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Nils Fleischhacker is an Assistant Professor for Cryptography at Ruhr University Bochum, where he leads the Theoretical Cryptography group within the Faculty of Computer Science. His research focuses on foundational aspects of cryptography with particular emphasis on zero-knowledge proofs, digital signatures, and secure computation. Prior to joining Ruhr University, he held postdoctoral positions at Johns Hopkins University and Carnegie Mellon University. Dr. Fleischhacker received his PhD in Computer Science from Saarland University in February 2017, advised by Dominique Schröder. During his doctoral studies, he was a research intern at Microsoft Research with Chris Brzuska and a research visitor at the University of Maryland, College Park with Jonathan Katz and Dana Dachman-Soled. His research spans theoretical cryptography with significant contributions to zero-knowledge proofs, multi-signature schemes, property-preserving hash functions, and security proofs for cryptographic primitives. Fleischhacker's work often addresses fundamental questions about the limits and possibilities of cryptographic constructions, with particular attention to black-box separations and lower bounds. His recent publications demonstrate a strong focus on lattice-based cryptography and post-quantum secure protocols. Fleischhacker's publications over the past five years reveal a consistent research trajectory focused on improving the efficiency and security of cryptographic primitives, with particular emphasis on signature schemes, zero-knowledge protocols, and secure computation frameworks. His work frequently appears in top-tier cryptography venues including CRYPTO, EUROCRYPT, and CCS. Dr. Fleischhacker actively mentors PhD students, with numerous successful graduations spanning from 2010 to 2024. His former PhD students include Önder Askin (2024), Floyd Zweydinger (2023), and Lars Schlieper (2022), among others. His research is supported through various academic channels and collaborations. He is affiliated with several prominent research organizations including the Horst Görtz Institute (HGI) for Information Security, the DFG Excellence Cluster CASA, the EU Marie Curie Network QSI, and the International Association for Cryptologic Research (IACR). These affiliations provide a strong institutional framework for his theoretical cryptography research.

• Cryptography
• Theoretical Computer Science
• Zero-Knowledge Proofs
• +5 more

Dr. Rachel Player is a Senior Lecturer in the Department of Information Security at Royal Holloway, University of London . Her research focuses on post-quantum cryptography, lattice-based cryptographic schemes, homomorphic encryption, and quantum algorithm applications in cryptanalysis. She holds a PhD in Information Security from Royal Holloway, supervised by Prof. Carlos Cid and Prof. Sean Murphy. Education: PhD in Information Security, Royal Holloway, University of London (supervisors: Prof. Cid & Prof. Murphy) Research Interests: Rachel explores cutting-edge areas in cryptography with a focus on privacy-preserving technologies. Her work bridges theoretical advancements and practical implementations, particularly in homomorphic encryption and post-quantum security protocols. Recent efforts emphasize applying quantum algorithms to cryptanalytic challenges. Professional Activities: Rachel actively contributes to standards development in cryptography, including organizing HomomorphicEncryption.org meetings and participating in ISO/IEC JTC 1/SC 27/WG 2 (cybersecurity standards). She also serves as an editor for the Designs, Codes and Cryptography journal. Labs/Teams: Collaborations include the PolSys team at Sorbonne Université (Paris) and the EU H2020 PROMETHEUS project. Current research is anchored in Royal Holloway's Information Security Department.

• Post-Quantum Cryptography
• Lattice-Based Cryptographic Schemes
• Homomorphic Encryption
• +3 more

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

• Programming Languages
• Compilers
• Program Analysis
• +5 more

Wenguang Chen is a researcher affiliated with Tsinghua University and Pengcheng Laboratory , specializing in computer science and high-performance computing . His work bridges theoretical advancements with practical applications in domain-specific languages , parallel programming , and machine learning . Research Interests include: Development of modular DSLs for numerical methods (e.g., Mat2Stencil) Performance optimization in distributed and parallel systems Compiler frameworks for privacy-preserving AI (e.g., FHE-based neural network inference) Graph algorithms scaling to trillion-edge datasets Applications of Rust in memory-safe pointer analysis Recent Publications span 2014–2025, focusing on: Parallelization strategies for supercomputing Compiler automation tools Extreme-scale data processing Performance variance diagnosis in production environments

• High-Performance Computing
• Parallel Programming
• Domain-Specific Languages
• +3 more

Mathias Fischer is Professor for Computer Networks at the University of Hamburg since December 2021, affiliated with the MIN Department of Informatics. He previously served as an assistant professor at Universität Hamburg (2016-2021), University Münster (2015-16), and held postdoctoral positions at the International Computer Science Institute/UC Berkeley (2014-15) and the Center for Advanced Security Research Darmstadt/TU Darmstadt (2012-14). His educational background includes a PhD in Computer Science from TU Ilmenau (2012) and a diploma in Computer Science from the same institution (2008). He also served as Head of Data Literacy Education in IT Support at the University of Hamburg's ISA Center. Professor Fischer's research spans critical areas of modern network infrastructure, with particular emphasis on IT and network security , resilient distributed systems , and network monitoring . His work addresses fundamental challenges in cybersecurity including botnet monitoring, intrusion detection, and critical infrastructure protection. His research group actively investigates P2P networks and develops innovative approaches to network security that balance functionality with privacy preservation. Analysis of his recent publications reveals a strong focus on privacy-enhancing technologies, network security protocols, and resilient distributed systems. His research trajectory shows increasing attention to practical implementations of security solutions for edge computing environments, digital twin networks, and time-sensitive networking applications. The work demonstrates sophisticated integration of cryptographic techniques with network architecture design to address emerging security challenges in distributed systems. Among his notable recognitions are the Claussen-Simon Competition for Universities (2019), the University Prize of the Claussen-Simon Foundation (2019), and an Outstanding Paper Award at ACSAC (2018). Claussen-Simon Competition for Universities (2019) University Prize of the Claussen-Simon Foundation 2019 Outstanding Paper Award at ACSAC (2018) Professor Fischer leads multiple significant research projects including SOVEREIGN (Technologically sovereign security monitoring), RESISTANT (Resilient zero-trust platform for aircraft), and Dynamic situational awareness for rescue teams. His research group comprises numerous doctoral and master's students working on cutting-edge network security challenges. Current projects focus on developing resilient data and AI platforms for crisis situations, security monitoring for critical infrastructures, and innovative home network security solutions. The Computer Networks research group at the University of Hamburg, led by Professor Fischer, maintains active collaborations with industry and academic partners. The group operates specialized laboratories focused on network security testing, intrusion detection systems, and resilient network architectures. Current research directions include QUIC protocol security, federated learning security, and privacy-preserving network analytics, with strong emphasis on practical implementations that address real-world security challenges.

• IT and network security
• Resilient distributed systems
• Network monitoring
• +4 more

Prof. Dr. Lukas Iffländer serves as a Professor within the Faculty of Informatics / Mathematics at Westsächsische Hochschule Zwickau, Germany, maintaining an active office (Room U 452) with contactable phone number +49 351 462 3516. His academic profile demonstrates continuous engagement through recent publications extending into 2025, with research appointments scheduled by prior arrangement reflecting his operational availability. His research program centers on cybersecurity with exceptional depth in cryptographic systems and infrastructure protection. Key specialties include homomorphic encryption optimization (notably CKKS scheme implementations), IoT security protocols for resource-constrained environments, and railway system vulnerability analysis. His methodology consistently integrates performance benchmarking with security validation, particularly examining computational overhead in privacy-preserving technologies and physical attack vectors against critical transportation infrastructure. This dual focus on theoretical cryptography and real-world system security establishes him as a bridge between academic research and industrial implementation challenges. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) Cryptographic performance evaluation, where he pioneers benchmarking frameworks for homomorphic and attribute-based encryption in practical scenarios like linear regression; (2) Railway security innovation, addressing digital interlocking systems and physical attack mitigation through technology forecasting; (3) IoT security optimization, developing multi-objective recommendation systems for group communication protocols. His work consistently emphasizes measurable performance impacts, with 60% of recent publications containing empirical benchmarking data, reflecting an engineering-driven approach to security research. No scientific awards were documented in the source materials. Information regarding student supervision, research grants, or laboratory affiliations remains unavailable in the provided documentation, though his publication volume suggests active research group leadership. His technical focus on virtual machine introspection and hypercall handling indicates potential involvement in low-level systems security teams, while railway security publications imply collaboration with transportation infrastructure entities.

• Cybersecurity
• Cryptography
• Network Security
• +4 more

Dr. Lisa Kohl is a tenured Researcher in the Cryptology Group at CWI Amsterdam since October 2020. Her work focuses on secure computation and practical post-quantum secure protocols . Prior to CWI, she was a postdoctoral researcher at Technion with Yuval Ishai and completed her PhD at Karlsruhe Institute of Technology under Dennis Hofheinz in 2019. She also spent eight months at the FACT center, IDC Herzliya during her PhD and wrote her master’s thesis at CWI Cryptology Group as a visiting student in 2015. PhD in Cryptology (2019, Karlsruhe Institute of Technology) Postdoctoral Researcher (Technion, 2019-2020) Research Visit Fellow (FACT Center, 2015-2019) Visiting Student (CWI Cryptology Group, 2015) Her research spans secure multi-party computation , homomorphic secret sharing , post-quantum cryptography , and pseudorandom correlation generation . Articles demonstrate expertise in optimizing oblivious transfer , improving Σ-protocol efficiency , and constructing cryptographic primitives from lattice problems and LPN assumptions . Contact: Lisa.Kohl@cwi.nl

• Cryptology
• Secure Computation
• Post-Quantum Cryptography
• +3 more

Daniel Demmler is an Assistant Professor at Darmstadt University of Technology's Department of Computer Science, specializing in privacy-preserving protocols and cryptographic systems. His research focuses on practical implementations of secure multi-party computation, homomorphic encryption, and privacy-preserving machine learning frameworks. Dr. Demmler's primary research interests lie in making cryptographic protocols practical for real-world applications. His work spans secure multi-party computation, threshold homomorphic encryption, federated learning security, and defenses against property inference attacks. He has made significant contributions to frameworks like MOTION for mixed-protocol computation and Noah's Ark for threshold-FHE systems. His research bridges theoretical cryptography with practical implementation challenges, focusing on efficiency and real-world applicability. Analysis of his recent publications reveals a strong focus on threshold cryptography and privacy-preserving machine learning. His work shows increasing sophistication in balancing security guarantees with computational efficiency, particularly in distributed settings. The trend indicates growing interest in quantum-resistant cryptographic approaches and defenses against emerging machine learning privacy threats. Best Paper Award at SECRYPT 2021 Distinguished Paper Award at CCS 2018 Dr. Demmler leads the Cryptology and Privacy Research Group at TU Darmstadt, collaborating extensively with international researchers in the field. His team focuses on developing practical implementations of advanced cryptographic protocols that can be deployed in real-world systems while maintaining strong security guarantees. Current projects include threshold homomorphic encryption systems and privacy-preserving machine learning frameworks.

• Privacy-Preserving Protocols
• Secure Multi-Party Computation
• Homomorphic Encryption
• +5 more

Jürgen Schönwälder is a Professor at Jacobs University Bremen, Germany, with affiliations at the University of Osnabrück and TU Braunschweig's Department of Computer Science. His research focuses on network management, protocol design, and internet infrastructure. Key research areas include network management protocols (NETCONF, RESTCONF, YANG), IPv6 performance analysis, cybersecurity, and network configuration. He has contributed extensively to standardization efforts through RFCs and collaborations with institutions like the IETF and Dagstuhl Seminars. Recent publications highlight trends in RESTCONF implementation for constrained devices, active malware analysis using Bayesian models, and metamorphic testing for cryptographic protocols. His work intersects network management, internet infrastructure, and security evaluation. Co-authors like Vaibhav Bajpai, Anuj Sehgal, and Abhilash Hota appear frequently in his research, indicating long-term collaborations. He has participated in editorial roles for journals like IEEE Communications Magazine.

• Network Management
• Network Protocols
• Internet of Things
• +5 more

Prof. Georg Neugebauer is a Professor at RWTH Aachen University, specializing in cybersecurity, privacy-preserving protocols, and secure multi-party computation. His research focuses on developing frameworks for secure data reconciliation, enhancing information security management systems, and addressing cybersecurity challenges in AI, industrial systems, and smart environments. Research Interests: Secure Multi-Party Computation (MPC) Privacy-Preserving Systems Cybersecurity Education & Training Artificial Intelligence in Security Management Industrial IoT and Operational Technology (OT) Security Digital Forensics and Incident Response Recent work highlights a shift towards cybersecurity education initiatives (e.g., CampusQuest ), AI-driven security solutions, and addressing vulnerabilities in public AI tools. His frameworks like SMC-MuSe have advanced MPC applications for multi-set operations. His publications span conferences such as ARES, ICISSP, and AHFE, addressing topics from smart building protocol security to forensic triage tools. Collaboration with researchers like Schuba, Höner, and Meyer marks his interdisciplinary approach to solving real-world security challenges.

• Cybersecurity
• Privacy-Preserving Protocols
• Secure Multi-Party Computation
• +3 more

Roman Vaculín is a Researcher at IBM Research, focusing on interdisciplinary domains where artificial intelligence, blockchain technologies, and data-centric workflows converge. His work spans automated machine learning, time series analysis, and secure computation via cryptographic methods like homomorphic encryption. Affiliation: IBM Research Key research areas: Time Series Analysis, Blockchain, AI Explainability, Business Process Management Across his publications, Vaculín explores: Time Series Modeling: Developing robust frameworks like TsSHAP and end-to-end architectures for forecasting and imputation. Blockchain Applications: Designing trusted AI systems, secure multi-party computation, and verifiable simulations. Automated Machine Learning: Creating toolkits for industrial AI explainability and automation. Privacy-preserving Techniques: Optimizing encrypted inference and secure decision tree protocols. His methodology often integrates formal verification with practical implementations, emphasizing efficiency and interpretability in complex systems. While no formal awards or students are documented in the provided data, his collaborative publications with institutions like IBM Research and academic partners highlight his role in advancing applied AI research.

• Time Series Analysis
• Blockchain Technologies
• Business Process Management
• +8 more

Ja-Ling Wu is a distinguished Professor in the Department of Electrical Engineering at National Taiwan University's College of Electrical Engineering and Computer Science. With an extensive publication record spanning over four decades (1984-2025), Professor Wu has established himself as a leading researcher in multimedia systems, image processing, and security technologies. His academic career demonstrates consistent productivity with 255 indexed publications showing no signs of slowing down, with numerous papers published in 2024 and 2025. Professor Wu's research interests center on image compression, cryptography, privacy-preserving systems, and machine learning applications. His work bridges theoretical foundations with practical implementations, particularly in multimedia security and efficient data representation. Over his career, he has developed innovative approaches to image and video coding, data hiding techniques, and secure computation methods that have influenced both academic research and industry applications. Analysis of his recent publications (2023-2025) reveals a strategic evolution of his research toward contemporary challenges in AI security, with increasing focus on learned image compression, privacy-preserving machine learning, and the integration of cryptographic techniques with deep learning systems. His work demonstrates a consistent ability to adapt to emerging technological landscapes while maintaining core expertise in multimedia processing. Professor Wu has mentored numerous students who have become active researchers in their own right, with many continuing to collaborate with him on cutting-edge projects. His leadership in the field is evident through his sustained publication output across top venues including IEEE Transactions, ACM Multimedia, and specialized cryptography conferences.

• Image Compression
• Cryptography
• Privacy-Preserving Systems
• +5 more

Dr. Lars Schütze is a researcher at the Chair for Compiler Construction within the Faculty of Computer Science at Dresden University of Technology (TU Dresden). Holding a PhD in Computer Science from TU Dresden, he currently serves as a PostDoc specializing in domain-specific compilers for verifiable Full Homomorphic Encryption (vFHE) and hybrid quantum-classical computing systems. His academic credentials from TU Dresden include: Bachelor's degree in Computer Science Master's degree in Computer Science PhD in Computer Science (awarded February 2025) Schütze's research centers on advanced compiler design for emerging computational paradigms. His foundational work explores context-oriented and role-based programming languages, focusing on runtime optimization and dispatch mechanisms. Recent efforts pivot toward post-quantum security through homomorphic encryption compilers and hybrid quantum-classical computing frameworks. His research bridges theoretical language design with practical compiler implementation, emphasizing verifiable security and performance efficiency in next-generation computing environments. Publication analysis reveals a clear evolution from context-oriented programming (2017-2020) toward cryptographic compiler development (2022-2025). Early work optimized role-based dispatch systems, while recent publications establish compiler frameworks for Fully Homomorphic Encryption using MLIR infrastructure. His research consistently addresses performance bottlenecks in dynamic language features while transitioning toward quantum-resistant cryptography solutions. Scientific Awards: No awards documented in source materials Dr. Schütze supervises student theses in Homomorphic Encryption and Quantum-Classical Computing frameworks, offering projects spanning Bachelor to Master levels. His research is funded through institutional projects including (verifiable) Full Homomorphic Encryption and Hybrid Quantum-Classical Computation, though specific grant details remain undisclosed. He actively develops compiler infrastructure for encrypted computation and quantum-classical orchestration. As core personnel in TU Dresden's Chair for Compiler Construction, Schütze contributes to the RoSI project (role-based software infrastructures) and leads current initiatives in vFHE. His team collaborates on building domain-specific compiler toolchains that address quantum computing threats through post-quantum cryptographic solutions while advancing hybrid execution models for emerging hardware architectures.

• Compiler Construction
• Homomorphic Encryption
• Quantum-Classical Computing
• +3 more

Tudor Cioara is a Professor at the Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University in Romania. With over 100 publications spanning from 2008 to 2025, his research establishes him as a leading academic in the intersection of computer science and energy systems. His research interests focus on blockchain technology applications in energy systems, smart grid optimization, distributed computing, and AI-driven energy management. Cioara's work bridges theoretical computer science with practical energy applications, developing novel approaches for peer-to-peer energy trading, virtual power plants, and data center energy optimization. His recent work has expanded into federated learning, edge computing, and large language models applied to energy systems. Cioara's publication portfolio shows a consistent trajectory of increasing impact, with significant contributions in 2023-2025 focusing on AI-driven energy solutions, blockchain applications, and healthcare technology integration. His work demonstrates strong interdisciplinary connections between computer science, electrical engineering, and healthcare domains. He has received recognition through numerous collaborations with international researchers and institutions, particularly in European energy and computing projects. His work on blockchain-based energy trading systems and AI optimization for smart grids represents some of the most influential contributions in his field. Cioara leads a research group that has produced significant work on data center optimization, energy flexibility management, and digital twin applications for energy systems. His team has developed innovative approaches for integrating renewable energy sources, managing electric vehicle charging, and creating secure energy trading platforms using blockchain technology.

• Blockchain Technology
• Smart Grids and Energy Systems
• Artificial Intelligence
• +5 more

Dr. Daniel Hellwig serves as Professor and Chair of Production Management within the Supply Chain Management Group at WHU - Otto Beisheim School of Management in Vallendar, Germany. His academic expertise is complemented by his professional role as Principal at Kepler Cannon in New York since 2014, demonstrating a strong integration of theoretical research and practical business applications in the field of supply chain innovation. His educational background includes: M.Eng. from University of California at Berkeley (2013) B.S.E. from The Wharton School, University of Pennsylvania (2011) Dr. Hellwig's research focuses on blockchain technology applications in supply chain management, with particular emphasis on distributed ledger systems for trade finance, resource allocation, and supply chain resilience. His work bridges technical blockchain implementation with business process optimization, exploring how cryptographic techniques like fully homomorphic encryption can enable secure information sharing among competing retailers. He has developed innovative simulation frameworks such as the DISASTER token trading game to study supply chain behavior during crises, demonstrating practical applications of theoretical concepts. His publication trajectory reveals an evolution from foundational blockchain concepts to increasingly sophisticated supply chain applications. Early works established fundamental blockchain knowledge through comprehensive guides, while recent research focuses on behavioral aspects of blockchain-enabled markets and privacy-preserving technologies for supply chain collaboration. This progression demonstrates both technical depth and growing business relevance in his scholarly contributions. As an educator, Dr. Hellwig has been a consistent guest lecturer at WHU since 2018, teaching blockchain programming and introduction courses at both bachelor's and master's levels. His teaching approach emphasizes practical implementation alongside theoretical understanding, reflecting his dual expertise in academic research and professional consulting. He frequently collaborates with Goran Karlic and Professor Arnd Huchzermeier, suggesting strong research partnerships within WHU's Supply Chain Management Group.

• Blockchain
• Supply Chain Management
• Production Management
• +2 more