جست‌وجوی استاد و پژوهشگر

Edith Cheuk Han NGAIمشاهده پروفایل

دانشیار

• Internet-of-Things
• Edge Intelligence
• Data Analytics
• +۵ مورد دیگر

Dr. Edith Cheuk Han Ngai is an Associate Professor in the Department of Electrical and Electronic Engineering at the University of Hong Kong (HKU), where she has been since 2020. Previously, she held an Associate Professor position at Uppsala University, Sweden. Her research focuses on Internet-of-Things (IoT), edge intelligence, data analytics, machine learning, network security, smart cities, and health informatics. She is an ACM Senior Member, IEEE Senior Member, and IEEE ComSoc Distinguished Lecturer (2023-2024). Her research contributions include the Green IoT project in Sweden (2014–2017), recognized in IVA’s 100-list (2020). She has led interdisciplinary projects like the Smart Water Auditing initiative, combining IoT and machine learning to address water conservation. Ngai has received awards such as the VINNMER Fellowship (2009) and a Meta Policy Research Award (2022). Her work on energy-aware edge computing and federated learning has been widely cited, ranking her in the top 1% globally by Clarivate Analytics (2021–2023). Ngai serves as an Associate Editor for multiple prestigious journals, including IEEE Transactions on Mobile Computing and IEEE Transactions on Industrial Informatics. She has organized conferences like IEEE GreenCom 2022 and IEEE IWQoS 2024. Her lab, the HKU IoT Lab, explores AI-driven smart systems, edge general intelligence, and healthcare applications. Recent work includes Radio2Text (mmWave-based speech recognition) and HealthPrism (multimodal health analytics). Ngai advises a dynamic research group with postdocs and PhD students focused on federated learning, edge computing, and wearable health sensing. Notable students include Zhihan Jiang (HKU Foundation PhD Award 2024) and Sukanya Jewsakul (BuildSys 2024 Best Paper Candidate). She collaborates with institutions like the HKU Center for Water Technology and Policy on projects like smart water auditing and health informatics.

• Operations Research
• Supply Chain Management
• Artificial Intelligence
• +۶ مورد دیگر

Ajay Kumar is a prominent researcher and academic with extensive contributions across multiple domains including Operations Research, Artificial Intelligence, Blockchain, and Biometric Recognition. His work spans a wide range of topics, from digital transformation in supply chains to machine learning applications in healthcare and software engineering. He has collaborated with numerous scholars and published extensively in high-impact journals and conferences. Research Interests: Operations Research, AI in Healthcare, Blockchain Applications, Biometric Recognition, Software Reliability, Digital Transformation Publications: Kumar has authored numerous publications in journals like Annals of Operations Research , IEEE Transactions on Engineering Management , and SN Computer Science , as well as conferences such as CVPR and IC3I. Collaborations: Kumar has worked with leading experts like Kim Hua Tan, Shivam Gupta, Seema Bawa, and others, contributing to interdisciplinary research in supply chain, data science, and IoT. Key Contributions: His research includes innovative frameworks such as blockchain-enabled supply chains, hybrid AI models for diabetes prediction, and scalable tools for genomic data analysis. Emerging Trends: Kumar’s recent work focuses on explainable AI, fake news detection, and integrating IoT with blockchain for secure and efficient systems across health, logistics, and UAV communication.

Zuoxia Yuمشاهده پروفایل

مدرس

• Privacy-Preserving Cryptography
• Blockchain Technology
• Lattice-Based Cryptography
• +۳ مورد دیگر

Zuoxia Yu is a Lecturer in Cyber Security at the University of Wollongong's School of Computing and Information Technology, where she researches privacy-preserving cryptography, blockchain applications, and post-quantum security. Her work develops advanced cryptographic primitives including accountable anonymous credentials, collusion-resistant watermarking, and lattice-based zero-knowledge proofs. Current research focuses on blocklistable anonymous credentials with post-quantum security and revocable ring signatures from lattice assumptions. She holds an ARC DECRA grant (2024-2026) for 'New Frontiers for Anonymous Authentication' and leads projects on lattice-based zero-knowledge proofs.

Iis Tussyadiahمشاهده پروفایل

استاد

• Artificial Intelligence Applications
• Digital Nudging
• Human-Machine Interaction
• +۷ مورد دیگر

Professor Iis Tussyadiah is a leading academic in intelligent systems and tourism management, serving as Dean of Surrey Business School and Fellow of the Surrey Institute for People-Centred Artificial Intelligence (PAI). She holds a PhD in Information Systems from Tohoku University, M.Eng. from Bandung Institute of Technology, and B.Eng. in Industrial Engineering. Her research focuses on AI applications, digital nudging, and sustainable tourism, influencing global policies on climate change and data privacy. Notable roles include Head of Surrey Hospitality & Tourism Management (2021–2024) and leadership in the PriVELT Project (2018–2022), exploring privacy-aware data management in travel. She has supervised over 10 PhD students, with recent advisees focusing on AI-human teaming, GenAI in tourism marketing, and blockchain applications. Awards include Clarivate’s Highly Cited Researcher in Social Sciences. Active in industry collaboration, her work bridges technology and human-centric solutions for the services sector. Education: PhD in Information Systems – Tohoku University M.Eng. in Industrial Engineering & Management – Bandung Institute of Technology B.Eng. – Not explicitly stated but implied in qualifications Key Projects: PriVELT Project: EPSRC-funded research on privacy in travel data (2018–2022) Leadership in digital tourism labs and innovation groups Research Themes: AI-driven behavioral change Immersive technologies in tourism Blockchain in sharing economy Climate change mitigation strategies Awards: 2024 Award (specific details unspecified) Advising & Grants: Supervised 7+ PhD students with topics ranging from GenAI to blockchain Secured £1.4m EPSRC funding for PriVELT Media Engagement: Featured in BBC Insights, Skift, and Hospitality Net for AI and automation insights

Aniket Kateمشاهده پروفایل

دانشیار

• Cryptocurrencies
• Blockchains
• Multi-Party Computation (MPC)
• +۵ مورد دیگر

Prof. Aniket Kate is an Associate Professor of Computer Science and a University Faculty Scholar at Purdue University. He also serves as Chief Research Officer at Supra, a blockchain technology company. His research focuses on applied cryptography, privacy, and secure distributed systems, with a particular emphasis on blockchain technologies, multi-party computation (MPC), and crypto-economic security. He holds a Ph.D. from the University of Waterloo and a Master's from IIT Bombay. Education: Ph.D. in Computer Science, University of Waterloo, Canada (Advisor: Ian Goldberg) Postdoctoral Fellowship at Max Planck Institute for Software Systems (Germany) M.Tech. in Computer Science, IIT Bombay, India Research Interests: Cryptocurrencies and Blockchain Scalability Privacy-Preserving Technologies (e.g., anonymous communication, metadata privacy) Crypto-Economic Security Mechanisms Multi-Party Computation (MPC) and Threshold Cryptography Secure Distributed Consensus and Ledgers Awards & Honors: NSF CAREER Award (2019) Best Paper Award at COSN 2015 Service & Leadership: Program Committee Member for IEEE S&P, CCS, FC, and others Editorial Board Member at ACM Transactions on Privacy and Security (TOPS) Organizer of Dagstuhl Seminars, 3Rand Workshop, and Decentralized Credit Networks (DCN) Workshop Labs & Teams: Leads the Freedom Lab at Purdue, focusing on decentralized privacy and security systems.

• Data Mining
• Distributed Systems
• Cloud Computing
• +۴ مورد دیگر

Professor Mohand Tahar Kechadi is a Full Professor at the School of Computer Science, University College Dublin (UCD), where he has been since 1999. His research focuses on Data Mining, Distributed Systems, Digital Forensics, and Healthcare Informatics. He has published over 260 articles and serves on editorial boards of journals like Future Generation Computer Systems and IST Transactions . He also holds roles in academic leadership, including directing UCD’s international BSc program in Sri Lanka and previously serving as Head of Teaching and Learning (2007–2012). Education: PhD and DEA (MSc) in Computer Science from the University of Lille, France; HDip in University Teaching & Learning from UCD. Research: Explores challenges in big data processing, including distributed data mining, cloud computing, and privacy-preserving techniques. Recent work addresses applications in healthcare (e.g., wearable devices, medical imaging), agriculture (precision farming), and cybersecurity (blockchain, IoT trust management). Grants: Led a grant on evaluating sugar-sweetened beverage taxes (2018–2019). Collaborates on projects like BigO, a public health decision support system for pediatric obesity. Teaching: Coordinates modules in Cloud Computing, Data Mining, and Distributed Systems. Developed a code-free cloud service for biomedical signal processing and advocates inclusive assessment strategies. Awards: None explicitly stated. Recognized for contributions to interdisciplinary research and education.

• Mobile Computing
• Distributed Systems
• Decentralized Applications
• +۴ مورد دیگر

Dr. Dimitris Chatzopoulos is an Assistant Professor (Ad Astra Fellow) at the School of Computer Science, University College Dublin. He holds a PhD from The Hong Kong University of Science and Technology and academic qualifications in Computer Engineering from the University of Thessaly, Greece. His research focuses on privacy-preserving systems, AI-driven decentralized applications, mobile computing, blockchain technology, and combating fake news. Education: PhD in Computer Science and Engineering, The Hong Kong University of Science and Technology (2013–2018) MSc in Computer Engineering and Communications, University of Thessaly, Greece Professional Diploma in University Teaching & Learning, University College Dublin Research Interests: Mobile and distributed systems Decentralized AI and blockchain applications Privacy-enhancing technologies Extended reality (XR) interfaces Metaverse infrastructure Awards & Recognition: Heidelberg Laureate Forum Participant (2017) Grants & Projects: "AI-enabled decentralized sensing for mobile and distributed systems" (2023–2026) "DIGITISE: Cross-sector services for societal empowerment" (2024–2027) Ad Astra Fellowship (2020–2027) Teaching & Supervision: Module coordinator for courses such as Blockchain & Decentralisation, Cloud Computing, and Python OOP PhD thesis supervisor

Dominik Molitorمشاهده پروفایل

دانشیار

• Digital Retailing
• Causal Inference
• Privacy and IT Security
• +۲ مورد دیگر

Dominik Molitor is an Associate Professor in the Information, Technology, and Operations department at Fordham University's Gabelli School of Business. He holds a PhD from Ludwig-Maximilian University and previously served as a research scientist at NYU Stern. His research integrates econometrics and data science to investigate digital retailing, location-based advertising, privacy/IT security, and advertising effectiveness. Key areas include mobile consumer behavior, geo-targeting, and quantitative UX analysis using large-scale observational data and field experiments. Recent publications focus on mobile ad effectiveness, geo-conquesting strategies, data breach characteristics, and cryptocurrency analytics. His work consistently examines how spatial data and interface design influence consumer decisions in digital environments.

Zakirul Alam Bhuiyanمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy-Preserving Systems
• Trustworthy AI/ML
• +۷ مورد دیگر

Dr. Md Zakirul Alam Bhuiyan is an Associate Professor in the Department of Computer and Information Sciences at Fordham University, New York. He leads the DependSys Lab (Dependable and Secure Systems Lab) and is affiliated with the Fordham Center for Cybersecurity. His research focuses on cybersecurity, data-driven dependability, trustworthy AI/ML, and IoT/CPS applications. He has authored over 250 publications, including top-tier journals and conferences like IEEE Transactions on Industrial Informatics and IEEE INFOCOM. Dr. Bhuiyan has held adjunct roles at Harvard University and Temple University. His work emphasizes securing healthcare monitoring systems, event detection in CPS, and privacy-preserving data collection. Education details are not explicitly stated, but his career trajectory includes prior positions at Temple University and Harvard. He has secured grants and awards, including the IEEE TCSC Award for Excellence, ScholarGPS recognition, and being named one of the world's top 2% scientists. His professional activities include editor roles for IEEE Transactions and ACM journals, and organizing major conferences like IEEE DASC and TrustCom. Research interests span cybersecurity, IoT, and AI/ML, with a focus on real-world applications like structural health monitoring and smart city infrastructure. His lab, DependSys, addresses challenges in dependable and secure systems. He has advised numerous students and collaborates globally, delivering keynote speeches at events like IEEE ISPA and ICECI. Key achievements include 25+ ESI Highly Cited Papers, 7 Best Paper Awards, and leadership in over 50 conferences. Current projects involve federated learning, edge computing, and blockchain for healthcare privacy. His lab explores innovative uses of Wi-Fi signals for sensing and security, including contactless health monitoring and intrusion detection.

Augustine Ikpehaiمشاهده پروفایل

مدرس ارشد

• Smart Grid
• IoT and Intelligent Infrastructure
• Electric Vehicle (EV) Charging Networks
• +۵ مورد دیگر

Dr. Augustine Ikpehai is a Senior Lecturer in the Department of Engineering and Mathematics at Sheffield Hallam University, part of the College of Business, Technology and Engineering. He joined the university in 2019 after completing post-doctoral research at Manchester Metropolitan University. His expertise spans Smart Grids, IoT, and Intelligent Infrastructure, with a focus on EV charging networks, cyber security, and renewable energy integration. Education: PhD in Smart Grid Communication (Manchester Metropolitan University) MSc in Communication Engineering (Lancaster University) Research Interests: His work addresses EV charging infrastructure, smart wireless power transfer, transactive energy systems, and IoT security in critical infrastructure. He has led projects such as the Innovate UK-funded City Verve IoT initiative and contributed to the EU H2020 Triangulum Smart Cities project. Grants & Projects: Overhead Line Warning System (£581,721 – 2023–2025) Optimal Scheduling of EV-Integrated Multi-Energy Systems (£83,986 – 2022) EU H2020 Triangulum Project (€23M – 2014–2019) Awards: MMU Research Knowledge Exchange Award (2016) UK-China Newton Fund Travel Grant (2019) UK-Brazil Newton Fund Travel Grant (2019) Advising & Labs: Supervises multiple PhD students and collaborates with the Centre for Automation and Robotic Research and Hallam Energy. He has advised projects ranging from hybrid encryption frameworks to hydrogen supply chain dynamics.

Weili Lily Wuمشاهده پروفایل

استاد

• Social Network Analysis
• Big Data
• Blockchain
• +۵ مورد دیگر

Weili Lily Wu is a Professor of Computer Science at the University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science . She holds a Ph.D. and M.S. in Computer Science & Engineering from the University of Minnesota (2002 and 1997, respectively). Her research focuses on social network analysis, big data, machine learning, and distributed database systems. She is an IEEE Fellow and recipient of the UCGIS Summer Assembly Student Travel Award (2000). Research interests include blockchain technologies, spatio-temporal data mining, wireless sensor networks, and algorithmic optimization for large-scale systems. Her work bridges theoretical computer science with practical applications in data-driven decision-making and network security. Publications span interdisciplinary domains such as computational biology, distributed systems, and database architectures. Recent trends highlight advancements in scalable machine learning frameworks and secure blockchain implementations. Professional Background : Postdoctoral roles at the University of Minnesota (1996–2002) included Research Assistant and Teaching Assistant. Current roles include leadership in UTD's data science initiatives and academic advising.

Robert H Dengمشاهده پروفایل

استاد

• Applied cryptography
• Data security and privacy
• Mobile and wireless security
• +۵ مورد دیگر

Professor Robert H. Deng is a distinguished academic and researcher at Singapore Management University's School of Computing and Information Systems, where he serves as Professor of Computer Science and Deputy Dean for Faculty & Research. With a PhD from Illinois Institute of Technology (1985), he has established himself as a leading authority in cybersecurity, data privacy, and applied cryptography. His research interests span applied cryptography, data security and privacy, mobile and wireless network security, trusted computing, and system security. Professor Deng has published extensively in top-tier security venues, with over 600 publications listed in DBLP. His work bridges theoretical foundations with practical applications, particularly in the domains of IoT security, blockchain systems, and privacy-preserving technologies. Professor Deng has received numerous prestigious awards, including the National Day Award (Public Administration Medal Silver) in 2020, the AXA Chair Professor of Cybersecurity (2017-2025), and the Lee Kuan Yew Fellow for Research Excellence at SMU in 2006. His recent publications demonstrate continued leadership in emerging areas like post-quantum cryptography, federated learning security, and hardware-assisted security systems. His research group has produced significant work on secure authentication protocols, privacy-preserving data analytics, and robust cryptographic systems for real-world applications. National Day Award, Public Administration Medal (Silver), 2020 AXA Chair Professor of Cybersecurity, AXA Research Fund, 2017-2025 Distinguished & Best Paper Awards at NDSS, ESORICS, IEEE ICPADS, etc. Asia-Pacific Information Security Leadership Achievements (ISLA), 2010 Lee Kuan Yew Fellow for Research Excellence, SMU, 2006 University Outstanding Researcher, National University of Singapore, 1999 As a research advisor, Professor Deng has mentored numerous students including SUN Bing. His active participation in the research community is evidenced by recent keynotes at major conferences including DSPP 2024 on post-quantum cryptography and ASIACCS 2024 on client-side encryption. His research group maintains strong industry connections and receives significant funding for cutting-edge security research.

• Cloud Computing
• Machine Learning
• Artificial Intelligence
• +۷ مورد دیگر

Dr. Prasad Calyam is the Greg L. Gilliom Professor of Cybersecurity in the Department of Electrical Engineering and Computer Science at the University of Missouri-Columbia. He also serves as Director of the Center for Cyber Education, Research, and Infrastructure (Mizzou CERI). His research focuses on Cloud Computing, Machine Learning, Artificial Intelligence, Cyber Security, and Advanced Cyberinfrastructure. He has led over $39 million in sponsored projects from NSF, DOE, NSA, and industry partners. Dr. Calyam's work emphasizes interdisciplinary collaboration, particularly in cybersecurity education for neurodivergent populations, drone networking, and blockchain-based systems. He has developed tools like 'Narada Metrics' for network monitoring and contributes to platforms like FlyNet for drone applications. His publications span AI-driven cybersecurity solutions, VR-based learning environments, and edge computing optimization. He holds IEEE Senior Member status and serves as an Associate Editor for IEEE Transactions on Network and Service Management. His recent projects address tactical edge network security, federated learning for drone swarms, and AI-driven anomaly detection. He actively fosters inclusive cybersecurity education through VR curricula and collaborates on medical data governance frameworks.

Olamide Jogunolaمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Blockchain Technology
• Peer-to-Peer Energy Trading
• +۲ مورد دیگر

Dr. Olamide Jogunola is a Senior Lecturer in Cyber Security in the Department of Computing and Mathematics at Manchester Metropolitan University. She holds a B.Eng. in Electrical Engineering from University of Ilorin, M.Sc. in Networking and Data Communication from Kingston University, and Ph.D. in Electrical Engineering from Manchester Metropolitan University. Her research focuses on cybersecurity for distributed critical infrastructures like smart grids. Research Focus: Investigates blockchain and AI applications for privacy and uncertainty modeling in distributed systems. Current projects examine secure smart contracts, federated learning for intrusion detection, and cyber resilience in IoT-enabled infrastructures. Grant Leadership: Principal Investigator for multiple projects including the £228K 'AI-enabled smart EV charging infrastructure' (Innovate UK/KTP) and £5K EPSRC/SuperGen Network project. Secured over £500K in research funding across 8 projects including EU Horizon 2020 and DFID initiatives. Teaching: Leads undergraduate and postgraduate units in Networks, Computer Networks and Security, and HPC & Big Data. Supervises PhD research on blockchain applications, AI security, and peer-to-peer energy trading.

Tianyi Liمشاهده پروفایل

استادیار

• Digital Twin
• Graph Neural Networks
• Energy Engineering
• +۸ مورد دیگر

Tianyi Li is a Tenure Track Assistant Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design and the Daisy - Center for Data-intensive Systems. His research focuses on data engineering, spatiotemporal systems, and digital twins, with applications in energy, transportation, and vehicular networks. Key areas include trajectory data management, graph neural networks, compression techniques, and federated learning. He has contributed to over 37 publications, including works on digital twin frameworks for autonomous driving and smart grids, trajectory prediction systems, and efficient time series compression. His research integrates machine learning, distributed systems, and cybersecurity to address challenges in data-intensive environments. Key Projects: Digital twin-enabled voltage control, federated vehicular networks, trajectory simplification frameworks. Labs: Involved with the Daisy Center, focusing on data-centric systems and scalable solutions. Technical Expertise: Blockchain systems, energy systems optimization, and real-time data processing.