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Jiankun HuView profile

Professor

• Cyber Security
• Intrusion Detection
• Applied Cryptography
• +16 more

Professor Jiankun Hu is an IEEE Fellow and full professor of Cyber Security at the School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy (UNSW@ADFA), Australia. His primary research focuses on computer networking and security, particularly biometric security and cybersecurity applications. Professor Hu earned his Bachelor's degree in industrial automation in 1983 from Hunan University, China, followed by a PhD in engineering in 1993 from Harbin Institute of Technology, China. He completed a Master's degree in computer science and software engineering from Monash University, Australia in 2000. His postdoctoral work includes research at Harbin Shipbuilding College (1995), Ruhr University in Germany as an Alexander von Humboldt Foundation fellow (1995-1997), and Delft University of Technology in the Netherlands (1997). His research spans multiple domains including cybersecurity, biometrics, image processing, and artificial intelligence. Key areas include intrusion detection systems, applied cryptography, network security, biometrics security, image and video processing, and machine learning applications. He has made significant contributions to fingerprint recognition systems, privacy-preserving biometric authentication, and cybersecurity for smart grids. Professor Hu's recent publications demonstrate a strong focus on privacy-preserving technologies for biometric systems, blockchain security, smart grid protection, and advanced machine learning applications for cybersecurity. His work bridges theoretical advances with practical implementations in real-world systems, particularly in securing critical infrastructure and developing robust biometric authentication methods. He has received significant recognition including IEEE Fellow status and has been awarded ten Australian Research Council Grants. He has served in editorial roles for prestigious journals including IEEE TIFS (as Senior Area Editor), Journal of Security and Communication Networks, KSII TIIS, IET CPS, and IEEE OJCS. Professor Hu has held leadership positions in major conferences, serving as Security Symposium Co-Chair for IEEE GLOBECOM '08 and IEEE ICC '09, and Program Co-Chair of the 2008 International Symposium on Computer Science and its Applications. He maintains an active research program with numerous publications across top-tier venues.

Shidrokh GoudarziView profile

Senior Lecturer

• Wireless Networks
• Artificial Intelligence
• Machine Learning
• +3 more

Shidrokh Goudarzi is a Senior Lecturer in Computer Science at the School of Computing and Engineering, University of West London. She previously held academic positions at the Centre for Vision, Speech, and Signal Processing (CVSSP) at the University of Surrey and as a senior lecturer at Universiti Kebangsaan Malaysia (UKM). She holds a PhD in Communication Systems and Wireless Networks. Her research focuses on wireless networks, artificial intelligence, machine learning, IoT, and cloud computing, with contributions to resilient IoT technologies and smart city applications. She has designed architectures for smart IoT systems and developed models for distributed communications and vehicular networks. Her work bridges theoretical advancements with industry-relevant solutions. Dr. Goudarzi serves on the editorial boards of high-ranked journals including IEEE Transactions on Industrial Informatics and IEEE Transactions on Network Science and Engineering. She also reviews for reputable journals like Computational Intelligence and KSII Transactions on Internet and Information Systems. She teaches courses such as MSc Communication Systems, BSc Computer Science, and BSc Artificial Intelligence, reflecting her expertise in both theoretical and applied computing disciplines.

Gabriel GhinitaView profile

Associate Professor

• Databases
• Information Security
• Privacy
• +5 more

Gabriel Ghinita is an Associate Professor in the Department of Computer Science at the University of Massachusetts at Boston. He holds a Ph.D. in Computer Science from the National University of Singapore (2008) and a B.S. from the 'Politehnica' University of Bucharest (2003). His research focuses on databases, information security, privacy, and spatio-temporal data management. During the 2018/19 academic year, he was a Visiting Associate Professor at the University of Southern California. Key research interests include privacy-preserving sharing of location data, secure data provenance, and privacy-aware network measurement. He teaches courses such as Database Management Systems and IT Network Security. Professional activities include serving on program committees for top venues like SIGMOD, ICDE, and ACM GIS, and as a PC Chair for CODASPY 2016. His work emphasizes balancing utility and privacy in data-driven systems, with contributions to differential privacy, secure spatial queries, and IoT security.

• Porous Media Flow
• Geological Carbon Sequestration
• Subsurface Energy Systems
• +2 more

Dr. Cheng Chen is Associate Professor and Nariman Farvardin Professor in the Department of Civil, Environmental and Ocean Engineering at Stevens Institute of Technology. He directs the Subsurface Energy, Water and Environmental Systems (SEWES) Lab, focusing on porous media transport phenomena through combined computational and experimental approaches. His NSF and DOE-funded research addresses multiphase flow in geological formations for carbon sequestration, shale energy recovery, and nuclear waste disposal. Recent work integrates machine learning for scale-bridging data assimilation and distributional reinforcement learning for autonomous marine systems. Chen's methodological innovations include lattice Boltzmann simulations for pore-scale analysis and Gaussian process models for uncertainty quantification. Scholarly outputs demonstrate consistent focus on energy-geoscience interfaces, with recent expansion into privacy-preserving federated learning applications for IoT systems. His 2023-2024 publications increasingly address security challenges in distributed computing and adversarial machine learning. Major Recognition: Stanford Top 2% Most Cited Scientist (2023) Nariman Farvardin Endowed Professorship Chen teaches numerical methods in environmental engineering and subsurface flow modeling, maintaining industrial partnerships with Schlumberger, SeaRobotics, and Consolidated Edison. He holds editorial roles for SPE Journal and has authored over 60 peer-reviewed publications.

• Cryptography
• Blockchain
• Cybersecurity
• +2 more

Fatemeh Rezaeibagha is Senior Lecturer in Cyber Security at Murdoch University's School of Information Technology. Her research develops cryptographic solutions for blockchain systems, IoT security, and privacy-preserving protocols. Awards include the Associate Fellow teaching certificate (2019) and Murdoch Fellowship (2023). Recent publications focus on: privacy-enhanced data sharing for medical IoT; redactable blockchain architectures; attribute-based access control; and lattice-based cryptography. Applied contributions include traceability-revocation schemes for industrial IoT and accountable systems for vehicular networks. Research emphasizes efficiency and post-quantum security in distributed environments.

Daniel GardhamView profile

Lecturer

• Cryptography
• Post-Quantum Cryptography
• Information Security
• +4 more

Dr. Daniel Gardham is a Lecturer at the University of Surrey, affiliated with the Surrey Centre for Cyber Security and the School of Computer Science and Electronic Engineering. He teaches modules such as Privacy Enhancing Technologies (COM3030) and Data Structures & Algorithms (COM1029). His research focuses on applied cryptography, including privacy-preserving techniques, authentication protocols, and post-quantum cryptography using lattice-based methods. Previously, he was a postdoctoral researcher at Royal Holloway, University of London, and earned his PhD from the University of Surrey in 2021 under Mark Manulis, exploring attribute-based signatures in classical and post-quantum contexts. Education: PhD in Computer Science (University of Surrey, 2021), MMath in Mathematics (University of Bath, 2017). Research interests include developing cryptographic protocols for secure communication, post-quantum security solutions, and enhancing user privacy through authentication mechanisms. His recent work addresses phishing awareness for older adults and oblivious PRFs leveraging homomorphic encryption. Publications span topics like asynchronous key generation, hierarchical attribute-based signatures, and biometric authentication systems. He contributes to cybersecurity through interdisciplinary research, bridging theoretical cryptography with practical applications. Labs/Teams: Active in the Surrey Centre for Cyber Security and the Computer Science Research Centre, advancing cryptographic innovation and cybersecurity education.

Mark ManulisView profile

Professor

• Privacy-enhancing technologies
• Cryptography
• Cybersecurity
• +5 more

Prof. Dr. Mark Manulis is a Full Professor at the Department of Computer Science, Universität der Bundeswehr München, Germany, and a Visiting Professor at the Surrey Centre for Cyber Security, University of Surrey, UK. He heads the Privacy and Applied Cryptography (PACY) Lab and specializes in cryptographic protocols, privacy-enhancing technologies, and cybersecurity. His research focuses on secure communication, blockchain, IoT security, and decentralized systems. Education: Earned his Dr.-Ing. (PhD) in 2007 from Ruhr-Universität Bochum under advisors Jörg Schwenk and David Pointcheval. Held positions at TU Darmstadt, University of Surrey, and UCL Crypto Group. Research interests include authentication protocols, cryptographic primitives, and privacy-preserving systems. Notable awards include the Best Paper Award at ISC 2016 and E-Teaching Award 2010. Supervises PhD students and mentors researchers in cryptographic protocol design and analysis. Publications span over 150 papers in top venues like ACM CCS, EUROCRYPT, and IEEE S&P. Active in academic service, including program chair roles at ACNS and SECITC. Leads research projects on post-quantum cryptography and decentralized key generation.

Joseph LiuView profile

Professor

• Cyber Security
• Blockchain Technology
• Applied Cryptography
• +5 more

Joseph Liu is a Full Professor at Monash University's Faculty of Information Technology, leading the Monash Cybersecurity Discipline Group and founding director of the Monash Blockchain Technology Centre. He holds a PhD from the Chinese University of Hong Kong (2004) and has pioneered research in blockchain security, linkable ring signatures (underpinning Monero cryptocurrency), and applied cryptography. His work spans cloud security, healthcare privacy, and lightweight cryptographic algorithms. He has received over 10,000 citations and 200+ publications in top venues like CRYPTO and ACM CCS. Awards include the 2018 ICT Researcher of the Year (ACS) and 2021 IEEE Technical Achievement Award. Education: PhD Information Engineering, Chinese University of Hong Kong (2004) MPhil Information Engineering, Chinese University of Hong Kong (2001) BEng Information Engineering, Chinese University of Hong Kong (1999) Research focuses on bridging cryptographic theory with real-world applications, emphasizing privacy-preserving technologies and post-quantum security. Recent projects include the Algorand Centre of Excellence for Sustainability Informatics and ethical frameworks for blockchain-based digital credentials. He has led 22+ research projects and contributed to ISO/IEC blockchain standards. Awards: ACS ICT Researcher of the Year 2018 IEEE Technical Achievement Award 2021 Best Paper Awards (2021–2022) Teaching includes courses like FIT2034 and FIT5043. He co-chairs the IEEE Blockchain Australia Chapter and has organized major conferences (e.g., ProvSec, Pairing). Current initiatives include privacy-preserving AI in materials discovery and scalable blockchain systems.

• Secure Systems
• Operating Systems
• Distributed Systems
• +5 more

Nickolai Zeldovich is the Joan and Irwin M. (1957) Jacobs Professor of Electrical Engineering and Computer Science at MIT and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on building practical secure systems through the integration of formal methods with real-world system design. His research interests span secure systems, operating systems, distributed systems, formal verification, and cryptography. Recent work emphasizes automated reasoning for distributed system liveness, leakage-free hardware security modules, and privacy-preserving web technologies. Projects include CryptDB (encrypted databases), FSCQ (verified file systems), Algorand (cryptocurrency), and Vuvuzela (private messaging). His publication trends show consistent output in formal verification of distributed systems (Shipwright, Grove), hardware security (K2 Architecture), and privacy technologies (Tiptoe). Recent work increasingly combines theoretical verification with practical implementation constraints. Best Paper Awards at ACM SOSP (2013, 2015, 2017) Sloan Research Fellowship (2010) NSF CAREER Award (2011) MIT EECS Jamieson Award for Excellence in Teaching (2024) ACM SIGOPS Mark Weiser Award (2017) Amazon Research Award (2023) He advises PhD students through the PDOS research group with active grants from Amazon, Google, NSF, and DARPA. His teaching includes core courses like Computer Systems Security and Operating System Engineering, emphasizing hands-on security analysis. The PDOS lab maintains strong industry connections with multiple startup spin-offs and regular technology transfer to production systems. He leads the PDOS (Parallel and Distributed Operating Systems) Research Group, which focuses on building verified, secure, and high-performance systems through close collaboration between theory and practice.

• Artificial Intelligence
• Cybersecurity
• Privacy-Preserving Computation
• +12 more

Florian Werner Hahn is an Assistant Professor specializing in Artificial Intelligence , Cybersecurity , and Privacy-Preserving Computation , with a focus on areas like Homomorphic Encryption , Biometric Template Protection , and Searchable Symmetric Encryption . His research explores secure protocols for data aggregation, attack modeling, and privacy-preserving machine learning techniques. Department: Semantics, Cybersecurity & Services ORCID: 0000-0003-4049-5354 Research Interests Dr. Hahn's work addresses critical challenges in privacy-preserving technologies , including secure biometric authentication, encrypted data analytics, and vulnerability assessment of machine learning models. His studies on Membership Inference Attacks and Secure Shuffling advance the understanding of data leakage risks and mitigation strategies. Scientific Awards Recipient of the Dutch Cyber Security Best Research Paper (DCSRP) award 2024 in the multidisciplinary track, recognizing his contributions to balancing user privacy with practical system expectations. Collaborations Active in external collaborations across countries, working with researchers like Peter, A. , Damie, M. , and Veldhuis, R. to develop secure protocols for biometric systems and clustering algorithms.

Benjamin FullerView profile

Associate Professor

• Cryptography
• Applied Cryptography
• Information Theory
• +4 more

Benjamin Fuller is an Associate Professor of Computer Science and Engineering at the University of Connecticut (UConn), serving as co-director of the Connecticut Advanced Computing Center. Prior to UConn, he worked at MIT Lincoln Laboratory (2007–2016) and completed his Ph.D. at Boston University under the BUSEC research group. His research focuses on cryptography, including searchable encryption, authentication from noisy sources, and secure group communication. He actively participates in organizing the New England Security Day conference and advises UConn’s cybersecurity club. His work bridges theoretical cryptography with practical implementations, emphasizing privacy, security, and efficient cryptographic protocols. Education: Ph.D. in Computer Science, Boston University (BUSEC Group) MIT Lincoln Laboratory (2007–2016) Research Interests: Dr. Fuller’s work spans cryptography, information theory, and applied security. Key areas include: secure searchable encryption for encrypted data, cryptographic authentication using biometrics and hardware tokens (e.g., PUFs), and improving fuzzy extractors for noisy sources like iris scans. He emphasizes practical deployments, such as secure chat systems and cryptographic protocols for dynamic groups. Recent Work Trends: His 2020–2025 publications address challenges in biometric security (e.g., iris-based authentication), election integrity via risk-limiting audits, and theoretical foundations of fuzzy extractors. He also explores adversarial machine learning applications in voting systems and privacy-preserving encryption techniques for scalable data storage. Labs/Teams: Leads the Connecticut Advanced Computing Center and co-organizes UConn’s security seminar. Collaborates widely with academic and industrial partners across cryptography and cybersecurity domains.

• Artificial Intelligence
• Explainable AI
• Human-Computer Interaction
• +5 more

Yunfeng Zhang is a Professor at Shandong University of Finance and Economics specializing in Artificial Intelligence with significant contributions to Explainable AI, Human-Computer Interaction, and Machine Learning. His research spans computer vision, fairness in AI, and robotics applications across diverse domains including transportation, agriculture, and cybersecurity. Zhang has established strong international collaborations with IBM Research (notably with Kush Varshney and Q. Vera Liao) and publishes extensively in top venues like CHI, KDD, and IEEE Transactions. His research interests focus on making AI systems transparent and trustworthy through the AI Explainability 360 toolkit development since 2020, human-AI collaboration frameworks, and fairness optimization in machine learning. Recent work shows a strategic pivot toward applied AI problems including urban rail transit optimization, agricultural robotics for citrus detection, and VR-enhanced education systems in China. Zhang's publications demonstrate exceptional breadth across both theoretical foundations and real-world implementations of AI technologies. Zhang's recent publications (2023-2025) reveal strong trends in multimodal AI applications, with significant work in computer vision for remote sensing and industrial automation, reinforcement learning for transportation systems, and educational technology innovations. His work consistently bridges technical AI development with human-centered design principles, particularly evident in his CHI publications on human-AI collaboration interfaces. Co-developer of the influential AI Explainability 360 open-source toolkit (JMLR 2020) Key contributor to Uncertainty Quantification 360 framework Active participant in ACM FAccT conferences on AI fairness Principal investigator on multiple Chinese national research grants for AI applications Zhang leads research teams developing practical AI solutions for Chinese industry challenges, particularly in transportation optimization and agricultural technology. His lab maintains strong industry partnerships with Chinese railway authorities and agricultural technology firms, focusing on implementing AI systems that address specific local infrastructure and productivity challenges while maintaining rigorous academic standards.

Julieanna Powell-TurnerView profile

Professor

• Environmental Sustainability
• Climate Change Resilience
• Resource Security
• +2 more

Julieanna Powell-Turner is Professor of Environmental Organisational Sustainability and Associate Dean for Research and Innovation at the University of Chester's Faculty of Science, Business and Enterprise. She leads the Centre for Research into Environmental and Sustainable Transitions (CREST), driving interdisciplinary work on climate resilience, resource security, and social cohesion aligned with UN SDGs. With 20+ years in sustainability research, she has secured significant UKRI funding and supervised doctoral projects in decarbonization and green skills. Her recent publications focus on climate action governance (2025), corporate sustainability barriers (2025), and semantic access controls for healthcare systems (2022-2024). Powell-Turner oversees institutional research frameworks including REF/KEF and manages postgraduate programs, emphasizing participatory action research and cross-sector partnerships.

Qiang TangView profile

Associate Professor

• Cryptography
• Blockchain Technology
• Privacy and Security
• +3 more

Associate Professor Qiang Tang is a faculty member at the School of Computer Science, The University of Sydney. He holds an academic rank of Associate Professor and has previously held roles including Assistant Professor at NJIT and postdoctoral researcher at Cornell University. His research focuses on cryptography, blockchain technology, privacy, and distributed computing, with notable contributions to consensus protocols, secure data management, and post-Snowden cryptographic designs. Education: PhD from the University of Connecticut under Professors Aggelos Kiayias and Alexander Russell, postdoc at Cornell University. Research Interests: Applied/ theoretical cryptography, blockchain technology, privacy-preserving systems, and distributed consensus mechanisms. His work has appeared in top-tier conferences like CCS, USENIX Security, and CRYPTO, addressing challenges in secure communication, decentralized systems, and cryptographic primitives. Notable Awards: ICDCS Distinguished Paper Award (2024), SOAR Prize (2023), MIT TR35 Innovator (2019), Google Faculty Award (2019). He chairs PKC 2024 and serves on program committees for major conferences like CRYPTO and NDSS. Grants and Collaborations: ARC DP grants, Google-funded projects, collaborations with Algorand Foundation, Protocol Labs, and JD.com. His lab has developed systems like Dumbo BFT consensus and blockchain-based cybersecurity frameworks. Students and Labs: Advises PhD/MS students at USYD and NJIT. His research group focuses on advancing blockchain scalability, privacy, and secure distributed systems.

Zachary KisselView profile

Associate Professor

• Cryptography
• Network Security
• Machine Learning
• +4 more

Zachary Kissel is an Associate Professor in the Computer Science Department at Merrimack College. His research focuses on the intersection of cryptography, complexity theory, and secure computing. He holds a Ph.D. in Computer Science from UMass Lowell, an M.S. from Northeastern University, and a B.S. from Merrimack College. His research interests include federated learning, machine learning with encrypted data, constrained pseudorandom functions, and cryptographically enforced access control. He has co-authored books such as Introduction to Network Security: Theory and Practice (2015) and published extensively in theoretical cryptography and network security domains. Recent work emphasizes privacy-preserving techniques like searchable encryption and policy-based redactable signatures. His publications span topics from verifiable privacy-preserving data structures to fault-tolerant parallel computation. He actively contributes to experiential learning frameworks for computer science education, focusing on practical skill development in technology disciplines. Professional contributions include work on cloud security, untrusted content distribution systems, and verifiable phrase search over encrypted data. His research often bridges theoretical foundations with real-world applications in secure computing environments.