Sidi Mohamed Beillahi is a Lecturer in the Department of Computer Science at the University of Toronto's Faculty of Arts and Science. He teaches courses including Principles of Programming Languages (CSC324H1S) and Algorithms and Data Structures (ECE345H1F). Previously, he served as a Teaching Assistant at both University of Paris and Concordia University for courses ranging from Automata Theory to Hardware Functional Verification. Dr. Beillahi's research focuses on developing formal verification and programming languages techniques to ensure the correctness of software systems, particularly distributed systems, concurrent programs, blockchain, and smart contracts. His work bridges theoretical computer science with practical security applications in decentralized finance. His publication record shows a clear progression from quantum circuit verification during his Master's to blockchain and smart contract security in his doctoral and postdoctoral work. Recent publications demonstrate expertise in authenticated data structures for blockchain storage, flash loan attack analysis, and formal verification of decentralized applications. Scientific Awards: ACM SIGSOFT Distinguished Paper Award (ICSE '24) ICBC Distinguished Paper Award (ICBC '22) Dr. Beillahi has advised multiple research projects in blockchain security and verification, often collaborating with Professor Fan Long and Professor Andreas Veneris at the University of Toronto. His research has been supported by prestigious fellowships including an NSERC Postdoctoral Fellowship and a Mitacs Accelerate Fellowship.
Bryan Parno is the Kavčić-Moura Professor of Electrical & Computer Engineering and Computer Science at Carnegie Mellon University, where he leads the Secure Foundations Lab within CyLab, CMU's Security & Privacy Institute. His research combines theory and practice to provide formal, rigorous security guarantees about concrete systems, with emphasis on creating solid foundations for practical solutions. His research spans secure systems , formal software verification , applied cryptography , data privacy , and usable security . Current work focuses on protocols for verifiable computation and zero-knowledge proofs, building practical formally verified secure systems, and developing next-generation application models. His lab maintains a strong commitment to reproducibility, open-sourcing code under permissive licenses, and avoiding patenting results to maximize public benefit. His recent publications demonstrate a clear trend toward practical verification of real-world systems, particularly through the Verus project for verifying Rust code, Everest for building verified HTTPS stacks, and Ironclad for provably secure systems. These works bridge the gap between theoretical security guarantees and practical implementation, with applications ranging from blockchain protocols to verified cryptographic libraries deployed in the Linux kernel. His scientific achievements include multiple Distinguished Paper/Artifact Awards (USENIX Security, SOSP, PLDI), the IEEE Cybersecurity Award for Practice , the Sloan Fellowship , and the ACM Doctoral Dissertation Award . His work on verifiable computation protocols has influenced blockchain systems, while his research on secure code execution environments contributed to Intel's SGX and TDX technologies. As an advisor, Parno has mentored numerous PhD students including Aymeric Fromherz (recipient of the ACM SIGSAC Doctoral Dissertation Award) and Jay Bosamiya. His lab receives funding from diverse sources including NSF, industry partners, and security foundations. Notably, his work has been incorporated into Windows 8+, iOS 13+, and the Linux kernel. He also serves in leadership roles including Chair of IEEE Computer Society's Technical Committee on Security & Privacy. The Secure Foundations Lab maintains strong industry connections, with alumni joining Microsoft Research, Inria, Northeastern University, and other leading institutions. Recent projects like Verus, Everest, and Ironclad represent the lab's commitment to building end-to-end verified systems that provide rigorous security guarantees while maintaining practical performance.
Fatih Mehmet ULU serves as a full-time Lecturer at Karabük University's TOBB Technical Sciences Vocational School in the Electricity and Energy Department since 2015. His academic background includes: Master of Science in Electrical and Electronics Engineering from Karabük University (2015-2019), thesis: "PLC and SCADA based automation of a synchronous micro hydroelectric power plant" Bachelor of Science in Electrical Education from Gazi University (1996-2000) His research concentrates on Lighting systems, Electrical Energy and Power Systems optimization, and Electrical Installations engineering. His work demonstrates practical applications in power plant automation, particularly through his thesis and related project. He has instructed 13 vocational-level courses including Illumination Technique, Electrical Energy Production Transmission and Distribution, and Asynchronous/Synchronous Machines. He participated as a researcher in one scientific project: "Synchronous Micro Hydroelectric Power Plant's PLC and SCADA Based Automation" (2016-2019) funded by Higher Education Institutions.
Gerwin Hoogsteen is an Assistant Professor at the University of Twente, affiliated with the Computer Architecture for Embedded Systems chair. He focuses on smart grids, cyber-physical systems, and applying theoretical research in field-tests. PhD in Decentralized Energy Management (2017, University of Twente) His research integrates machine learning , distributed coordination , and cybersecurity into smart grid optimization. Recent work emphasizes multi-objective optimization for EV charging hubs, energy community resilience, and congestion management. Key article trends include EV charging algorithms , decentralized control , and hybrid storage systems . He contributes to UN SDGs like Climate Action and Affordable Energy . Founder of DEMKit and ALPG open-source software Collaborator in EU projects (SUSTENANCE, SERENE, LocalRES)
S. Prabhu Kumble is a researcher active in the fields of Blockchain , Lightning Network , and Payment Channel Networks . His work focuses on security analysis , anonymity , and network congestion in decentralized financial systems. Current affiliations include research contributions to Data-Intensive Systems .
Professor Andrzej Demenko is a distinguished academic at Poznań University of Technology, where he holds a position in the Institute of Electrical Engineering and Industrial Electronics within the Faculty of Automatic Control, Robotics and Electrical Engineering. He serves as Chairman of the Committee on Electrical Engineering of the Polish Academy of Sciences, demonstrating his significant standing in the national academic community. His career spans several decades, beginning with his doctoral dissertation in 1975 on modeling magnetic circuits of electrical machines using potential field analyzers. Professor Demenko's research focuses on computational electromagnetics, electrical machine analysis and design, finite element methods, and power system safety. His work particularly emphasizes permanent magnet synchronous motors, field-circuit coupling approaches, and electromagnetic phenomena in nonlinear circuits. He has made significant contributions to understanding squirrel cage design in motors, temperature effects on motor performance, and the development of numerical methods for electromagnetic field calculations. Analysis of his recent publications (2015-2024) reveals a continued focus on advanced electrical machine design, particularly permanent magnet synchronous motors, with increasing attention to optimization techniques, thermal effects, and control strategies. His work consistently combines theoretical developments with experimental validation, demonstrating practical relevance alongside theoretical rigor. Professor Demenko has supervised five doctoral dissertations to completion and has reviewed numerous others, indicating his commitment to academic mentorship. His publication record is substantial, with 65 articles, 61 book chapters, and 11 books or edited volumes spanning several decades of research. As an active researcher, Professor Demenko continues to contribute to the field through ongoing projects, editorial work for international conferences like the Electromagnetic Phenomena in Nonlinear Circuits (EPNC) symposium series, and collaborations with researchers worldwide. His work bridges theoretical developments in computational electromagnetics with practical applications in electrical machine design and power system safety.
Dr. Hatem Ahriz is a Professor at Robert Gordon University's School of Computing, Engineering & Technology, with a distinguished career spanning over 25 years in artificial intelligence and cybersecurity research. His academic journey began with a BSc in Computer Science (1987-1992), followed by an MSc (1993-1994) and PhD in Artificial Intelligence (1994-1998). Dr. Ahriz's research has evolved from constraint satisfaction and optimization problems to cutting-edge cybersecurity applications, with particular expertise in Advanced Persistent Threats (APTs). His work combines artificial intelligence, machine learning, and security frameworks to develop innovative solutions for threat detection and cyber defense systems. His recent publications (2019-2024) show a clear shift toward cybersecurity applications, with multiple papers on APT detection frameworks, machine learning approaches for threat analysis, and cyber physical systems security. This represents a natural progression from his earlier foundational work on distributed constraint satisfaction problems. Active supervision of PhD students in cybersecurity Current research project on AI-powered vulnerability detection systems Teaching expertise in database systems and information security Dr. Ahriz maintains active collaborations with industry partners, as evidenced by his project with CyberShell Solutions to develop a SaaS platform for Cyber Threat Intelligence. His research bridges theoretical computer science with practical applications in critical infrastructure protection and enterprise security.
Gianluca De Marco is an Associate Professor in the Department of Computer Science at the University of Salerno. His research specializes in Algorithms, Distributed Computing, and Combinatorial Search, with a focus on developing efficient contention resolution protocols for shared channels and radio networks. He leads the 'Research Group on Resource Contention in Shared Channels,' collaborating internationally with institutions like Augusta University and University of Wroclaw. De Marco has an extensive publication record in top-tier venues, including SIAM Journal on Computing and PODC. His recent work emphasizes: Deterministic algorithms for conflict resolution Energy-efficient network protocols Optimization of channel utilization in asynchronous systems He actively contributes to the academic community as an Associate Editor for Fundamenta Informaticae and through program committee roles at conferences like IPDPS and EURO-PAR. His research is supported by the University of Salerno and international grants, including the Polish National Science Center project 'Distributed Computing in Dynamic Networks.'
Martin Berger is an Associate Professor in Foundations of Computation at the University of Sussex's School of Engineering and Informatics. His research bridges theoretical computer science and practical systems engineering, with focus areas including: Formal methods and program verification Programming language design and semantics Hardware security vulnerabilities and mitigations GPU-accelerated computation and program synthesis Automated reasoning and logic-based systems With 51 publications, his recent work demonstrates strong emphasis on: Developing high-performance simulation tools (Pydrofoil) GPU-based acceleration of formal methods Security analysis of programming language ecosystems Automated inference systems for regular expressions He maintains active research collaborations across Europe and welcomes inquiries via his institutional email.
Wojciech Siwicki is an Assistant Professor at the Department of Radiocommunication Systems and Networks within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. Based in room 406 of Building A, he can be contacted via email (wojciech.siwicki@pg.edu.pl) or phone (+48 58 347 1577). His research focuses on radio navigation and terrestrial positioning systems , particularly: Hyperbolic radio navigation alternatives to GNSS Asynchronous and self-organizing radiolocation methods Indoor localization algorithms using radio distance measurements Security analysis of navigation infrastructure Internet of Things radio interfaces Publications from 2013-2020 reveal consistent work on Polish radiolocation systems (AEGIR/JEMIOLUSZKA), with emphasis on system reliability, asynchronous operation, and comparative performance analysis in both static and dynamic environments. His contributions span theoretical modeling and practical implementation of terrestrial navigation solutions. Dr. Siwicki participates in research projects funded by the Intelligent Development Operational Programme, including DUCH IoT (software-defined radio interfaces for IoT devices) and VCS-MLAT (aircraft location in distributed VCS systems), demonstrating applied research engagement in navigation technology innovation.
mgr inż. Alicja Olejniczak serves as a Lecturer at the Department of Radiocommunication Systems and Networks within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. Her work focuses on the intersection of wireless communications and artificial intelligence, particularly applying deep learning techniques to solve challenging problems in modern radio systems. Her primary research interests include: Deep learning applications in wireless communication systems Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) identification in indoor environments Signal processing for GMSK modulation schemes Software-defined radio implementations for NB-IoT technologies Train detection using LTE reference signals Radiolocation systems and multilateration techniques Analysis of her recent publications reveals a strong trend toward applying deep learning methods to solve practical problems in wireless communications. Her work spans both theoretical development and practical implementation of algorithms for signal processing, channel estimation, and radio interface design. A significant portion of her research focuses on NB-IoT and LTE technologies, with applications ranging from Internet of Things to transportation systems like train detection. Dr. Olejniczak actively participates in multiple research projects at Gdańsk University of Technology, including: SDIDS - Software-Defined Device for Detecting and Mitigating Interferences in 4G-LTE and 5G-NR radio interfaces DUCH IoT - A software-defined, universal radio interface for intelligent IoT devices VCS-MLAT - Innovative method of aircraft locating in distributed VCS systems AEGIS - Mobile Device for Generating Electromagnetic Curtain Her laboratory work involves hands-on implementation of software-defined radio systems and conducting measurements in real-world environments to validate theoretical models. She collaborates extensively with colleagues including O. Błaszkiewicz, K. Cwalina, P. Rajchowski, and J. Sadowski on various research initiatives.
Sergey Vladimirovich Samsonov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he also serves as Head of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis within the Institute of Artificial Intelligence and Digital Sciences. He is affiliated with the Department of Big Data and Information Retrieval and the Joint Department of the A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences. Samsonov began his tenure at HSE in 2018 and has accumulated 7 years of scientific and teaching experience. His educational background includes a PhD from HSE (2024) and a Bachelor's degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University (2017). Samsonov's research focuses on stochastic approximation, reinforcement learning, sampling techniques, Markov chain Monte Carlo (MCMC) methods, and multivariate statistics . His work bridges theoretical mathematics with practical machine learning applications, particularly in developing algorithms with strong theoretical guarantees. He has made significant contributions to understanding convergence properties of stochastic algorithms and developing variance reduction techniques. Analysis of his recent publications reveals a consistent focus on the mathematical foundations of machine learning, particularly in stochastic approximation methods, reinforcement learning theory, and generative modeling. His work often combines rigorous theoretical analysis with practical applications, demonstrating expertise in both pure mathematics and applied machine learning. The publication venues (including top conferences like NeurIPS, ICLR, and AISTATS) reflect the high impact and quality of his research in the machine learning community. Young Scientist Badge (December 2024) Letter of gratitude from the First Vice-Rector of HSE (March 2023) Letter of gratitude from the Faculty of Computer Science at HSE (September 2021) Rector's personal allowance (2022-2023) Numerous bonuses for high-impact publications (2021-2027) Best Teacher award (2024-2025, 2022, 2020) Segalovich Scientific Prize (2022) National Prize 'Leaders in AI - 2024' Samsonov teaches advanced courses including Markov Chains, Sampling and Generative Modeling, and Matrix Computations. His laboratory work focuses on developing stochastic algorithms for machine learning applications. He has been involved in HSE's collaboration with Sber, which has resulted in 19 successfully implemented AI projects since 2021. His research has gained significant recognition, with multiple papers accepted at top-tier conferences including 12 papers presented at NeurIPS in recent years.
Felix Stutz is a postdoctoral researcher in the Security and Trust of Software Systems (SaToSS) group at the University of Luxembourg. His research focuses on formal methods for concurrent and distributed systems, as well as security protocols. He previously held positions as a PhD student at the Max Planck Institute for Software Systems (MPI-SWS) and a half-year research intern at MIT CSAIL (with Nikos Vasilakis) and Imperial College London (with Emanuele D’Osualdo and Philippa Gardner). MSc in Computer Science, University of Saarland PhD, Max Planck Institute for Software Systems (MPI-SWS), co-advised by Rupak Majumdar and Damien Zufferey Research interests include formal verification of software systems, algorithmic analysis of message-passing programs, and depth-bounded protocol verification. His work has produced tools like Lemma9 for cryptographic protocol verification and contributions to the PaSh parallelization framework. He has collaborated with institutions including MIT CSAIL, Imperial College London, and the University of Saarland. Felix is actively involved in software development and is available for asynchronous communication via email.
Klaus von Gleissenthall is a tenured Assistant Professor in Computer Science at Vrije Universiteit Amsterdam, affiliated with the Theory Group and VUSec security lab. He holds a joint appointment with CWI's Computer Security group. Previously, he was a post-doc at UCSD and completed his PhD at TUM under a Microsoft Research scholarship. His research integrates programming languages , security , and systems to develop formally verified, low-overhead solutions for hardware/software correctness. Key focus areas include: Side-channel attack mitigation via leakage contracts Refinement-type systems for hardware verification Byzantine fault tolerance in distributed systems Publications demonstrate strong emphasis on hardware security (45% of recent papers), formal methods (30%), and distributed systems (25%), with consistent appearances in top-tier venues (S&P, CCS, OOPSLA). Awards & Honors: ERC Starting Grant (€1.5M, 2024) Intel Hardware Security Award Honorable Mention (2020, 2024) Distinguished Paper Awards: CCS'23, OOPSLA'23, POPL'21 He advises four PhD students and two post-docs, supported by his ERC grant. Current projects include refinement types for hardware and pre-silicon leak detection. His lab collaborates with VUSec and CWI, focusing on scalable verification tools like LLVM Blade and methodologies for constant-time execution guarantees.
Daniel W. C. HO is a Chair Professor of Applied Mathematics and Associate Dean (Undergraduate Education) at the College of Science, City University of Hong Kong. He has been with City University of Hong Kong since 1989, having previously served as a Research Fellow at the University of Strathclyde, Glasgow, UK from 1985 to 1988. Prof. Ho received first class honours in BSc, MSc, and PhD degrees in mathematics from the University of Salford, Greater Manchester, UK in 1980, 1982, and 1986, respectively. His academic journey began with foundational work in control theory and has evolved into a distinguished career spanning over three decades. Prof. Ho's research interests span multiple domains in control theory and systems engineering. His primary focus areas include Control Theory , Estimation and filtering theory , Complex dynamical distributed networks , Multi-agent networks , Nonlinear singular systems , and Stochastic systems . His work bridges theoretical advances with practical applications, particularly in networked control systems, cybersecurity for cyber-physical systems, and distributed optimization. Prof. Ho has made significant contributions to the understanding of synchronization phenomena in complex networks, resilient control under cyber attacks, and quantized control systems with communication constraints. His research has evolved from classical control theory to address contemporary challenges in networked and distributed systems, reflecting the changing landscape of control engineering. Prof. Ho's publication record shows a strong emphasis on secure control systems under cyber attacks, distributed optimization with communication constraints, event-triggered control schemes, quantized control systems, and synchronization of complex networks. His work demonstrates a consistent progression from theoretical foundations to addressing practical implementation challenges in cyber-physical systems, with increasing focus on security aspects in recent years. Prof. Ho has received numerous prestigious awards and honors throughout his career. He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2017 and elevated to IEEE Life Fellow status in 2024. He was awarded the Chang Jiang Chair Professorship by the Ministry of Education, China in 2012. Prof. Ho has been recognized as a Highly Cited Researcher for eleven consecutive years from 2014 to 2024, and is among the Top 2% of most highly cited scientists globally from 2020 to 2024. He received the Best Paper Award from The 8th Asian Control Conference in 2011 and the Teaching Excellence Award from City University of Hong Kong in 2020 for his innovative teaching approaches. Prof. Ho has held significant editorial responsibilities, serving as Subject Editor of the Journal of Franklin Institute, Co-Editor in Chief of Franklin Open, Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, Asian Journal of Control, and Action Editor of Neural Networks. He has also served on the editorial boards of several other prestigious journals, contributing to the advancement of his field through scholarly communication. His leadership extends beyond research and teaching as Associate Dean (Undergraduate Education) of the College of Science at City University of Hong Kong, where he plays a key role in shaping the educational experience for science students.
