Find Academic Supervisors

• Machine Learning
• Data Science
• Supply Chain Management
• +3 more

Divyansh Agrawal is a Researcher and Teaching Assistant at the University College London (UCL) School of Management. He supports courses in Programming for Business Analytics, Marketing Analytics, Predictive Analytics, and Data Engineering under faculty members like Dr. Wei Miao and Dr. Alastair P. Moore. Additionally, he serves as a Research Assistant to Dr. Wei Miao and Dr. Rafael P. Greminger. Divyansh holds an MSc in Business Analytics from UCL SoM (2024) and previously specialized in Computer Science with a focus on Machine Learning and Data Sciences. Before academia, he worked as a data and strategy consultant at PwC and contributed to analytics capabilities at a supply chain consulting firm. His research interests span Machine Learning, Data Science, Blockchain Technology, and Supply Chain Management. Recent publications explore applications in cloud security using DNA computing, blockchain for drug recall systems, and healthcare predictive analytics. His work bridges technical innovation with practical business challenges. No scientific awards or grants are explicitly listed in the provided information. His current roles emphasize teaching assistance and collaborative research within UCL's academic ecosystem.

Zhou HaiView profile

Professor

• Logical Methods for Computer Systems (LogiCS)
• Algorithms
• Formal Methods
• +4 more

Hai Zhou is a Professor of Electrical and Computer Engineering at Northwestern University, with a courtesy appointment in Computer Science. He directs the NuLogiCS Research Group, focusing on Logical Methods for Computer Systems (LogiCS), integrating logic into hardware/software protocols and their verification for security, efficiency, and correctness. His work bridges formal methods, algorithms, and optimization with applications in security, machine learning, and economics. Education: PhD in Computer Science from the University of Texas at Austin, ME and BE in Computer Science and Technology from Tsinghua University, Beijing, China. Research Interests Zhou’s research emphasizes formal methods for constructing and verifying reactive systems. Key areas include logic encryption, hardware security, VLSI design automation, and AI-driven optimization. He explores how graph signal processing and machine learning can accelerate chip placement and floorplanning. Recent work addresses vulnerabilities in cellular networks and develops obfuscated locking frameworks like ObfusLock for circuit IP protection. Grants & Advising While specific grants are not listed, his publications suggest sustained funding in hardware security and VLSI. No listed advisees indicate possible omission in provided data. Labs & Teams Leads the NuLogiCS Research Group, collaborating on projects spanning formal verification, cryptographic hardware, and interdisciplinary applications in economics and machine learning.

Hoang DinhView profile

Associate Professor

• Wireless Communications
• Networking Systems
• Machine Learning Applications
• +5 more

Associate Professor Hoang Dinh is a faculty member at the School of Electrical and Data Engineering, University of Technology Sydney (UTS), Australia. He holds an ARC DECRA Fellowship and leads research in wireless communications, machine learning applications, and cybersecurity. His work includes over 200 publications, 20,000+ citations (h-index 53), and significant industry collaborations with Cisco and Apple Inc. He teaches IoT Security and Cyber Security for Mobile Platforms, achieving high student satisfaction scores. Key awards include the IEEE TCI Rising Star Award (2023), IEEE TCSC Excellence Award (2021), and multiple editorial recognitions from IEEE Transactions. His research focuses on 6G networks, metaverse technologies, federated learning, and blockchain security. Current projects involve secure edge computing, AI-driven communication systems, and digital twin integration. Education: PhD in Computer Science from Nanyang Technological University (2016). Research Funding: AUD 6M+ in external grants, including DECRA (2021). Editorial Roles: Editor for IEEE Transactions on Communications, Network Science and Engineering, Mobile Computing, and Wireless Communications. Industry Impact: Developed IoT security frameworks and contributed to disaster management digital transformation projects recognized in iAWARDS2024.

Michael Anthony C. DizonView profile

Senior Lecturer

• Law and Information Technology
• Cybersecurity
• Cybercrime Law
• +3 more

Michael Anthony C. Dizon, PhD, is a Senior Lecturer and Co-Director of Research and Innovation at Curtin Law School, Curtin University. He holds academic roles in multiple countries, including New Zealand, the Netherlands, the UK, and the Philippines. His research focuses on law and information communication technology (ICT), cybersecurity, and the socio-legal study of technology. Dizon earned degrees from Ateneo de Manila (BA), University of the Philippines (LLB), Edinburgh (LLM with Distinction), and Tilburg (PhD). His research interests include encryption policy, cybercrime laws, and the norms/values shaping technology regulation. Notable projects include studies on AI cloning regulation (2024–present), cybersecurity and human rights (2023–present), and governance of remote court hearings in the Philippines (2022–2023). He contributed to the Jean Monnet Network on European Cyber Diplomacy (2020–2024) and led Technology in Legal Education for New Zealand (2019–2021). Recent publications (2021–2024) address encryption law frameworks, socio-legal norms in technology, and trust’s role in encryption policy. His work bridges legal theory, technology ethics, and regulatory practice, emphasizing interdisciplinary approaches to emerging digital challenges. Professional affiliations include roles as a tech/AV enthusiast (macdizon), with an active online presence (website, LinkedIn). He teaches law and technology courses, integrating practical and theoretical dimensions of digital-age legal challenges.

Atefeh MashatanView profile

Associate Professor

• Cybersecurity
• Blockchain Technology
• Quantum-Resistant Solutions
• +6 more

Dr. Atefeh Mashatan is an Associate Professor and Canada Research Chair (Tier II) in Quality of Security (QoS) Framework for IoT at Toronto Metropolitan University (TMU). As the founding director of the Cybersecurity Research Lab (CRL), her research focuses on IoT security, quantum-resistant solutions, and blockchain technology. She holds a PhD in Mathematics from the University of Waterloo and is certified in CISSP and SOA. Her work bridges academia, industry, and policy, addressing cybersecurity challenges in emerging technologies. Education: PhD in Mathematics, University of Waterloo MMath, University of Waterloo BMath, Carleton University Certificate in University Teaching, University of Waterloo Research Interests: Dr. Mashatan’s research includes IoT security, cryptography, post-quantum cryptography, blockchain, and privacy-preserving technologies. Her CRC program targets enhancing security quality in IoT devices under contextual constraints. Articles Trends: Her publications span cybersecurity frameworks, quantum threats, blockchain applications, and privacy solutions. Recent work addresses IoT encryption, zero-trust models, and quantum-resistant protocols. Subfields include supply chain finance, medical IoT security, and adversarial quantum communication. Awards: Top 25 Women of Influence (2024) Canada Research Chair (2021) SC Magazine’s Top 5 Women of Influence (2019) Grants & Teams: She leads over $98M in grants, including the Canada First Research Excellence Fund and SSHRC Partnership. Collaborates with Compute Ontario, Rogers Cybersecure Catalyst, and Mastercard’s ELCI initiative. Supervises research in labs like CRL and contributes to the National Quantum Advisory Council. Labs/Teams: Heads the Cybersecurity Research Lab (CRL) and participates in initiatives like the Human Centered Cybersecurity Partnership (HC²P) and Quantum-Resistant Threat Analysis.

• Wireless Communication Systems
• Signal Processing
• Network Security
• +3 more

Mustafa Matalgah is a Professor of Electrical and Computer Engineering at the University of Mississippi. He holds a B.S. from Yarmouk University (1987), an M.S. from Jordan University of Science and Technology (1990), and a Ph.D. from the University of Missouri-Columbia (1996). His research focuses on wireless communication systems, signal processing, and network security with a particular emphasis on UAV networks, fading channel analysis, and cooperative diversity techniques. Professor Matalgah has published extensively in top-tier journals and conferences, contributing to advancements in aviation communication systems, encryption algorithms for IoT, and relay-based cooperative networks. His work spans theoretical analysis of channel models, practical implementations of communication protocols, and real-time data transmission systems. Education: B.S. Electrical Engineering, Yarmouk University (1987) M.S. Electrical Engineering, Jordan University of Science and Technology (1990) Ph.D. Electrical Engineering, University of Missouri-Columbia (1996) Research Interests: Professor Matalgah’s research explores cutting-edge topics in wireless communication, including UAV networks, machine learning for drone activity classification, and robust encryption methods for IoT devices. He investigates the impact of fading channels on signal performance and develops protocols to enhance reliability in cooperative relay systems. His work often bridges theoretical models (e.g., outage probability analysis) with practical implementations (e.g., real-time flight data recorders). Advancing Communication Technologies: His articles highlight contributions to aviation safety through ground-based aircraft recorders, satellite data transfer optimization, and VHF digital link design. He also addresses challenges in mobile networks, such as enhancing throughput in V2X (vehicle-to-everything) systems and improving error performance in cryptographic transmissions over noisy channels.

Bhavani ThuraisinghamView profile

Professor

• Cyber Security
• Data Security
• Privacy
• +5 more

Bhavani Thuraisingham is the Louis A. Beecherl Jr. Distinguished Professor of Computer Science and Executive Director of the Cyber Security Research and Education Institute at The University of Texas at Dallas. She holds a Doctor of Engineering (D.Eng.) from the University of Bristol (2011), a Ph.D. in Mathematics (Theory of Computation) from Swansea University (1979), and earlier degrees in Mathematics and Physics from the University of Ceylon (1975). Her research focuses on cyber security, data security, privacy, and the integration of AI with security. Specific interests include assured information sharing, secure geospatial data management, surveillance/biometrics, and data mining for counter-terrorism. She pioneered work on secure database systems, the inference problem in databases, and cloud data management security. Notable achievements include over 130 journal articles, 300+ conference papers, 7 patents, and prestigious awards from IEEE, AAAS, ACM, and others. She founded UT Dallas’ Cyber Security Institute, which has secured $65M+ in research funding. Her leadership roles include NSF program director (2001–2004) and MITRE Corporation researcher. Awards include IEEE Fellow (2003), AAAS Fellow (2003), and recognition as a top innovator by Silicon India (2002). Current initiatives emphasize trustworthy AI, blockchain security, and policy frameworks for emerging technologies.

• Visible Light Communication
• Optical Camera Communication
• GaN Schottky Diodes
• +3 more

Xicong Li is a Lecturer in Northumbria University's Department of Mathematics, Physics and Electrical Engineering, specializing in visible light communication (VLC) and optical systems. His research develops advanced communication protocols and hardware implementations for next-generation optical networks. Recent projects investigate CMOS-based camera communication, power allocation in NOMA-VLC systems, and fiber-optic UV sensors. Li's work frequently applies machine learning to optimize signal transmission and security in photonic networks.

PANG Hwee HwaView profile

Professor

• Artificial Intelligence and Data Science
• Data Management & Mining
• Information Systems & Technology
• +4 more

PANG Hwee Hwa is a Professor and Dean of the School of Computing and Information Systems at Singapore Management University (SMU). He holds a PhD in Computer Science from the University of Wisconsin-Madison (1994). His research focuses on Artificial Intelligence, Data Science, Cybersecurity, and Privacy-Preserving Technologies , with contributions to secure computation, encrypted databases, and trustworthy digital systems. Professional roles include leadership in national initiatives such as the Singapore National Research Foundation’s Global Young Scientist Summit (2014–2015) and board memberships in SkillsFuture Singapore (2016–2018). He has extensive experience in academic administration and has advised numerous projects in data privacy and system security. His work spans 100+ peer-reviewed publications across databases, security, and information systems. Key contributions include query authentication frameworks, steganographic file systems, and privacy-preserving search techniques. Current research priorities include digital transformation and trustworthiness in emerging technologies.

Sazadur RahmanView profile

Assistant Professor

• Hardware Security
• Supply Chain Security
• Electronic Design Automation
• +7 more

Sazadur Rahman is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Central Florida (UCF), affiliated with both ECE and Computer Science departments under the Cyber Security and Privacy Cluster. He holds a Ph.D. and M.Sc. from the University of Florida and a B.Sc. from Bangladesh University of Engineering and Technology. Previously, he worked as a Security Architecture Engineer at Intel Corporation, focusing on processor security hardening and threat modeling. His research interests include hardware security, semiconductor supply chain security, and AI-assisted chip design. He has published over 20 peer-reviewed papers and contributed to patents and textbooks. Education Ph.D. Electrical Engineering, University of Florida, 2022 M.Sc. Electrical and Computer Engineering, University of Florida B.Sc. Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology Research Interests His work centers on securing electronic design automation (EDA) tools, semiconductor supply chains, and hardware systems against reverse engineering, piracy, and attacks. Key areas include: Hardware obfuscation techniques (e.g., logic locking, watermarking) CAD tools for security assessment and mitigation Machine learning applications in secure chip design Secure heterogeneous integration and FHE acceleration Professional Activities Technical Program Committee Member: IEEE HOST Conference (2024) Reviewer: Top journals/conferences like IEEE Transactions on CAD, ACM TODAES, and DAC Awards 2022 IEEE/ACM DAC PhD Forum Finalist 2023 IEEE/ACM DATE Best Paper Nomination 2022 IEEE VTS TTTC Best Thesis Runner-Up Research Contributions His publications focus on innovative solutions like LLE for IC piracy mitigation, iPROBE for probing attack protection, and ReTrustFSM for RTL obfuscation. He has developed tools for threat modeling using NVD databases and evaluated cloud-based EDA platforms' security.

Shaoyi HuangView profile

Assistant Professor

• Efficient machine learning algorithms
• Algorithm-system co-design for AI acceleration
• Large-scale machine learning for chip design
• +3 more

Shaoyi Huang is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology. She holds a PhD in Computer Engineering from the University of Connecticut (2024), where she was advised by Professors Caiwen Ding and Omer Khan. Her research focuses on advancing AI systems through algorithm-hardware co-design, with emphasis on efficient machine learning algorithms, energy-efficient privacy-preserving techniques, and large-scale machine learning for chip design. She has received multiple accolades including the 2024 Machine Learning and Systems Rising Star award and the 2022 DAC Publicity Paper Award. Education: PhD in Computer Engineering, University of Connecticut (2024) Appointments: Assistant Professor, Stevens Institute of Technology (2024–present) Key Research Areas: AI acceleration, graph neural networks, privacy-preserving ML, and EDA applications Her work spans theoretical contributions to practical implementations, with publications in top-tier conferences like HPCA, ASPLOS, and NeurIPS. She actively contributes to the academic community through program committee roles (e.g., DAC 2025, IPDPS 2025) and serves as a Guest Editor for special issues on high-performance computing. Huang mentors PhD students and oversees a team advancing interdisciplinary AI research, including funded projects from NSF and industry partners like AWS and OpenAI. Awards highlight her impact: Marion & Frederick Buckman Engineering Fellowship (2024), multiple fellowships from UConn, and recognition at WISE conferences for promoting women in hardware security. Her lab emphasizes scalable solutions for real-world challenges in AI and hardware systems.

• Cryptography
• Network Security
• Distributed Systems
• +2 more

Antonio Nicolosi is an Associate Professor of Computer Science at Stevens Institute of Technology's Schaefer School of Engineering, specializing in cryptography and secure distributed systems. His NSF CAREER award-winning research explores lattice-based cryptography, non-commutative cryptographic protocols, and future internet architectures like NEBULA. Education PhD in Computer Science, New York University MS in Computer Science, Università di Catania Research Focus: Develops provably secure cryptographic systems using group-theoretic approaches, with applications in network security and privacy-preserving protocols. Honors: NSF CAREER Award (2014), EU Marie Curie Fellowship. Recent publications address pseudorandom functions, broadcast steganography, and internet architecture security. Teaches courses including Foundations of Cryptography and Secure Systems. Professional Service: Program Director for Cybersecurity Masters, editorial roles, and conference organization. Research funded by NSF, Air Force Research Lab, and DOD.

Arashdeep KaurView profile

Senior Lecturer

• Artificial Intelligence
• Audio Watermarking
• Deep Learning
• +3 more

Arashdeep Kaur is a Senior Lecturer in the Department of Computer Science at New Jersey Institute of Technology (NJIT). She holds a Ph.D. in Computer Science and Engineering from Amity University (2017), an M.Tech. from Punjab Technical University (2008), and a B.Tech. (2006) in the same field. Her research focuses on artificial intelligence, audio watermarking, deep learning applications, environmental science, and IoT-based healthcare solutions. She has contributed to crop freshness assessment using deep learning, ethanol production optimization from food waste, and heavy metal adsorption using nanotechnology. Dr. Kaur’s work spans over 20 years, with notable contributions in audio watermarking algorithms for security and robustness, including methods leveraging multi-resolution decomposition and neural networks. Her environmental projects address waste valorization and sustainable energy solutions. She actively teaches courses in AI and computer science fundamentals at NJIT. Her publications highlight interdisciplinary applications of CS in agriculture, cybersecurity, and environmental engineering. While no scientific awards are explicitly mentioned, her prolific research output indicates impactful contributions to multiple fields. She has advised no listed students, but her courses mentor future computer science professionals. Labs or collaborative teams are not detailed in the provided information, but her work intersects with NJIT’s strategic research areas in technology and sustainability.

Jordi Castellà RocaView profile

Associate Professor

• Cybersecurity
• Blockchain Technology
• Privacy Preservation
• +2 more

Jordi Castellà Roca is an Associate Professor at the Universitat Rovira i Virgili's Department of Computer Engineering and Mathematics. His research specializes in blockchain applications, cybersecurity, and privacy-preserving technologies. Recent publications demonstrate a consistent focus on decentralized systems, smart contracts, and secure access control mechanisms, with applications ranging from low-emission zones to smart grids. Key research areas include: Blockchain-based data management Privacy-enhancing technologies Cryptographic applications in IoT His work frequently addresses compliance frameworks like GDPR and explores practical implementations for urban infrastructure and digital services.

• Health Informatics
• Health Information Management
• Telehealth
• +5 more

Shannon Houser is a Professor in the Department of Health Services Administration at the University of Alabama at Birmingham (UAB), School of Health Professions. She also holds secondary appointments as a Senior Scientist at multiple UAB research centers, including the Center for AIDS Research and the Center for Clinical and Translational Science. Her academic career spans over two decades, with tenure as Associate Professor (2004–2019) and Assistant Professor (2004–2009). Dr. Houser earned her PhD in Public Health (Health Behavior) and an MPH in Epidemiology from UAB, alongside a B.S. in Health Information Management. Her research focuses on health information management, telehealth, data analytics, and global health. Notable contributions include pioneering work on telehealth privacy and security, machine learning in healthcare, and HIV/AIDS research. She chairs international committees like the IFHIMA Education Community of Practice and serves as an editorial board member for journals such as Perspectives in Health Information Management . Dr. Houser’s awards include the AHIMA Triumph Award (2024, 2021), FAHIMA designation (2015), and recognition for global health contributions. She has published over 70 peer-reviewed articles, edited textbooks, and developed toolkits like the AHIMA Telehealth Toolkit . Her professional service spans leadership roles in AHIMA, HIMSS, and AUPHA, alongside mentoring students and fostering international collaborations, notably at Tsinghua University in China. Key grants and projects include work on HIV care monitoring, Project HOPE evaluations, and curriculum development in health informatics. Labs/Teams: Active in UAB’s Center for AIDS Research, Center for Outcomes and Effectiveness Research and Education (COERE), and the Sparkman Center for Global Health. Collaborates internationally on health data literacy and telehealth innovation.