جست‌وجوی استاد و پژوهشگر

Riad Wahbyمشاهده پروفایل

استادیار

• Cryptography
• Zero-Knowledge Proofs
• Secure Computation
• +۱ مورد دیگر

Riad Wahby is an Assistant Professor in the Electrical and Computer Engineering department at Carnegie Mellon University's College of Engineering, with affiliations in the Computer Science Department. His research focuses on theoretical computer science with applications in cryptography and security systems. Primary research areas include: Zero-knowledge proof systems and SNARKs Secure multiparty computation Cryptographic protocol design Formal verification methods His publications demonstrate consistent innovation in cryptographic compilers, constraint systems for SNARKs, and practical applications of zero-knowledge proofs. Recent work highlights include advancements in finite-field verification, decentralized auction systems, and side-channel attack analysis. Current advising includes graduate students Quang Dao and Kunming Jiang. Teaching includes courses in computer systems and cryptography (15-330).

• Formal Methods
• Programming Languages
• Concurrency Theory
• +۳ مورد دیگر

Marco Giunti is a Researcher at the University of Oxford's Department of Computer Science. His work focuses on formal methods, programming languages, and distributed systems, with a particular emphasis on session types, concurrency theory, and blockchain technology. He explores topics such as typestate systems, formal verification, and secure channel abstractions. Recent research highlights include advancements in iso-recursive multiparty sessions, blockchain consensus mechanisms (e.g., Lupin), and data-centric synchronization frameworks like AtomiS. His contributions bridge theoretical foundations with practical applications, addressing challenges in distributed systems and static analysis. Giunti's publications span technical reports and peer-reviewed articles, showcasing innovations in automated verification, type systems, and concurrency control. His work often emphasizes the intersection of formal methods and real-world distributed computing scenarios.

Alex Schwarzmannمشاهده پروفایل

استاد

• Cyber Security
• Distributed Computing
• Election Integrity
• +۳ مورد دیگر

Alex Schwarzmann is a Professor and Dean in the Department of Computer Science at Augusta University's School of Computer and Cyber Sciences. He holds a Ph.D. and MS in Computer Science from Brown University (1992, 1989) and an MS from Cornell University (1981). His research focuses on distributed computing systems, cyber security, election integrity, and cryptographic protocols. He has led initiatives in secure distributed storage systems, fault-tolerant algorithms, and voting system security. Notably, he received the 2022 and 2010 Edsger W. Dijkstra Prizes in Distributed Computing for foundational contributions to the field. His work integrates theoretical rigor with practical applications, such as developing robust frameworks for election-day voter check-in and securing atomic memory operations. He has served as Committee Chair for the 5th International Symposium on Cyber Security Cryptology and Machine Learning (CSCML 2021). His research spans distributed consensus algorithms, intrusion detection mechanisms, and privacy-preserving technologies in networked systems. Recent publications highlight advancements in atomic storage systems, low-latency distributed memory, and mitigating vulnerabilities in multi-source transfer learning. His grants include NSF funding for secure voting systems and resilient distributed frameworks.

• Cyber Security
• Applied Cryptography
• IoT Security
• +۴ مورد دیگر

Dr. Abid Khan is a Senior Lecturer in Cyber Security at the School of Computing and Engineering, University of Derby, England. Previously, he held roles at Aberystwyth University and COMSATS University Islamabad. His research focuses on applied cryptography, privacy in IoT, blockchain, and secure smart grid systems. He is a Senior Member of IEEE and serves as an Associate Editor for IEEE Access. Education: PhD in Computer Science (Harbin Institute of Technology, China), MS in Computer Science (Quaid-i-Azam University, Pakistan), BS in Maths and Physics (University of Punjab, Pakistan). His postdoctoral research at Politecnico di Torino, Italy, focused on e-security. Research interests include secure data aggregation in smart grids, quantum-resistant distributed ledgers, and privacy preservation in vehicular networks. Recent work emphasizes blockchain applications for healthcare data provenance and IoT security frameworks. Teaching responsibilities include modules on Communication & Security Protocols, Security Management, and Enterprise Security Management. His publications span privacy-preserving techniques, blockchain-based solutions, and VANET security. He has contributed frameworks like BCALS (blockchain-based log management) and MobChain (collusion-resistant location proof systems). His work addresses challenges in decentralized systems, fog computing, and federated learning privacy.

Bernardo Luís Portelaمشاهده پروفایل

پژوهشگر

• Cryptography
• Information Security
• Secure Multiparty Computation
• +۳ مورد دیگر

Bernardo Luís Portela is a Senior Researcher at HASLab/INESC TEC since January 2014 and a fourth-year Ph.D. student in the MAPi doctoral programme at the University of Minho. His research focuses on cryptography, information security, and secure multiparty computation (MPC) leveraging trusted hardware. He contributes to projects like SafeCloud and NanoSTIMA, advancing high-assurance MPC protocols by bridging theoretical and practical implementations. Education: M.Sc. in Informatics Engineering from the University of Minho. Research Interests: Specializes in secure MPC protocols using Isolated Execution Environments (IEEs), privacy-preserving machine learning, and distributed system security. His work includes formalizing security guarantees for IEEs and hybrid schemes for efficient ML computation. Advising & Projects: Supervised multiple theses on topics like telecom fraud detection, speculative execution resilient cryptography, and TLS 1.3 C2 traffic analysis. Active in collaborative projects addressing cloud security and distributed system vulnerabilities. Labs/Teams: Member of HASLab/INESC TEC, contributing to high-assurance software solutions for distributed systems and network security.

Marino Miculanمشاهده پروفایل

استاد

• Cybersecurity
• Formal Methods
• Distributed Systems
• +۳ مورد دیگر

Marino Miculan is a Professor of Computer Science at the University of Udine, leading the MADS Lab and Cybersecurity Lab. His research focuses on formal methods, cybersecurity, and distributed systems, with an emphasis on verifying security in concurrent systems. He has authored over 100 publications and contributed to 16 research projects. His research interests include formal verification of security protocols, distributed computing architectures, and the application of category theory to system modeling. He has developed frameworks like Netstaldi for network discovery and tools such as DBCChecker for analyzing container compositions. Miculan’s work bridges theoretical foundations (e.g., adhesive categories, behavioral equivalences) with practical applications in IoT security, multi-factor authentication, and cloud containerization. His labs explore cutting-edge topics like continuous learning for anomaly detection and stateful access control mechanisms.

• Privacy-Preserving Machine Learning
• Cryptography
• Health Informatics
• +۳ مورد دیگر

Helen Möllering is a researcher at the Technical University of Darmstadt, Germany. She holds a PhD in Computer Science from the same institution, awarded in 2023 for her thesis titled "Towards Practical Privacy-Preserving Clustering and Health Care Data Analyses" . Her research focuses on privacy-preserving techniques in machine learning, cryptography, and healthcare data analysis. Key areas include federated learning, secure multiparty computation, and applications in medical data privacy. PhD: Technical University of Darmstadt (2023) Primary Affiliation: Technical University of Darmstadt Her work emphasizes balancing privacy and utility in data-driven systems, particularly in healthcare and epidemiological modeling. Notable collaborations include projects with Thomas Schneider, Benny Pinkas, and Hossein Yalame on secure aggregation protocols and privacy-preserving clustering algorithms. Recent publications highlight advancements in federated learning security, such as "ScionFL" and "BOLT" , which address robustness and efficiency in distributed machine learning systems. She also contributes to applications like secure kidney exchange problem solutions and epidemiological modeling under privacy constraints. Co-author networks include prominent researchers in cryptography and data security, reflecting her interdisciplinary approach to tackling privacy challenges in computational systems.

José Proençaمشاهده پروفایل

مدرس

• Component-based systems
• Distributed systems
• Software engineering
• +۳ مورد دیگر

José Proença is a Lecturer and Integrated PhD Researcher at CISTER Research Centre, ISEP, Portugal. He is currently a postdoc focusing on formal models for component-based systems. Previously, he worked at HASLab (University of Minho) and Distrinet (KU Leuven), collaborating with researchers like Luís Barbosa, Danny Hughes, and Dave Clarke. His expertise includes coordination of distributed components (Reo language), software product line engineering, and embedded systems (LooCI middleware and VirtuosoNext RTOS). Education: 5-year degree in Mathematics and Computer Science from University of Minho, with an Erasmus exchange at Bristol University, UK. PhD in Computer Science from Leiden University (2011), conducted at CWI, Amsterdam, in the Foundations of Software Engineering group. Research interests span formal methods, distributed systems, embedded systems, and software engineering. He has contributed to projects like IBEX (quantitative cyber-physical programming) and MARS (toolset for real-time systems). His work emphasizes practical applications of formal models in real-time and safety-critical systems. Publications focus on coordination models, multiparty session types, and formal verification, with contributions to journals like Science of Computer Programming and conferences such as COORDINATION and FMAS. He actively collaborates on tools like CAOS (Scala framework) and ARx (reactive programming for connectors).

• Cryptography
• Cryptographic Voting Systems
• Key Exchange Protocols
• +۴ مورد دیگر

Kristian Gjøsteen is a Professor at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU). He holds a MSc and PhD from NTNU and is part of the Algebra Group. His research focuses on cryptographic systems, including voting protocols, key exchange mechanisms, cloud security, and formal verification of cryptographic proofs. Gjøsteen has contributed to Norwegian government projects on electronic voting (2009-2013) and electronic identification systems. He served on the Norwegian Government’s Committee on Digital Vulnerabilities (Lysne-utvalget). Research interests include cryptographic voting systems, key exchange protocols (with a focus on forward secrecy and tight security proofs), privacy-preserving technologies in blockchain and cloud environments, and formal methods for verifying security protocols. Notable work includes development of coercion-resistant voting systems, lattice-based cryptographic schemes for voting, and machine-checked proofs of accountability. Publications highlight advancements in secure voting systems, post-quantum cryptography, and protocols for constrained networks. Collaborations span international researchers in cryptography and security. His textbook Practical Mathematical Cryptography (2022) provides foundational insights into applied cryptographic techniques. Professional activities include advising on national cybersecurity initiatives and contributing to the design of secure electronic voting infrastructure. Current projects emphasize privacy-preserving blockchain systems and formal verification of cryptographic protocols.

Michele Ciampiمشاهده پروفایل

پژوهشگر ارشد

• Cryptography
• Zero-Knowledge Proofs
• Multi-Party Computation
• +۳ مورد دیگر

Michele Ciampi is a Chancellor's Fellow at the University of Edinburgh's School of Informatics, specifically within the Laboratory for Foundations of Computer Science. His research focuses on cryptographic theory, including zero-knowledge proofs, multi-party computation, and blockchain protocols. He holds a PhD in Computer Science from the University of Salerno (2018), where his thesis earned the Best PhD Thesis in Theoretical Computer Science Award (2018). Prior roles include a Visiting Graduate Researcher at UCLA (2016) and research associate at the University of Edinburgh's blockchain lab (2018–2021). Education: Bachelor's in Computer Science, University of Salerno (2012) Master's in Computer Science, University of Salerno (2014) PhD in Computer Science, University of Salerno (2018) Research interests emphasize theoretical foundations of secure computation, with a focus on cryptographic protocol design, blockchain scalability, and privacy-preserving technologies. His work bridges formal security models with practical implementations, often addressing round complexity and computational efficiency. Key contributions include agile cryptography frameworks, list oblivious transfer protocols, and non-malleable schemes. Recent projects include Inclusive Open Finance Passport (2023–2026) and multiple EPSRC-funded initiatives on privacy-preserving data linkage and digital identity systems. He has received grants totaling over £2M for research in decentralized finance and cryptographic infrastructure. Labs/Teams: Active in the Edinburgh Blockchain Technology Lab and collaborates internationally with institutions like UCLA and Aarhus University.

Rukshan Athaudaمشاهده پروفایل

مدرس ارشد

• Cloud Computing
• Educational Technology
• Database Systems
• +۳ مورد دیگر

Dr. Rukshan Athauda is a Senior Lecturer at the University of Newcastle, affiliated with the School of Information and Physical Sciences (Computing and Information Technology). He holds a PhD in Computer Science from Florida International University and has over 15 years of academic and industry experience. His roles include leadership positions such as Program Convenor for multiple degree programs and RHD Coordinator. Research Expertise: His work spans Database Systems, Educational Technology, Cloud Computing, and IT Security. Notable projects include frameworks for collaborative music post-production, virtual labs in education, and trust models in digital ecosystems. He has co-authored 75+ publications and attracted $741K in grants. Teaching: Currently teaches Systems and Network Administration and Cloud Computing. Previously developed courses in databases and IT systems at the University of Moratuwa and SLIIT in Sri Lanka. Professional Activities: Editorial board member of the International Journal of Computer and Information Technology. Keynote speaker at multiple conferences and recipient of awards for collaboration and teaching innovation. Grants & Supervision: Lead 19 grants, including projects on transport scheduling and learning analytics. Supervised 10+ PhD/Masters projects on topics like cybersecurity, learning frameworks, and fog-cloud environments.

Vincent Leeمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Signal Processing
• +۷ مورد دیگر

Dr. Vincent Lee is an Associate Professor in the Department of Data Science & AI at Monash University's Faculty of IT. He specializes in machine learning, deep learning, and healthcare informatics. His research spans signal processing, data mining, and AI-driven solutions for healthcare and finance. Lee has secured over 22 competitive grants and published 200+ peer-reviewed articles in top journals like IEEE Transactions and Neurocomputing. He is a Fellow of the Institute of Engineers, Australia, and a registered electrical engineer in Singapore. Education: PhD in Computer System Engineering (University of Newcastle, 1992) MBA (Brunel University London, 1991) MSc in Electrical Engineering (NUS, 1984) BBus (Hons I) in Economics and Finance (RMIT, 2002) Research Interests: Lee's work focuses on AI/ML applications in healthcare (e.g., thyroid cancer diagnostics), secure multiparty computation, IoT analytics in precision medicine, and neuro-financial engineering. He has developed decision support systems for ICU patient care and thyroid treatment analytics. Recent projects include ESV-ML OCR pipeline design and Tokopedia's recommendation systems. Grants & Awards: Recipient of Monash University's 2016 Dean of IT Excellence Award for Supervision. Principal investigator on 12+ projects funded by ARC, A*STAR, and industry partners like Energy Safe Victoria. Teaching & Supervision: Supervised 30+ PhD and 35+ master's students. Taught courses like FIT3051 (Decision Support Systems), FIT5186 (Intelligent Systems), and FIT5163 (Computer Security). Labs & Collaborations: Leads research in AI-driven healthcare systems and secure distributed computing. Collaborates with Tsinghua University, Singapore's Infocomm Institute, and industry partners like Tokopedia.

Aloni Cohenمشاهده پروفایل

استادیار

• Cryptography
• Privacy
• Law
• +۳ مورد دیگر

Aloni Cohen is an Assistant Professor of Computer Science and Data Science at the University of Chicago. Previously, he served as a Postdoctoral Associate at Boston University, with a joint appointment at the Hariri Institute for Computing and the School of Law. He is also a former affiliate at the Berkman Klein Center for Internet & Society and a Fellow at the Aspen Tech Policy Hub. Aloni earned his PhD in Electrical Engineering and Computer Science from MIT, advised by Shafi Goldwasser, supported by a Facebook Fellowship and an NSF Graduate Student Research Fellowship. His research bridges theoretical cryptography, privacy, law, and policy, focusing on real-world applications like differential privacy, encryption, and legal frameworks such as GDPR and the Fifth Amendment. Key research themes include privacy-preserving data analysis, cryptographic watermarking, and ethical implications of AI. He explores tensions between cryptographic theory and legal regulations governing data privacy and surveillance. His recent publications address topics such as the societal impacts of differential privacy, legal challenges in compelled decryption, and policy questions around multiparty computation. Notable awards include the 2024 Outstanding Paper Award at the International Conference on Algorithmic Learning Theory and the 2022 Distinguished Paper Award at USENIX Security Symposium. Awards: 2024 Outstanding Paper Award, International Conference on Algorithmic Learning Theory 2022 Distinguished Paper Award, USENIX Security Symposium 2014 NSF Graduate Student Research Fellowship Aloni’s work involves interdisciplinary collaborations, addressing both technical and policy dimensions of modern computational challenges. Details on grants or specific advising roles are not explicitly listed in the provided texts.

Michael Hicksمشاهده پروفایل

استاد بازنشسته

• Software Security
• Programming Languages
• Quantum Computation
• +۳ مورد دیگر

Michael Hicks is a Senior Principal Scientist at Amazon Web Services (AWS), focusing on automated reasoning and test generation, and a Professor Emeritus at the University of Maryland (UMCP). He co-led the development of the Cedar authorization language for AWS Verified Permissions. Previously, he was Chair and Past Chair of ACM SIGPLAN, and Editor-in-Chief of PACMPL. His research spans secure programming, quantum computation, and secure multiparty computation. He holds a PhD in Computer and Information Science from the University of Pennsylvania and has been affiliated with UMIACS and the Maryland Cybersecurity Center (MC²). His research interests include improving software security and reliability through techniques like the Build-it-Break-it-Fix-it contest, Checked C extensions for C safety, and quantum programming languages like VOQC. He has advised numerous students, many of whom hold prominent academic and industry roles. Hicks has received recognition including Distinguished Paper awards at ICSE 2025 and OOPSLA 2022. He has taught courses on programming languages, software security, and formal methods, and contributed to conferences like POPL, PLDI, and OOPSLA.

• Bioinformatics
• Machine Learning
• Network Science
• +۴ مورد دیگر

Anne Hartebrodt is a Postdoctoral Researcher at the Biomedical Network Science Lab in the Department of Artificial Intelligence in Biomedical Engineering at Friedrich-Alexander University Erlangen-Nürnberg (FAU), Germany. She has been working at FAU since March 2023, focusing on network-based embeddings and carbon-aware computing for bioinformatics following her PhD completion at the University of Southern Denmark. Her research spans multiple cutting-edge domains at the intersection of AI and biomedical science: Bioinformatics and computational biology with emphasis on network science Federated learning and privacy-preserving computation for biomedical applications Single-cell omics analysis and gene regulatory network inference Carbon-aware computing for sustainable bioinformatics research Machine learning applications in proteomics and cancer research Dr. Hartebrodt's publication record demonstrates expertise in developing computational methods that bridge theoretical machine learning with practical biomedical challenges, particularly in maintaining data privacy while enabling collaborative research across institutions. Her work on federated learning approaches has been published in high-impact journals including Nature Computational Science and Bioinformatics. Her research leadership includes: Principal investigator for the 'Dimensionality reduction for molecular data based on explanatory power of differential regulatory networks' project (NetMap) funded by the Bundesministerium für Forschung, Technologie und Raumfahrt (2023-2026) Development of FedProt for privacy-preserving protein analysis Creation of Decoil for reconstructing extrachromosomal DNA structures Advancements in federated singular value decomposition methods Dr. Hartebrodt actively supervises multiple graduate students working on gene regulatory networks, differential expression analysis, and carbon-aware optimization. Her laboratory work in the Biomedical Network Science Lab focuses on developing innovative approaches to analyze complex biological networks while addressing computational sustainability through carbon-aware computing methods.