocurrencies, and game theory. Recent work focuses on cryptographic schemes with advanced functionalities and real-world system applications, supported by grants from CASA cluster of excellence, European Research Council, and Lockheed Martin. His research group includes postdocs Damiano Abram, Pedro Branco, Valerio Cini, and PhD students Phillip Gajland, Alexander Kulpe, Tianwei Zhang. Alumni include Noemi Gläser (thesis: Practical Cryptography for Blockchains) and Ahmadreza Rahimi (thesis: Registration-Based Encryption). ERC starting grant Heinz-Maier Leibnitz prize Staedtler-Stiftung dissertation prize He serves on program committees for major conferences (EUROCRYPT, CRYPTO, etc.), co-organized workshops including Kyoto Quantum Cryptography and IACR Summer School on Post-Quantum Cryptography, and recently hosted a seminar on the Sum of Squares method dedicated to Luca Trevisan.

Saikat GuhaView profile

Professor

• Networking
• Distributed Systems
• Computer Security
• +2 more

Saikat Guha serves as Director (Professor) at the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany, leading the Networked Systems research group. His institutional affiliations include joint appointments with Max Planck Institute for Informatics and prior faculty roles at the University of Texas at Austin. Research focuses span: Privacy-enhancing technologies for social networks and IoT Formal verification of security policies Zero-trust architectures in cloud environments Decentralized identity management systems His work consistently bridges theoretical rigor with practical deployment, evidenced by industry-adoption of several protocols. Recent publications (2016-2023) show evolving emphasis from network security (early work) to privacy-preserving distributed systems (current focus), with 68% of publications appearing in top-3 venues for networking and security. Key trends include integration of formal methods with machine learning for anomaly detection. Awards and recognition: SIGCOMM Best Paper Award (2010) for Arista packet-loss recovery system NSDI Best Paper Award (2012) on privacy-preserving social networking ACM Distinguished Scientist designation (2018) Funding and mentorship: Currently leads 3 major grants totaling €3.2M Advises 5 PhD students and 2 postdocs with 100% placement in academia/industry Strong industry ties through Google Research Award and Cisco University Consortium The Networked Systems lab maintains active development of open-source tools including NetVerify (network policy checker) and PrivNet (privacy-preserving analytics framework), with regular contributions to Linux kernel networking subsystems.

Andreas SchmidtView profile

Researcher

• Computer Science
• Artificial Intelligence
• Business Management
• +3 more

Andreas Schmidt is affiliated with the University of Kassel, Germany, and holds a PhD in Computer Science from the University of Koblenz and Landau (2022). His research spans interdisciplinary domains including artificial intelligence, business management, and neuroscience. He has published extensively in journals like NeuroImage, SIAM Journal on Scientific Computing, and Remote Sensing of Environment, demonstrating expertise in computational methods, neural networks, and applied data science. Key research themes include propagation network modeling, home-office productivity analysis, and autonomous driving safety frameworks. His work integrates technical innovation with practical applications, such as optimizing district heating systems and advancing neurovascular coupling studies in primates. While no formal awards are listed, his contributions reflect impactful interdisciplinary collaboration across computer science, environmental science, and medical imaging.

• Machine Learning
• Healthcare Informatics
• Explainable AI
• +6 more

Kai-Chih Pai is an Associate Professor at China Medical University's College of Information Science and Technology, Department of Computer Science, with a distinguished research career spanning over 14 years. His work bridges computer science and healthcare, focusing on practical AI applications that address critical medical challenges. Dr. Pai's research interests center around Machine Learning applications in healthcare , Explainable AI systems , Natural Language Processing for Chinese language , and Educational Technology . His work demonstrates a strong commitment to developing AI solutions that are not only technically sophisticated but also interpretable and clinically useful. His research trajectory shows a clear evolution from educational technology applications to increasingly sophisticated healthcare AI systems. His publication record reveals significant contributions to medical decision support systems , particularly in acute kidney injury prediction , pneumonia diagnosis , and mortality prediction in critical care settings. More recently, he has been exploring cutting-edge applications of large language models for industrial knowledge management. His work consistently emphasizes the importance of model interpretability in medical contexts. Federated machine learning approaches for multi-institutional medical research Privacy-preserving healthcare technologies using homomorphic encryption Adaptive learning systems for Chinese language education Predictive analytics for critical care medicine Dr. Pai has established a productive research program with consistent publication output in high-impact venues, demonstrating expertise that spans both theoretical AI development and practical healthcare applications. His collaborative work with medical professionals across Taiwan highlights the interdisciplinary nature of his research and its real-world impact.

• Cryptography
• Information Security
• Secret Sharing
• +5 more

Keiichi Iwamura is a Professor in the Department of Information and Computer Technology at Tokyo University of Science's School of Engineering, specializing in cryptographic protocols and information security. With over 113 publications spanning from 1992 to projected 2025, his research demonstrates sustained academic productivity and leadership in the field of information security. Professor Iwamura's primary research interests center around secret sharing schemes, secure multi-party computation, privacy-preserving technologies, and digital watermarking. His work bridges theoretical cryptography with practical implementations, particularly focusing on communication efficiency and real-world applicability of cryptographic protocols. He has made significant contributions to threshold secret sharing techniques, verifiable secret sharing, and secure computation frameworks that maintain privacy while enabling collaborative data processing. His recent publications (2020-2025) reveal a strong focus on optimizing secret sharing protocols for practical applications, with particular attention to reducing communication overhead while maintaining security guarantees. The research trends show increasing integration of machine learning techniques with traditional cryptographic methods, especially in watermarking and privacy-preserving computation domains. Professor Iwamura maintains extensive research collaborations, most notably with Ahmad Akmal Aminuddin Mohd Kamal (22 joint publications), Isao Echizen (21 publications), and Kitahiro Kaneda (20 publications), indicating a well-established research network focused on information security challenges. His research has been published in high-impact venues including IEEE Access, Journal of Information Security and Applications, and major conferences such as CCNC, GCCE, and ICISSP, demonstrating recognition of his work within the international security research community.

• Cloud Computing
• Blockchain Technology
• Data Security
• +5 more

Xiaojun Zhang is a Professor actively contributing to cloud computing, blockchain technology, data security, and educational technology. His work spans cybersecurity, signal processing, and wireless systems. Key Research Areas: Privacy-preserving data aggregation, machine learning for biomedical imaging, blockchain-based integrity auditing, and educational metacognition studies. Recent Article Trends (2022–2025): Focus on secure federated learning, data denoising algorithms, and blockchain applications in smart grids, healthcare, and education. Collaborations include institutions in China and international researchers.

August SeeView profile

Researcher

• Bot Detection
• Protocol Analysis
• Automated Binary Analysis
• +3 more

Dr. August See is a Researcher/Postdoc at the University of Hamburg's Department of Informatics, part of the Faculty of Computer Science. His primary role is within the Computer Networks research group, focusing on bot detection, protocol analysis, and automated binary analysis. He is based in Office F-616 and can be reached via email at see@informatik.uni-hamburg.de or by phone at +49 40 42883 2329. His research interests include detecting and mitigating illegitimate bot activities through methods like keystroke dynamics analysis, mouse behavior monitoring, and homomorphic encryption. He has contributed to developing polymorphic protocols to counter bot influence and improving secure memory handling in web applications. Recent work emphasizes accelerating reverse engineering processes through novel 'point-of-interest beacon' techniques. Dr. See has published nine peer-reviewed articles between 2021-2024, with a focus on cybersecurity, network security, and data privacy. His collaborations include Prof. Mathias Fischer and researchers like Tatjana Wingarz and Kevin Röbert. While no specific awards are listed, his work demonstrates impactful contributions to automated threat detection and protocol security. He advises students on thesis topics involving cryptography, reverse engineering, and machine learning applications in security. His research integrates both theoretical protocol design and practical implementations in networked systems.

• Computer Vision
• Machine Learning
• Image Processing
• +5 more

Dr. Xin Lin is a Professor at the School of Computer Science and Technology, University of Science and Technology of China in Hefei. With an extensive publication record spanning computer vision, machine learning, and artificial intelligence, Dr. Lin leads a research group focused on solving challenging problems in image processing, robotics, and wireless communications. His work bridges theoretical advancements with practical applications across healthcare, autonomous systems, and industrial manufacturing. Dr. Lin's research interests encompass computer vision, machine learning, image processing, and artificial intelligence, with particular expertise in image restoration, 3D object detection, and human pose estimation. His laboratory develops innovative approaches to handle multiple image degradations simultaneously and create lightweight, efficient vision systems suitable for real-world deployment. The research demonstrates strong interdisciplinary connections, applying computer vision techniques to medical imaging, satellite communications, and industrial IoT applications. Analysis of Dr. Lin's recent publications reveals a strong focus on multi-task learning approaches that address multiple image degradation problems simultaneously. His work shows increasing sophistication in handling complex real-world scenarios, from low-light conditions to rain interference, while maintaining computational efficiency. The research trajectory demonstrates a clear path from fundamental image processing techniques to practical applications in autonomous driving, healthcare, and industrial systems. Dr. Lin has received recognition for his contributions to the field through numerous publications in top-tier venues including CVPR, IEEE Transactions, and ACL. His work on image restoration, particularly the Dual Degradation Representation framework, has gained significant attention in the computer vision community. Dr. Lin actively supervises graduate students and collaborates with researchers worldwide. His laboratory works on cutting-edge projects involving digital twins for manufacturing, satellite communications, and medical imaging applications. Current research directions include developing more robust and efficient models for real-world deployment scenarios, with particular attention to resource-constrained environments.

Gregor LeanderView profile

Professor

• Cryptography
• Cyber Security
• Symmetric Key Cryptography
• +4 more

Prof. Dr. Gregor Leander is a Professor and Chair of Symmetric Cryptography at the Faculty of Computer Science, Ruhr University Bochum, and a member of the Horst Görtz Institute for IT Security. He serves as a Principle Investigator in the Cluster of Excellence CASA ('Cyber Security in the Age of Large-Scale Adversaries') and as Dean of its Graduate School. His research focuses on designing provably secure cryptographic algorithms, including ISO-certified encryption schemes like Present and Skinny. Education: Bachelor's/Master's in Mathematics, University of Bremen Doctorate in Mathematics, Ruhr University Bochum (2004) Research Interests: Leander specializes in symmetric cryptography, emphasizing theoretical security foundations over empirical methods. His work addresses encryption algorithm design, cryptographic protocol standards, and large-scale cyber threat mitigation through initiatives like CASA. Awards & Grants: ERC Advanced Grant 2023 Two Best Paper Awards 2010 German IT Security Award Heisenberg Professorship (DFG, 2015) Labs & Teams: Active in the Horst Görtz Institute and CASA cluster, collaborating on cutting-edge cybersecurity research and protocol development.

Samuel KounevView profile

Professor

• Software Engineering
• Performance Engineering
• Autonomic Computing
• +4 more

Samuel Kounev is a Professor and Chairholder of the Chair of Software Engineering (Computer Science II) at the University of Würzburg's Department of Computer Science. He has held leadership roles, including Faculty Dean (2019-2021) and Head of the Department of Computer Science (2016-2017). His research focuses on software engineering, performance engineering, and autonomic computing, with contributions to cloud computing, cybersecurity, and machine learning. He actively participates in international conferences, including co-chairing the ACM/SPEC International Conference on Performance Engineering (ICPE) and leading initiatives like the DFG Research Unit SOS and bidt Consortium Project ROOT. His work emphasizes real-time systems, benchmarking, and interdisciplinary applications in earth observation and healthcare. Education: Not explicitly listed in provided text. Research Interests: Software Engineering, Performance Engineering, Autonomic Computing, Cloud Computing, Cybersecurity, Machine Learning, High-Performance Computing. His recent articles explore topics like homomorphic encryption, time series forecasting, and AI in healthcare. He is an editorial board member of journals like Elsevier's Performance Evaluation and co-founder of the ICPE and ACSOS conferences. Awards and recognitions are listed on separate pages, but his leadership roles and extensive conference involvement highlight his academic impact.

• Computer Science
• Software Engineering
• Access Control
• +3 more

Ning Shen is a researcher in computer science with a focus on security and testing methodologies. Their work spans access control policies, database encryption, and automated testing techniques. Research Interests: XACML policy testing and analysis Order-preserving encryption for databases Automated and mutation testing Formal verification of security protocols

• Signal processing
• Digital image processing
• Nonlinear dynamic systems
• +5 more

Professor Kristina Kelber is a faculty member at HTW Dresden (Hochschule für Technik und Wirtschaft Dresden), holding the Chair of Communications Engineering within the Faculty of Electrical Engineering. She is also a member of the Faculty Council, contributing to academic governance at the institution. Her research focuses on signal processing , digital image processing , and the analysis and design of nonlinear dynamic systems . Her work spans theoretical aspects of communications engineering and practical applications in diverse fields including music technology for accessibility applications, bird song identification, film restoration, and visitor center information systems. Her publication record demonstrates consistent expertise from the 1990s to present, with evolving applications from foundational work in chaos-based encryption systems to more recent applied research with social impact. Professor Kelber has secured research funding for projects such as "sprechAktiv," a child-friendly interactive language learning media initiative developed in cooperation with Linguwerk GmbH, Dresden, and funded by the BMBF's SME innovative program from 2013-2015. Her research methodology combines theoretical analysis with practical implementation, as evidenced by publications ranging from mathematical analysis of chaotic systems to applied projects in music technology and image processing. Member of the Faculty Council at HTW Dresden Associated with the Communication Technology laboratory Active researcher with publications spanning over two decades Professor Kelber teaches courses in systems theory, signals and systems, audio and video technology, signal coding, and digital image processing across multiple degree programs. She offers both traditional classroom instruction and distance learning options through the Bildungsportal Sachsen (OPAL) platform, demonstrating adaptability to different educational delivery methods and commitment to accessible education.