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Zhiyong LiView profile

Professor

• Biomechanics
• Mechanobiology
• Hemodynamics
• +7 more

Professor Zhiyong Li is a Professor in Biomedical Engineering at Queensland University of Technology (QUT), affiliated with the School of Mechanical, Medical and Process Engineering. He holds a PhD from Queen Mary University of London and a MA from the University of Cambridge, where he was a research fellow and later an elected Fellow of Wolfson College. His research focuses on biomechanics, mechanobiology, and cardiovascular diseases, particularly atherosclerosis and aneurysm. He has pioneered novel imaging and computational methods for assessing high-risk plaques, with over 100 publications in top journals such as Circulation and Nature Communications . Awards include the 2014 ARC Future Fellowship and the 2015 Australia Vascular Biology Society Award. Education: BEng in Civil Engineering (1998), Tongji University PhD in Biomedical Engineering (2004), Queen Mary University of London MA (2009) from University of Cambridge Research Interests: Mechanical and hemodynamic factors in atherosclerosis progression Development of MRI/IVUS/OCT-based plaque assessment tools Biomaterial scaffold design for bone regeneration Left atrial appendage thrombosis mechanisms in atrial fibrillation Computational modeling of vascular mechanics Articles Trends: His recent work (2024-2025) emphasizes advanced computational models for cardiovascular systems, novel biomaterials for tissue engineering, and innovative encryption algorithms for medical data security. Key themes include patient-specific biomechanical analysis, thrombus formation mechanisms, and scaffold design for bone regeneration. Scientific Awards: ARC Future Fellowship (2014) 2015 Australia Vascular Biology Society Achievement Award Advising & Grants: Currently supervising multiple PhD candidates funded by ARC and CSC scholarships, focusing on projects like plaque vulnerability assessment and scaffold design. Active in securing competitive grants for translational biomedical engineering research. Labs/Teams: Leads a multidisciplinary team in QUT's Centre for Data Science and collaborates with clinical partners on translational cardiovascular research initiatives.

Miguel PardalView profile

Assistant Professor

• Cybersecurity
• Internet of Things (IoT)
• Cloud Technologies
• +5 more

Miguel Pardal is an Assistant Professor at the Instituto Superior Técnico, Universidade de Lisboa, where he has been teaching since 2002. His research focuses on Cybersecurity, IoT, and Cloud Technologies, with recent projects exploring Blockchain technologies (launched in 2023) and intrusion recovery systems. He is also affiliated with INESC-ID, a leading research institution in Lisbon. Education: Licenciatura em Engenharia Informática, Instituto Superior Técnico (2000) Mestrado em Engenharia Informática, Instituto Superior Técnico (2006) Research Interests: Cybersecurity, IoT Security, Cloud Infrastructure, Intrusion Detection and Recovery, Blockchain Applications, and Secure Communication Protocols. His work emphasizes practical solutions for critical systems, including industrial process specifications and decentralized identity management. Recent Articles: Focus on intrusion recovery mechanisms, decentralized systems, and secure communication protocols. Key themes include vulnerability-tolerant TLS, fault-tolerant microservices, and AI-driven algorithm synthesis. Awards: None explicitly listed, though his extensive publication record reflects recognition in cybersecurity and IoT fields. Advising & Grants: Active in guiding students through workshops on LaTeX and research methodologies. Collaborates on EU-funded projects like SafeWalk and CrossCity location proofs. INESC-ID provides infrastructure for his lab-based research. Labs/Teams: Part of INESC-ID's Cybersecurity group, contributing to projects like SPATIO and MACHETE.

Savvas ZannettouView profile

Assistant Professor

• Machine Learning
• Data-Driven Analysis
• Social Media
• +12 more

Savvas Zannettou is an Assistant Professor at the Faculty of Technology, Policy, and Management (TPM) at Delft University of Technology (TU Delft). He is also an Associated Researcher at the Max Planck Institute for Informatics (MPI-INF) and a core member of the iDrama Lab. His research is centered on applying machine learning and data-driven analysis to understand online phenomena such as misinformation, hate speech, and algorithmic recommendations on social media platforms. His research interests lie at the intersection of computer science, social media, and policy. Key areas include online disinformation, hate speech detection, algorithmic transparency, toxic content in AI-generated media, and platform moderation. He employs large-scale data analysis to study user behavior on platforms like TikTok, Twitter, Reddit, and WhatsApp, with a strong focus on ethical and societal implications. His recent publications reveal a strong trend in auditing social media algorithms, analyzing AI-generated harmful content (e.g., hateful memes), and leveraging data donation frameworks to study user exposure. His work frequently appears in top-tier venues like WWW, IEEE S&P, USENIX Security, and ICWSM. He has led research on topics including QAnon, incel communities, state-sponsored trolls, and the impact of moderation policies. He has received several scientific honors, including: Distinguished Paper Award, ACM IMC 2018 Best Paper Honorable Mention, ICWSM 2020, 2024 Best Paper Honorable Mention, CSCW 2021 Best Paper Honorable Mention, ACM CCS 2022 Best Senior Program Committee Member, AAAI ICWSM 2022, 2023 Savvas Zannettou actively mentors students, with several PhD and Master’s advisees leading publications in top conferences. He has been involved in significant grant-funded research, including a €1.3M NWO project on trusted flaggers under the Digital Services Act (DSA), and has secured funding from Google’s Academic Research Award Program. He serves on the program committees of major conferences such as ICML, NeurIPS, USENIX Security, and The Web Conference. He is a core member of the iDrama Lab, which focuses on data-driven research for advanced modeling and analysis, particularly in the context of online safety and platform governance.

Boris ŠkorićView profile

Associate Professor

• Quantum Cryptography
• Information Security
• Digital Forensics
• +3 more

Boris Škorić is an Associate Professor in the Security of Embedded Systems (SEC) group at the Department of Mathematics and Computer Science, Technische Universiteit Eindhoven. His research focuses on quantum cryptography, security with noisy data, and collusion-resistant watermarking. He is affiliated with the CREST project and has contributed to advancements in quantum-secure authentication and quantum key distribution protocols. Education : Ph.D. in Physics (Quantum Hall Effect), M.Sc. in Physics His research interests span three core areas: (1) Security with noisy data, addressing challenges in cryptographic primitives using physical measurements; (2) Quantum physics for security, including quantum readout of Physical Unclonable Functions (PUFs) and quantum key recycling; and (3) Collusion-resistant watermarking codes for digital content protection. He has pioneered techniques such as quantum-secure authentication via laser speckle and error correction methods for secure key storage. His publications reflect a strong emphasis on quantum security, including developments in continuous-variable quantum key distribution, entropically secure encryption, and quantum position verification. Recent work explores applications in healthcare data protection and secure communication over turbulent optical channels. Grants & Labs : Active in the CREST project (Collusion-Resistant Embedding and Secure Tracing) and collaborates with industry on quantum-secure technologies. Leads research in the SEC group, mentoring projects on cryptographic protocols and embedded system security.

• Cyber Security
• Big Data Analytics
• Software Engineering
• +2 more

Dr. Faheem Ullah is an Assistant Professor in the School of Computer and Mathematical Sciences at the University of Adelaide. He holds a dual role as Lecturer/Assistant Professor and is part of the Centre for Research on Engineering Software Technologies (CREST), where he leads R&D in big data analytics and cloud computing. His research focuses on cybersecurity, big data analytics, software engineering, cloud computing, and machine learning. He has applied these skills in healthcare, oil & gas, defense, and green computing domains. Dr. Ullah is eligible to supervise Masters and PhD students as a co-supervisor, emphasizing collaborative research endeavors. He actively contributes to the design and evaluation of cybersecurity systems, including frameworks for microservices, distributed data processing, and adaptive security analytics. His work bridges theoretical advancements with industry applications, addressing challenges such as vulnerability analysis in microservices, AI-driven threat detection, and optimizing cloud infrastructure. He is a sought-after expert in cybersecurity and cloud-native technologies, with a strong publication record in top-tier venues.

Kan YuView profile

Tutor

• Microbiome
• Bacterial Interactions
• Respiratory Tract Microbiology
• +3 more

Kan Yu is a PhD candidate in the School of Biomedical Sciences at The University of Western Australia (UWA) and concurrently serves as a sessional academic tutor at Edith Cowan University's School of Science. His primary research focuses on bacterial interactions in the human upper respiratory tract during infancy, with a particular emphasis on the microbiome's role in health and disease. He holds a Master's degree in Computational Biology (2021) from Edith Cowan University and has been supported by prestigious awards such as the Australian Research Training Program Scholarship and University Postgraduate Awards. His academic and research contributions span microbiology, bioinformatics, and infectious diseases. Notably, he has explored Mycobacterium tuberculosis molecular clocks, tuberculosis drug resistance prediction tools, and bacterial interactions in the nasopharynx. His work bridges clinical and computational approaches, addressing global health challenges like antimicrobial resistance and food allergy development. Education : Master of Science by Research (Computational Biology), Edith Cowan University, 2021 Doctor of Philosophy (Biomedical Sciences), University of Western Australia, ongoing Yu has received several accolades, including the Shellam Fund for Research in Microbiology (2024) and the ASM WA Branch Student Travel Award (2025). His mentorship includes guiding UWA postgraduate students through the UniMentor Program. He actively participates in academic networks, such as the Australian Society for Microbiology, and has contributed to initiatives like the Future Leader Experience Program. His research aligns with UN Sustainable Development Goals, particularly in advancing health equity and innovation. Collaborations include studies on aquaculture microbiology and pediatric cardiology biomarkers, showcasing interdisciplinary reach.

• Cybersecurity
• Privacy-Preserving Machine Learning
• Secure Multi-Party Computation
• +3 more

Xiaoning (Maggie) Liu is a Lecturer (equivalent to US Assistant Professor) at the School of Computing Technologies, RMIT University, where she earned her Ph.D. in Computer Science. Her research focuses on secure systems to address data privacy and security challenges in machine learning, particularly through secure multi-party computation (MPC) and privacy-preserving machine learning (PPML). She applies these techniques to practical domains like medical diagnostics and mobile image classification. Her design philosophy emphasizes lightweight, fundamental protocols leveraging advanced cryptographic methods, such as function secret sharing and zero-knowledge proofs. Research Interests: Secure multi-party computation and its applications in PPML Privacy-preserving medical diagnostics (e.g., MediSC , CryptMed , OblivGNN ) Secure cloud and edge computing systems ( Sonic , EncSIM , Leia ) Cross-domain encryption and collaborative computation Advising & Supervision: Xiaoning supervises Masters and PhD students in research projects such as intrusion detection systems for healthcare IoT devices, defenses against backdoor attacks in neural networks, and privacy-preserving fairness verification. She emphasizes recruiting self-motivated researchers passionate about impactful security work. Interdisciplinary Contributions: Her work bridges computer systems, cryptography, and machine learning to address real-world challenges in areas like MLaaS, medical data collaboration, and mobile-edge inference. Collaborative frameworks like MediSC and Leia

• Coding Theory
• Discrete Mathematics
• Blockchains
• +5 more

Dr. Son Hoang Dau is a Senior Lecturer in Computer Science at the School of Computing Technologies, RMIT University, Australia. His research focuses on coding theory, discrete mathematics, blockchains, and their applications in secure distributed systems and quantum computing. He actively supervises PhD and Master’s students in areas like fraud detection on blockchain networks and quantum annealing for satellite communication optimization. Research Interests: - Coding Theory & Error-Correcting Codes - Blockchain Security & Decentralized Systems - Quantum Computing & Optimization - Privacy-Preserving Algorithms - Distributed Storage Systems Dr. Dau's recent work includes groundbreaking studies on blockchain fraud detection, secure erasure coding in distributed storage, and quantum annealing for satellite beam placement. His contributions bridge theoretical computer science with practical applications in cybersecurity and telecommunications. Supervision Projects: - Machine Learning methods for Fraud Detection on Blockchain networks - Efficient Repair of Reed-Solomon Codes - Robust Computer vision for surveillance and threat detection Collaboration Network: Engages with global researchers in cryptography, distributed systems, and quantum computing through publications in top venues like IEEE Transactions and ACM Conferences.

Yonghao WangView profile

Associate Professor

• Networking
• Cybersecurity
• Blockchain Technology
• +3 more

Dr. Yonghao (Leo) Wang is an Associate Professor at Birmingham City University's Department of Computer Science and Creative Technologies. His research focuses on Networking, Cybersecurity, Blockchain Technology, Digital Signal Processing (DSP), and Cloud/Edge Computing. He actively contributes to international standards bodies like ETSI and AES, and has authored over 60 peer-reviewed publications. His work emphasizes ethical technology integration, particularly in blockchain for inclusive finance and AI, as well as low-latency networking for beyond-5G systems. Research interests include blockchain security, multimedia steganography, AI-driven network optimization, and time-deterministic systems. Dr. Wang also explores how advanced information systems can enhance knowledge acquisition across domains. His recent articles span topics from smart contract security to video steganography in HEVC, reflecting his interdisciplinary approach to technology and societal impact. He serves as a journal reviewer, guest editor, and conference chair, fostering academic collaboration. No specific scientific awards are listed, but his extensive publication record and committee roles highlight his impactful contributions to the field.

Manoranjan PaulView profile

Professor

• Artificial Intelligence
• Video/Image Processing
• Machine Vision
• +8 more

Manoranjan Paul is a Full Professor in Computer Science at the School of Computing, Mathematics, and Engineering, Charles Sturt University (CSU), Australia. He is Director of the Computer Vision Lab and Head of the Machine Vision & Digital Health (MAVIDH) Research Group. Paul holds a PhD from Monash University (2005) and has held academic and research roles at institutions including UNSW, Nanyang Technological University (Singapore), and Ahsanullah University of Science and Technology. His research spans Artificial Intelligence , Video/Image Processing , Quantum Computing , Digital Health , and Medical Imaging . Notable contributions include $10M+ in grants (e.g., ARC Discovery Projects, Japanese grants), 250+ refereed publications, and commercialized apps like VineSignal for vine disease detection and Hunter Gatherer Networks for Indigenous marketplaces. Awards include the Golden Disruptor Award and ICT Researcher of the Year 2017 (ACS), and recognition as a World's Top 2% Scientist (Elsevier/Stanford, 2021). Key research initiatives: EEG-based epilepsy prediction ( 90% accuracy ) Quantum image compression ( novel circuits ) Hyperspectral soil analysis ( regression models ) Non-contact cardiopulmonary detection ( smartphone-based ) Supervised 19 PhD students and led international conferences (e.g., PSIVT-19, DICTA-2023). Editor for IEEE Transactions on Image Processing and Multimedia, and Steering Committee Chair for PSIVT.

Ibraheem Al-DhamariView profile

Researcher

• Trustworthy AI
• Deep Learning
• Computer Vision
• +3 more

Ibraheem Al-Dhamari is a postdoctoral researcher in the Software Engineering Institute at the University of Koblenz, Germany. He holds a PhD in Computer Science supported by DAAD scholarships, alongside MSc and research grants from DAAD. His primary research focuses on Trustworthy AI, Deep Learning, Medical Image Analysis, and Cellular Automata, with applications in healthcare imaging and data protection. He has contributed to projects like medical image registration algorithms and cochlear implant analysis. Al-Dhamari's academic journey includes postdoctoral work at the Institute of Software Engineering (Department 4), and he previously belonged to the Arbeitsgruppe Paulus (Active Vision Group). His work bridges computer science and medicine, emphasizing practical tools for clinical imaging challenges. He actively mentors students seeking thesis opportunities in AI and medical imaging through DAAD-funded programs. His achievements include developing ultra-fast algorithms for medical image analysis and pioneering multi-modal imaging fusion techniques. He maintains an active GitHub profile showcasing repositories like medical-image-registration-course and tutorials on deep learning and recursion. Al-Dhamari is affiliated with organizations such as the International Data Spaces Association and contributes to open-source software for medical research. Key awards include DAAD scholarships for MSc (2007), short research (2008), and PhD (2012). His research has led to innovations in cochlear duct measurement, cervical spine analysis, and cellular automata-based data mining. He remains a sought-after collaborator in interdisciplinary projects at the intersection of AI and healthcare.

Heming CuiView profile

Associate Professor

• Distributed Systems
• Operating Systems
• Cloud Computing
• +7 more

Dr. Heming Cui is an Associate Professor at the Department of Computer Science, University of Hong Kong, affiliated with the School of Computing and Data Science. He joined HKU in 2015 after completing his PhD at Columbia University, following bachelor's and master's degrees from Tsinghua University. His research focuses on distributed systems, operating systems, and high-performance computing, with a strong emphasis on reliability and security. Dr. Cui leads projects in distributed AI training systems, blockchain frameworks, and secure execution environments, collaborating closely with industries like Huawei. He has received notable awards including the Croucher Innovation Award (2016), HK$5 million RGC Research Impact Fund (2023), and best paper awards at ICSE and ACSAC. His work has led to commercialized systems such as Huawei's MindSpore integration of Fold3D and TICS' UTEE component derived from his secure systems research. Dr. Cui actively recruits PhD students specializing in systems security and database systems, prioritizing candidates with strong systems-building backgrounds. Key grants include leadership in projects totaling HK$30 million, including flagship collaborations with Huawei and RGC grants targeting transaction/analytical processing in edge computing and cloud security. His research spans over 50 publications in top venues like SOSP, NSDI, and IEEE journals, emphasizing reproducibility and industrial impact.

• Cryptography
• Blockchain Technology
• 5G Network Security
• +7 more

Professor Danilo Gligoroski is affiliated with the Norwegian University of Science and Technology (NTNU) under the Department of Information Security and Communication Technology. His work bridges cryptography, blockchain technology, and 5G network security, with a focus on decentralized systems and privacy-preserving protocols. Key research trends in his recent publications include blockchain applications in healthcare and reseller markets, verifiable delay functions for consensus mechanisms, and cryptographic frameworks for chat-based systems. He explores data integrity, network coding, and scalable storage solutions for blockchain ecosystems. Major collaborations include co-authors like Mayank Raikwar, Katina Kralevska, and Anton Karl Oskar Hasselgren. His work often intersects with GDPR compliance, network slice isolation, and secure service implementation in modern telecommunications.

• Control Theory
• Nonlinear Systems
• Complex Networks
• +7 more

Jinsheng Sun is a prolific researcher with active contributions to Control Theory , Complex Networks , and Image Processing , often collaborating with scholars from institutions like the University of Melbourne and Harbin Institute of Technology . His work spans theoretical advancements and applied methodologies. Key Affiliations : Co-authored papers with researchers from diverse domains, indicating interdisciplinary collaborations. Research Themes : Focus on control systems for nonlinear dynamics, synchronization in complex networks, and forensic analysis of digital media. Research Interests revolve around: Designing adaptive control mechanisms for nonlinear systems and vibration systems , as seen in his 2025 work on transient performance design. Advancing complex network analysis through novel algorithms for identifying vital spreaders and secure synchronization protocols. Developing digital forensics techniques for JPEG compression and watermarking, with applications in information security . Recent Article Trends highlight his focus on control theory (e.g., neural network-based tracking control, H∞ fault detection) and network science (e.g., pinning synchronization, spreader identification). His 2024 work also includes robotics (object-driven navigation) and point cloud segmentation via interactive frameworks. Advising and Grants are not explicitly mentioned, but his extensive co-authorship network suggests mentorship roles. Funding details remain absent in the provided data. Labs and Teams : Collaborated with teams working on TCP/AQM systems , image encryption , and metabolic network reconstruction (e.g., 2018 work on Eriocheir sinensis).

Anys BachaView profile

Associate Professor

• Cybersecurity
• Computer Systems
• Mobile and Cloud Computing
• +5 more

Anys Bacha is an Associate Professor at the University of Michigan-Dearborn and leads the Security and Systems Lab . He has over 13 years of R&D experience at Hewlett-Packard and holds a Ph.D. from The Ohio State University. His work focuses on secure and energy-efficient computer systems, bridging mobile/cloud computing with security research. Education : Ph.D. in Computer Science from The Ohio State University (2016) Expertise : Systems security, hardware-software co-design, machine learning for security, side-channel attacks, non-volatile memory His research explores: Novel malware defenses (ransomware, cryptojacking) Side-channel attack mitigation in speculative execution Machine learning acceleration using emerging memory technologies Security implications of non-volatile caches Peer-reviewed publications appear in top venues like IEEE TDSC, DSN, RAID, and MICRO. Notable trends include: Integration of deep learning and hardware security Systematic approaches to firmware trust Energy-conscious security mechanisms Scientific recognition includes: NSF grants totaling $1.4M+ IEEE Micro Top Picks Honorable Mentions Best Paper Award at CAL 2019 12 issued/pending patents Professional service includes committee roles at ISCA, IPDPS, and MICRO symposia, alongside memberships in IEEE and ACM.