جست‌وجوی استاد و پژوهشگر

Muhammed Ali Bingolمشاهده پروفایل

مدرس ارشد

• Cryptography
• Information Security
• Blockchain & Cryptocurrencies
• +۹ مورد دیگر

Dr. Muhammed Ali Bingol is a Senior Lecturer in Cyber Security and Programme Leader for the BSc in Computer Networks and Security at De Montfort University, UK, within the School of Computer Science and Informatics, Faculty of Computing, Engineering and Media. He is affiliated with the Cyber Technology Innovations and Digital Future Institute research groups. Education: Ph.D. in Computer Science and Engineering, Sabanci University, 2019 M.Sc. in Electronics and Communication Engineering, Istanbul Technical University, 2012 B.Sc. in Telecommunications Engineering, Istanbul Technical University, 2008 His research focuses on cryptography , information security , blockchain , secure multi-party computation , private function evaluation , authentication systems , and e-voting . He has contributed significantly to RFID security, distance-bounding protocols, and cryptographic protocol design. His work bridges theoretical cryptography and practical security implementations in wireless, cloud, and mobile environments. His recent publications (2022–2025) span topics from flexible threshold signatures and homomorphic encryption to blockchain-based voting and pedestrian safety analysis , indicating an interdisciplinary reach while maintaining a core in cryptographic protocol development. Trends show increasing focus on blockchain integration, privacy-preserving technologies, and real-world security applications. Scientific Awards and Memberships: Fellowship of the Higher Education Academy (FHEA) Member, Institute of Electrical and Electronics Engineers (IEEE) Cisco Networking Academy (CNA) Dr. Bingol has advised on multiple EU, public, and government cybersecurity projects and has served as a visiting scientist at Université Catholique de Louvain and a visiting lecturer at Istanbul City University. He has held industrial research roles at TÜBİTAK BİLGEM (Chief Researcher, 2008–2020), TSSG, and AOL. He leads curriculum development for undergraduate cybersecurity programs and teaches courses in cryptography, networks, malware analysis, and security management. He is actively involved in the Cyber Technology Innovations research group, where he contributes to advancing secure communication protocols, blockchain applications, and privacy-preserving technologies.

• Energy Systems
• Smart Grids
• Electricity Markets
• +۶ مورد دیگر

Sergio Potenciano Menci is a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg. His research focuses on smart grids, energy systems, and machine learning applications in energy management. He contributes to projects like the Energy Synchronization Platform, aiming to optimize industrial demand response and grid flexibility. His work addresses challenges in electricity markets, distributed energy resources, and privacy-preserving technologies like federated learning. Key areas of expertise include: Design of local flexibility markets for congestion management Short-term load forecasting with spatiotemporal models Privacy-preserving federated learning for energy data Optimization of battery storage in intraday markets Scalability analysis of smart grid functions Publications emphasize energy market structures, data imputation for smart meters, and regulatory frameworks for grid safety. His work intersects technical innovation with policy considerations, addressing both European energy systems and global climate risks. Active in collaborative projects like InteGrid and InterFlex, he explores grid management services and functional scalability in distribution networks. Research outcomes include frameworks for assessing vulnerability of national economies to physical climate risks and taxonomies for local flexibility markets.

• Formal Verification
• Parallel and Distributed Systems
• GPU Programming
• +۴ مورد دیگر

GANESH GOPALAKRISHNAN is a Professor of Computer Science at the University of Utah's School of Computing. His work focuses on formal verification of parallel/distributed systems, GPU programming, and numerical error analysis. He has contributed to tools like ISP for MPI verification, ARCHER for OpenMP race detection, and FLiT for floating-point consistency testing. His research spans theoretical foundations (e.g., concurrency models) and practical applications (e.g., GPU error analysis). Recent work includes advancing formal methods for mixed-precision computing and resilience in exascale systems. Notable projects include rigorous error estimation for floating-point operations and compiler-assisted verification techniques. Research Interests: Formal Verification of Parallel Systems | GPU & HPC Correctness | Floating-Point Numerical Analysis | Concurrency Bugs | Tools for Distributed Systems. Current work emphasizes hybrid approaches combining formal methods with dynamic analysis to address emerging challenges in heterogeneous computing architectures. Articles Trends: Recent publications (2020–2025) emphasize GPU verification (data races, error analysis), mixed-precision computing (matrix operations, tensor cores), and resilience in HPC systems. Tools like FPDetect and BinFPE highlight practical contributions to error detection in production runs. Workshops (DOE/NSF) indicate leadership in defining correctness strategies for exascale computing. Labs/Teams: Leads research groups focused on formal methods for parallel computing and numerical system reliability. Collaborations include Argonne National Lab, NVIDIA, and LLNL on verification tools and HPC correctness frameworks.

Samuel Kounevمشاهده پروفایل

استاد

• Software Engineering
• Performance Engineering
• Autonomic Computing
• +۴ مورد دیگر

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.

• Quantum Computing
• Cybersecurity
• Artificial Intelligence
• +۵ مورد دیگر

Athanasios Vasilakos is a Professor at the University of Agder's Department of Information and Communication Technology. His research focuses on cutting-edge ICT domains including quantum computing, cybersecurity, and distributed systems. He maintains an extensive publication record with recent works concentrated in quantum machine learning, blockchain applications, and IoT security. Research interests span: Quantum computing architectures and cryptographic applications Secure federated learning frameworks for distributed networks AI-driven solutions for IoT and telecommunications systems Advanced cybersecurity techniques including steganalysis and homomorphic encryption Cross-domain applications in bioinformatics, smart grids, and autonomous vehicles Publication analysis reveals strong thematic focus on: security enhancements for emerging technologies (blockchain, quantum systems), privacy-preserving machine learning, and IoT optimization. Recent works demonstrate increasing attention to quantum-classical hybrid systems and their real-world implementations. Collaboration networks include extensive international partnerships across Europe and Asia, particularly in quantum computation, cybersecurity, and intelligent systems research.

Manoj M. Prabhakaranمشاهده پروفایل

استاد

• Cryptography
• Secure Multi-Party Computation
• Theoretical Computer Science
• +۹ مورد دیگر

Manoj M. Prabhakaran is the Vijay and Sita Vashee Chair Professor at the Indian Institute of Technology Bombay in the Department of Computer Science and Engineering , and an Adjunct Professor at the University of Illinois, Urbana-Champaign . His research spans Cryptography, Theoretical Computer Science, Algorithms, and Complexity Theory , with a focus on Secure Multi-Party Computation (MPC) and Zero-Knowledge Proofs . As Principal Investigator of the IITB Trust Lab , he has organized major events like the 2017 MPC School and Workshop . Education: Ph.D. in Computer Science His work explores foundational questions in Cryptography , including Randomness Complexity , Non-malleable Codes , and Homomorphic Encryption . Recent publications address Leakage-Resilient Cryptography and Interactive Proofs . He advises Ph.D. students like Debasish Ray Chawdhuri and Kaartik Bhushan , and his email is publicly listed.

Ünal ÇAVUŞOĞLUمشاهده پروفایل

دانشیار

• Cybersecurity
• Network Security
• Intrusion Detection Systems
• +۶ مورد دیگر

Prof. Dr. Ünal Çavuşoğlu is an Associate Professor at the Department of Software Engineering, Faculty of Computer and Information Sciences, Sakarya University. With a doctorate in chaos-based encryption algorithms (2016) and a master's degree comparing network simulation tools (2014), his research focuses on cybersecurity, machine learning, and chaos theory. He has contributed extensively to intrusion detection systems, IoT security, and cryptographic protocols. Education: Doctorate (2016), Master's (2014), and Bachelor's (2011) in Computer Engineering. Research Interests: Cybersecurity frameworks, machine learning adaptation for threat detection, chaotic encryption, and IoT communication protocols. Recent Work: 2025 publications on homomorphic encryption and LSTM-based intrusion detection demonstrate cutting-edge applications of deep learning in security domains. His 2019-2024 publications reveal a trajectory from foundational chaos theory to applied IoT and cloud security solutions. Key methodologies include genetic algorithms, fractional calculus, and hybrid encryption systems.

Abdullah SEVİNمشاهده پروفایل

استادیار

• Cryptography
• Internet of Things
• Blockchain
• +۳ مورد دیگر

Abdullah SEVİN serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences, a position held since 2017. Previously, he worked as a Research Assistant at Sakarya University (2009-2011) and American University of Sharjah (2014). His academic credentials include: Doctorate in Computer Engineering, Sakarya University (2011-2016), Thesis: A NEW MEDIA ACCESS CONTROL PROTOCOL WITH QUALITY OF SERVICE SUPPORT FOR WIRELESS BODY AREA NETWORKS Master's in Electronics and Computer Education, Sakarya University (2008-2011) Bachelor's in Computer Systems Teaching, Sakarya University (2004-2008) Dr. SEVİN's research integrates advanced cryptographic methods with emerging technologies. His primary expertise spans Cryptography—including hash functions, lightweight cryptography, and Torus fully homomorphic encryption (TFHE)—alongside Blockchain systems, Internet of Things (IoT) communication protocols, and Parallel Computing architectures. His performance analysis focuses on security testing of IoT application layers and cryptographic implementations, emphasizing real-world system optimization. No scientific awards were documented in the source material. Details regarding student supervision, research grants, laboratory facilities, or collaborative teams were not provided in the available text.

• Cryptography
• Security analysis of cryptographic algorithms
• Fully Homomorphic Encryption
• +۱ مورد دیگر

Håvard Raddum serves as Chief Research Scientist in the Department of Cryptography at Simula UiB, a joint research entity of Simula Research Laboratory and the University of Bergen. His primary focus involves advancing cryptographic security through algorithm analysis, Fully Homomorphic Encryption applications, and hardware-level attack mitigation. Raddum's research spans cryptography with specialization in security analysis of cryptographic algorithms, practical deployment of Fully Homomorphic Encryption, and physical attacks on hardware implementations. His work addresses vulnerabilities in symmetric ciphers, multivariate schemes, and lattice-based systems through algebraic cryptanalysis, side-channel techniques, and theoretical security proofs. Analysis of his 2019-2025 publications reveals concentrated expertise in cryptanalysis across diverse primitives. Key trends include algebraic attacks on arithmetization-oriented cryptography, side-channel analysis of lightweight ciphers, error detection in lattice computations, and security evaluations of Fully Homomorphic Encryption. His research consistently bridges theoretical frameworks with practical implementation vulnerabilities.

• Computational Biology
• Bioinformatics
• Privacy-Preserving Data Mining
• +۵ مورد دیگر

Kana Shimizu is a Professor at Waseda University’s Faculty of Science and Engineering, School of Fundamental Science and Engineering, and a leading authority on privacy-preserving algorithms for genome and biomedical data. Since obtaining her Dr.Eng. from Waseda, she has held positions at AIST and a visiting investigator role at Memorial Sloan-Kettering Cancer Center, advancing to full Professor at Waseda in 2018. Education: Dr.Eng., Waseda University M.Eng., Waseda University (Dept. of Information Science) B.Eng., Waseda University (School of Science and Engineering) Research Interests: Prof. Shimizu integrates cryptography with life-science data analytics, developing homomorphic encryption and secret-sharing protocols that enable secure genome search, private chemical database queries, and privacy-preserving machine learning. She also contributes to computational biology through algorithms for next-generation sequencing, structural bioinformatics, and prediction of intrinsically disordered proteins. Publication Trends: Her recent works (2022-2024) emphasize practical privacy technologies—secure range queries, function secret sharing, and gradient-clipping for synthetic genomes—while earlier high-impact papers established fast similarity search (SlideSort), binding-site databases (PoSSuM), and encrypted genomic search using the Burrows-Wheeler transform, collectively bridging algorithmic innovation and real-world biomedical privacy needs. Scientific Awards: KDDI Foundation Achievement Award 2022 MEXT Commendation for Science and Technology (Research) 2018 Multiple best-paper/demo awards at CSS, IIBMP, and domestic bioinformatics meetings Grants & Advising: She currently leads JSPS KAKENHI (S) on “Compressed Secure Computation for Large-Scale Data” and an AMED project on precise cancer-genome graphs. She serves as advisor/evaluator for JST PRESTO, AMED, NBDC, and the Tokyo High Court, and has supervised numerous bachelor theses at Waseda. Labs & Teams: Prof. Shimizu heads a laboratory within the School of Fundamental Science and Engineering at Waseda, collaborating with national centers (AIST, RIKEN) and international partners (MSKCC, Finland Tekes/AF), focusing on encrypted bioinformatics platforms and high-performance genomic algorithms.

Daniel Wichsمشاهده پروفایل

استاد

• Cryptography
• Computer Security
• Algorithms
• +۷ مورد دیگر

Daniel Wichs is a tenured Professor at the Khoury College of Computer Sciences at Northeastern University in Boston. He is a prominent researcher in the field of cryptography and serves as a Senior Scientist at NTT Research. His academic journey includes a PhD from New York University under Yevgeniy Dodis, a postdoctoral fellowship at IBM Research T.J. Watson, and degrees from Stanford University. Current Position: Professor at Northeastern University Prior Positions: IBM Josef Raviv Memorial Postdoctoral Fellow (2011-2013) Education: PhD NYU (2011), BS/MS Stanford (2005) Professor Wichs specializes in cryptography with research interests spanning computing on encrypted data, program obfuscation, lattice-based cryptography, information-theoretic cryptography, and foundational aspects of cryptography. He also maintains broad interests in computer security, algorithms, complexity theory, coding theory, and information theory. His research group includes current PhD students Manu Kondapaneni, LaKyah Tyner, and Ethan Mook, along with numerous successful alumni who have become professors at institutions worldwide. His recent publications demonstrate a strong focus on advanced cryptographic primitives including homomorphic encryption, zero-knowledge proofs, private information retrieval, and functional encryption. These works frequently appear at top-tier conferences like STOC, FOCS, CRYPTO, and EUROCRYPT, with several receiving best paper awards. His research often bridges theoretical foundations with practical applications in privacy-preserving computation. Best Paper at STOC 2023 Alfred P. Sloan Research Fellowship (2018) NSF CAREER Award (2018) J.P. Morgan Faculty Research Award (2022) IBM Postdoctoral Fellowship (2011-2013) Professor Wichs actively contributes to the academic community through service as Area Chair for CRYPTO 2025 and EUROCRYPT 2024, Program Chair for ITC 2020, General Chair for STOC 2016, and membership on numerous program committees. He teaches advanced courses including Foundations of Cryptography (CS 7810) and Theory of Computation (CS 3800), and has organized events like the Charles River Crypto Day and the Simons Summer Program in Cryptography 2025. His research group operates at the forefront of cryptographic theory, addressing fundamental questions about secure computation on encrypted data while developing practical cryptographic tools for real-world applications.

Anitha Gollamudiمشاهده پروفایل

استادیار

• Language-based Security
• Trusted Execution Environments
• Formal Methods
• +۴ مورد دیگر

Anitha Gollamudi is an Assistant Professor in the Department of Computer Science at the Miner School of Computer and Information Sciences, University of Massachusetts Lowell. She teaches core courses including Systems Security (COMP 5300), Compiler Construction (COMP 4060/5340), and Organization of Programming Languages (COMP 3010). Her research focuses on language-based security through hardware-assisted mechanisms, cryptography, and formal methods. Current projects include: Automatic compartmentalization of Trusted Execution Environment (TEE) programs Formal foundations of Fully Homomorphic Encryption (FHE) compilers Privacy-preserving machine learning with encrypted learning Analysis of her 8 recent publications (2016-2025) reveals dominant themes in TEE security and secure compilation. Key contributions address memory safety in WebAssembly, authorization logic for computation principals, and formal verification of cryptographic systems. Her work consistently bridges theoretical foundations with practical implementations for real-world security challenges. No scientific awards were mentioned in the available information. Professor Gollamudi actively mentors students across levels, currently advising PhD candidates Wesley B. Nuzzo and Samuel Dodson alongside undergraduate Benjamin Houle. Her former students include Nam Bui, James Chen, Yuka Akiyama (honors thesis), and Andrew Eggleston. She emphasizes collaborative research and encourages prospective students to contact her with research interests and academic background. She leads a research group focused on applying programming language techniques to security problems, with ongoing projects targeting enclave placement optimization, FHE correctness verification, and encrypted machine learning frameworks.