جست‌وجوی استاد و پژوهشگر

Razi Arshadمشاهده پروفایل

پژوهشگر ارشد

• Applied Cryptography
• Provable Security
• Privacy-Enhancing Technologies
• +۳ مورد دیگر

Dr. Razi Arshad is a Research Fellow in Security and Privacy at the University of Surrey, UK, affiliated with the Computer Science Research Centre and Surrey Centre for Cyber Security. Previously, he held an Assistant Professor position at the School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, Pakistan. He earned his PhD in Mathematical Cryptography from Otto-von-Guericke University (Germany, 2018) and MSc in Information Security from Sichuan University (China, 2007). His expertise includes applied cryptography, post-quantum security, privacy technologies, and authentication schemes. His research focuses on advancing cryptographic primitives, securing communication protocols, and exploring quantum-resistant solutions. Notable contributions include critiques of existing cryptographic schemes (e.g., identifying flaws in S-box constructions and SIP authentication protocols) and designing secure frameworks like elliptic curve-based mutual authentication systems. Recent work emphasizes AI-driven privacy solutions (e.g., emotion detection via wearable sensors) and cybersecurity challenges in fintech. Razi Arshad has published extensively in top-tier venues, addressing topics from S-box design and hyperchaotic encryption to regulatory compliance in privacy. He holds certifications as an ISO/IEC 17025 Lead Assessor and ISO/IEC 27001 ISMS Lead Auditor, reflecting his commitment to standards-based security practices. His consulting experience with tech firms like Xprime Inc. and Graxo Consulting Pvt. Ltd. underscores his industry relevance.

• Probability Theory
• Statistical Mechanics
• Bayesian Modeling
• +۲ مورد دیگر

Johan Jonasson is Professor in the Department of Mathematical Sciences at Chalmers University of Technology. His research investigates fundamental questions in probability theory with applications to statistical mechanics and machine learning. Key research areas: Mixing times and convergence properties of Markov chains Stochastic processes in disordered systems Bayesian inference methodologies Combinatorial probability models Professor Jonasson teaches advanced courses on probability theory and supervises doctoral research in stochastic processes. His pedagogical work includes developing mathematical curricula for graduate education.

Ryan O'Donnellمشاهده پروفایل

استاد

• Algorithms and Complexity
• Security and Privacy
• Theoretical Computer Science
• +۶ مورد دیگر

Ryan O'Donnell is a Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He specializes in theoretical computer science, with a focus on algorithms, complexity theory, quantum computing, and probability. His research includes Fourier analysis of Boolean functions, constraint satisfaction problems, and quantum information theory. He teaches courses such as 15251 (Fall 2025), 15754 (Spring 2025), and others. His work spans quantum tomography, pseudorandomness, and algorithmic design. Recent publications explore topics like quartic quantum speedups, uniformity testing, and explicit expanders. He advises PhD students William He, Noah Singer, and Jingxun Liang. His research interests bridge foundational theory and practical applications, including healthcare informatics and cryptographic tools. He actively contributes to academic conferences and program committees, reflecting his leadership in the field.

Christine Zargesمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Evolutionary Algorithms
• Optimization
• +۳ مورد دیگر

Christine Zarges is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. Her research focuses on evolutionary algorithms, artificial immune systems, and optimization techniques, with applications in data preprocessing, anomaly detection, and bioinformatics. She has contributed significantly to the theoretical foundations of immune-inspired randomized search heuristics and has explored their practical implementations in various domains. Her work often addresses challenges in combinatorial optimization, such as improving variable orderings in OBDDs and developing efficient algorithms for Lyndon factorization of biosequences. Recent projects include applications of adversarial diffusion for video anomaly detection and the use of rough set theory for big data preprocessing. She has also been involved in initiatives to address bias in physical science and engineering research. Christine has led and collaborated on externally funded projects, including the Horizon 2020-funded RoSTBiDFramework project and EPSRC grants focused on bias reduction in STEM fields. She has supervised graduate students, such as Yumna Zahid, whose work contributes to video anomaly detection. She actively contributes to the academic community by organizing conferences like EvoCOP and the Genetic and Evolutionary Computation Conference (GECCO), and serves on editorial boards of journals including Evolutionary Computation and IEEE Transactions on Evolutionary Computation .

• Cryptography
• Constraint Programming
• Formal Methods
• +۳ مورد دیگر

Dr. Arthur Gontier serves as a Research Associate within the School of Computing Science at the University of Glasgow, where he conducts specialized research at the intersection of cryptography and constraint programming. His academic profile centers on advancing formal methods for security-critical systems through rigorous algorithmic development. Research interests span Cryptography (symmetric ciphers, cryptanalysis), Constraint Programming (explanation generation, decomposition methods), and Formal Verification techniques. Recent work demonstrates deep engagement with Feistel network optimization, Trivium stream cipher analysis, and conflict-driven search methodologies, reflecting a consistent focus on mathematical foundations of secure computation. Publication trends from 2020-2022 reveal concentrated contributions to top-tier cryptography venues (INDOCRYPT, SAC) and constraint programming workshops. His research exhibits growing sophistication in post-quantum cryptographic techniques and trustworthy AI verification, with increasing emphasis on practical implementation challenges alongside theoretical advances. Collaborative patterns indicate active engagement with European research networks, particularly in cryptographic analysis. While specific grant details aren't public, the publication frequency suggests sustained research activity within Glasgow's security research ecosystem. Prospective collaborators would find opportunities in formal methods for security protocol verification and constraint-based AI validation systems.

Xavier Goaocمشاهده پروفایل

استاد

• Computational Geometry
• Discrete Mathematics
• Combinatorial Convexity
• +۵ مورد دیگر

Xavier Goaoc is a Professor of Computer Science at Université de Lorraine, affiliated with the Department of Computer Science & Engineering at École des Mines de Nancy and the Gamble research team (joint between LORIA and INRIA). His research focuses on algorithms and discrete mathematics, particularly discrete and computational geometry, including convex hulls, intersection patterns, topological generalizations, and geometric transversal theory. University: Université de Lorraine School: School of Engineering Department: Department of Computer Science & Engineering Research Team: Gamble (LORIA/INRIA) Emails: xavier.goaoc@loria.fr , xavier.goaoc@univ-lorraine.fr His research spans computational geometry, combinatorial convexity, geometric transversal theory, and random geometric structures. Key topics include homological minors, order types of point sets, and geometric optimization. His 15 most recent publications highlight advancements in computational geometry algorithms, structural complexity, and topological constraints. Notably, his work has received Best Paper Awards at SoCG 2020, 2018, 2016, and 2012. Administrative roles include heading the computer science & engineering department at Mines Nancy and co-chairing the computer science department of the IAEM doctoral school. He is also a member of the Université de Lorraine's ‘pôle AM2I’ council. Teaching activities encompass courses in algorithms, computer architecture, blockchains, and geometric models for vision, with publications and grants reflecting his interdisciplinary impact in computer science and mathematics.

• Combinatorial Optimization
• Quadratic Programming
• Binary Optimization
• +۵ مورد دیگر

Cédric Elloumi is a Professor at the CEDRIC Laboratory within Conservatoire National des Arts et Métiers (CNAM), specializing in combinatorial optimization and mathematical programming. With a continuous publication record since 1992, he has established himself as a leading researcher in quadratic programming, binary optimization, and facility location problems. His research interests focus on developing exact and approximate methods for discrete optimization problems, particularly through convex reformulation techniques. Elloumi has made significant contributions to the p-center and p-median problems, quadratic assignment problems, and more recently, quantum-inspired optimization methods. His work bridges theoretical advancements with practical applications in network design, energy systems, and telecommunications. Analysis of his recent publications (2022-2025) reveals a continued focus on facility location problems, with increasing attention to robust optimization under uncertainty and emerging applications in quantum computing. His research demonstrates consistent methodological innovation, particularly in reformulation techniques that transform difficult non-convex problems into tractable forms. Throughout his career, Elloumi has maintained extensive collaborations with researchers including Billionnet, Lambert, Alès, and Plateau, resulting in numerous publications in top-tier optimization journals such as Journal of Global Optimization, Computers and Operations Research, and Mathematical Programming.

• Quantum Computing
• Cryptography
• Theoretical Computer Science
• +۳ مورد دیگر

Sean Hallgren is a Professor in Computer Science and Engineering, specializing in quantum algorithms and computational complexity. His research spans both theoretical and applied aspects of quantum computing, cryptography, and mathematical optimization. Research Interests Hallgren's work focuses on: Quantum algorithm design and complexity Cryptographic reductions under quantum models Number-theoretic problems in cryptography Quantum linear algebra techniques Computational complexity of combinatorial problems Recent Publications Hallgren's 15 most recent articles (5 shown) demonstrate expertise in quantum algorithm limitations, cryptographic hardness reductions, and isogeny-based cryptography. His 2023 study in Quantum analyzed the Macaulay matrix approach for solving polynomial systems using quantum linear solvers. Grants & Projects Current and past projects include: Exponential Speedups and Limitations of Quantum Computation (U.S. Navy, 2018–) NSF Convergence Accelerator: Scalable Quantum Artificial Intelligence for Discovery (2020–2023) SaTC: CORE: Small: Classical and quantum algorithms for number-theoretic cryptography (2020–2025) AF: Small: Quantum Algorithms and Complexity (2016–2020, PI)