Find Academic Supervisors

• Cybersecurity
• Machine Learning
• Artificial Intelligence
• +5 more

Dr. Kehinde Babaagba is a Lecturer at the School of Computing (Edinburgh Napier University), specializing in cybersecurity, machine learning, and evolutionary computation. She holds a PhD in Computing and has contributed to malware analysis, AI-driven solutions for real-world challenges, and cybersecurity defense mechanisms. Her research emphasizes metamorphic malware detection, generative adversarial networks (GANs), and federated learning privacy. Education: BSc (Hons) Computer Science (First Class), Redeemers University, Nigeria MSc Computing Information Engineering (Distinction), Robert Gordon University PhD in Computing, Edinburgh Napier University Research Interests: Transfer learning, computer vision, cybersecurity applications of AI, evolutionary algorithms Awards: Outstanding Contribution Award (Evo* 2020) Best Paper (3rd Place, IEEE DSC 2022) Excellent Oral Presentation (ACM ICEIT 2019) Professional Roles: IEEE Member (Women in Engineering, Computational Intelligence) STEM Ambassador Associate Fellow of Advance HE Her recent work includes developing adversarial learning frameworks for malware evolution prediction and enhancing federated learning models for privacy compliance. She actively contributes to conferences as a reviewer and organizer, including roles as Finance Chair (IEEE DSC 2022) and Publication Chair (EvoAPPS 2022).

Emanuela MarascoView profile

Assistant Professor

• Artificial Intelligence
• Computer Vision
• Hyperspectral Imaging
• +3 more

Emanuela Marasco is an Assistant Professor at George Mason University within the College of Engineering and Computing , affiliated with the Information Sciences and Technology (IST) Department , Center for Secure Information Systems (CSIS) , and Institute for Digital Innovation (IDIA) . She leads the CySBeR Lab and holds a tenure-track position. PhD: Computer and Automation Engineering, University of Naples Federico II (Italy), 2010 BSc/MSc: Computer Engineering, University of Naples Federico II (Italy), 2006 Her research focuses on Artificial Intelligence (AI) with applications in Computer Vision , Hyperspectral Imaging , Biometrics , and Cybersecurity . Key themes include: Designing AI algorithms for identity verification using pattern recognition and deep learning . Developing multi-factor authentication systems, including a patented biometric-based MFA technology . Advancing hyperspectral imaging for biochemical analysis in security contexts. Her recent publications explore fingerprint anti-spoofing , demographic bias mitigation , and AI integration in virtual reality and military decision-making . She has received the Mason Innovation Award (2023, 2025) and IDIA P3 Faculty Fellowship (2023) . NSF-funded projects: "Sweaty Digits" ($200,000, 2023-2025) and "Hyperspectral Sweat Metabolite Detection" (2020). She has previously held postdoctoral positions at the University of North Carolina at Charlotte and West Virginia University , contributing to pattern recognition and biometric interoperability research.

• Cybersecurity
• Blockchain Technology
• Data Privacy
• +3 more

Hisham Ali is a Researcher at the School of Computing Engineering and the Built Environment at Napier University. His research focuses on cybersecurity, blockchain-based systems, and privacy-preserving technologies. He holds a Doctorate (PhD) completed in 2024, supervised by Prof Bill Buchanan, Dr Jawad Ahmad, and Dr Zakwan Jaroucheh. His work spans multiple areas including privacy-preserving machine learning, blockchain security frameworks, and IoT network protection. Notable contributions include developing homomorphic encryption schemes for secure SVM learning, analyzing blockchain threats, and creating intrusion detection systems leveraging deep learning. Recent publications (2021–2025) highlight advancements in trusted threat intelligence sharing via Hyperledger Fabric, chaos-based image encryption, and systematic reviews of blockchain vulnerabilities. His research emphasizes practical applications of cryptography and distributed ledger technologies to real-world cybersecurity challenges. Awards and grants are not explicitly mentioned in the provided texts. Hisham has collaborated extensively with industry and academic partners, contributing to both theoretical and applied cybersecurity solutions.

Hisham Al AssamView profile

Associate Professor

• Machine Learning
• Cyber Security
• Medical Imaging
• +3 more

Dr. Hisham Al Assam is a Reader in Computer Science at the University of Buckingham's School of Computing, serving as Programme Director for MSc Innovative Computing and MSc Applied Computing, and Research Lead of the School. He leads the Cyber Security Stream and teaches modules like Ethical Hacking, Digital Forensics, and Web Technologies. His research focuses on machine learning applications in cyber security (e.g., biometric recognition, encryption, cyber defense) and healthcare (e.g., medical image analysis for diseases like Alzheimer's and ovarian tumors). He has supervised numerous student projects across undergraduate and postgraduate levels and secured two KTP grants for biometric-based innovations. He is a member of the British Computer Society and contributes to university governance via Senate and Research committees. Research Interests: - Machine Learning in Cyber Security: developing algorithms for intrusion detection, encryption, and privacy-aware authentication. - Healthcare Informatics: automated analysis of medical images (X-rays, ultrasounds, microscopy) for disease diagnosis, including ovarian tumors, Alzheimer's, and atrial fibrillation. - Biometric Systems: designing secure authentication protocols using dynamic features and cloud integration. Grants & Collaboration: - Two KTP grants with Innovate UK and Deepnet Security for biometric product development. - Collaborative projects with institutions like University College London Hospitals and King's College London on medical image analysis. Labs & Teams: - Leads the Cyber Security Research Group at the School of Computing. - Co-leads interdisciplinary projects with medical researchers on AI-driven diagnostic tools.

Tamara LehmanView profile

Assistant Professor

• Computer Security
• Computer Architecture
• Microarchitectural Security
• +7 more

Tamara Lehman is an Assistant Professor at the University of Colorado Boulder in the Electrical, Computer & Energy Engineering Department , with a courtesy appointment in Computer Science . Her work focuses on computer security from microarchitectural perspectives , particularly in the intersection of computer architecture and security . PhD in Electrical and Computer Engineering from Duke University (2019) MEng from Duke University (2013) BS in Industrial and Systems Engineering from University of Florida (2007) Her research spans secure memory systems , side-channel attack mitigation , and trusted execution environments , with industrial experience at Intel Labs (2015-2016) leading to a patent on Cryptographic Cache Lines . She has authored 11 publications in top-tier venues, including a best paper award and honorable mention in Micro Top Picks. Email: Tamara.Lehman@colorado.edu

• Machine Learning
• Control Systems
• Signal Processing
• +3 more

Shuo Huang is an academic researcher with a focus on interdisciplinary fields spanning Machine Learning, Control Systems, and Signal Processing. Their work integrates theoretical advancements with practical applications in areas like neural networks, robotics, and sensor technology. They have contributed significantly to methodologies in predictive modeling, privacy-preserving machine learning, and optimization algorithms. Key research areas include the development of distributed Kalman filters for robotics, semi-supervised learning frameworks, and deep learning applications in computer vision and autonomous systems. They also engage in statistical process control and quality assurance, reflecting a blend of theoretical and applied engineering expertise. Notable contributions include advancements in privacy-preserving neural networks, adaptive control systems for electromechanical devices, and sensor design innovations. Their interdisciplinary approach bridges computer science, electrical engineering, and industrial applications.

Eleni BoumpaView profile

Researcher

• Smart Environments
• Healthcare Services
• Cyber-Physical Systems
• +3 more

Eleni Boumpa is a Researcher and Ph.D. candidate at the Department of Computer Science and Biomedical Informatics, University of Thessaly. She leads the AuDi-o-Mentia research team and is affiliated with the Intelligent Systems Laboratory. Her work focuses on assistive technologies for people with neurodegenerative diseases, smart environments, cyber-physical systems, and healthcare in consumer electronics. Education: BSc in Computer Science & Biomedical Informatics (2018), University of Thessaly Current Role: Ph.D. candidate since 2018, researching 'Ambient Assistive Systems in Smart Environments' Her research interests include developing smart systems for elderly care, gas leakage detection via TinyML, logistics optimization, and security in healthcare wearables. Her work is funded by the EPICS in IEEE program and has led to innovations like home assistive systems for dementia patients. Awards: 1st place in IEEE Mind the Gap 2017 (dementia assistive system) Finalist in Microsoft Imagine Cup 2017 3rd place at ECESCON 2017 (best business idea) Advising & Grants: As team leader of AuDi-o-Mentia, she coordinates interdisciplinary research on memory aids for neurodegenerative diseases. Her projects integrate acoustic-based systems, tinyML, and sensor networks into assistive technologies. Labs & Teams: Member of the Intelligent Systems Laboratory and founder of the AuDi-o-Mentia team, focusing on dementia care technologies.

Ruba Abu-SalmaView profile

Lecturer

• Cybersecurity
• Privacy-enhancing technologies
• Human-computer interaction (HCI)
• +3 more

Ruba Abu-Salma is a Lecturer in Computer Science at King’s College London, affiliated with the Cybersecurity Group and Human Centred Computing Group within the Department of Informatics. Her research focuses on interdisciplinary cybersecurity, privacy, human-computer interaction (HCI), and public policy, with an emphasis on vulnerable populations. She holds a PhD from University College London (UCL) and previously held postdoctoral roles at UC Berkeley and Inria Sophia Antipolis. Education: PhD in Computer Science, UCL (2019) Postdoctoral Researcher at ICSI (UC Berkeley) and Inria (2019–2021) Research Interests: Designing equitable privacy-enhancing technologies; smart home privacy; digital security for marginalized groups; privacy law and policy. Affiliations: King’s Cybersecurity Centre, EPSRC-NCSC Academic Centre of Excellence, Centre for Technology and the Body. Her work bridges computational and social science methods, addressing privacy and security challenges faced by vulnerable populations such as migrant domestic workers and older adults. Recent studies include smart home privacy dynamics, mHealth app vulnerabilities, and longitudinal migration security practices. Key achievements include publications at venues like ACM CHI, USENIX Security, and IEEE S&P, alongside media coverage in The New York Times and CNET. She leads projects funded by Google and the UK’s Technology Strategy Board, focusing on gaze-enhanced authentication and female health app privacy. Grants & Projects: “Usable Privacy in Female Health Apps” (Google, 2023–2025) EyeLock: Gaze-Enhanced Authentication (TSB, 2024–2025) Dr. Abu-Salma advises PhD students on topics intersecting cybersecurity, privacy, and marginalized communities. She actively participates in academic service roles, including organizing workshops on privacy and serving on program committees for top-tier conferences.

Reda BELLAFQIRAView profile

Researcher

• Federated Learning
• Homomorphic Encryption
• Data Security
• +3 more

Reda BELLAFQIRA is an Enseignant Chercheur (Researcher) at IMT Atlantique's Data Science Department, based in Brest. His work focuses on securing sensitive data processing in distributed systems, combining cryptography with machine learning techniques. Key areas include federated learning, homomorphic encryption, and watermarking for intellectual property protection. He has contributed to privacy-preserving frameworks in healthcare and IoT applications, emphasizing secure collaborative data analysis without compromising confidentiality. Research Interests: Secure federated learning architectures and robustness against adversarial attacks Cryptography applications in AI, including homomorphic encryption for encrypted data processing Watermarking techniques for model integrity and ownership in distributed environments Privacy-preserving methods for healthcare data (e.g., EHRs, genomics) IoT cybersecurity and embedded system security for medical devices Key Contributions: His 2025 work on blockchain-enhanced watermarking for federated learning and 2023 research on automated EHR de-identification exemplify his focus on practical security solutions. Recent trends show increasing emphasis on interdisciplinary approaches merging cryptography with healthcare informatics and IoT systems. Labs/Teams: Active in IMT Atlantique's Data Science Department research groups, collaborating on EU-funded projects related to federated learning in healthcare and secure IoT ecosystems.

• Internet of Things
• Machine Learning
• Data Security
• +4 more

Farhan Amin is a prolific researcher in computer science with a focus on Internet of Things (IoT) technologies, data security, and smart systems. He has published extensively in high-impact journals like IEEE Access and PeerJ Comput. Sci., collaborating with international experts such as Rashid Abbasi and Gyu Sang Choi. His work spans domains including smart city analytics, medical data protection, and next-generation IoT frameworks. Key Contributions: Dynamic trust management in IoT, 3D arthritis detection models, and hybrid data watermarking techniques. Collaborators: Rashid Abbasi, Salabat Khan, Abdul Mateen, Isabel de la Torre Díez. His research bridges theoretical innovation and practical applications, particularly in cybersecurity for IoT, network navigation, and healthcare analytics. Recent publications highlight advancements in zero-knowledge proofs, deep learning for medical imaging, and 6G-enabled healthcare systems. Farhan’s work on anticancer peptide prediction and child custody decision modeling demonstrates interdisciplinary reach. While not explicitly stated, his output suggests a faculty or senior research role at an institution engaged in cutting-edge computational science.

• Cybersecurity
• Internet of Things (IoT)
• Vehicular Networks
• +3 more

Samiha AYED is an Associate Professor at the Université de Technologie de Troyes (UTT), affiliated with the LIST3N laboratory. She holds key administrative roles including Co-Responsable of the FISEA SN engineering branch (Systems Numeriques), and has led the ISI (Computer Science and Information Systems) and CSR (Network Convergence) engineering branches. She is also a member of the UTT Scientific Council and multiple institutional committees. Her research focuses on cybersecurity, IoT, vehicular networks, and AI-driven security solutions. Notable contributions include frameworks for UAV security, blockchain-based trust management in vehicular networks, and federated learning applications for intrusion detection. She has supervised four PhD theses and published extensively in top-tier journals and conferences. Her work addresses critical challenges in secure communication protocols, distributed systems, and medical data protection.

Tom Heine NättView profile

Associate Professor

• Computer Science
• Information Security
• Programming Languages
• +3 more

Tom Heine Nätt is an Associate Professor at the Department of Computer Science and Communication at Høgskolen i Oslo og Akershus. His academic work focuses on foundational computer science concepts, information security, and programming language theory. He has contributed extensively to technical lexicon entries covering IT infrastructure, cyber-security practices, software development methodologies, and digital literacy education. His research interests include exploring system reliability through redundancy mechanisms, mitigating cyber-threats via robust validation techniques, and clarifying core IT concepts for educational purposes. He has authored over 50 entries in the Store Norske Leksikon , addressing topics ranging from API architecture to quantum computing basics . Professionally, he teaches courses in software engineering and cyber-security at HiOA. His publications consistently emphasize clear technical communication and practical application of theoretical principles.

• Artificial Intelligence
• Neural Networks
• Robotics
• +5 more

Abdullatif Baba is an Assistant Professor in the Department of Computer Engineering at Turkish Aeronautical Association University. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and sustainable energy systems. He develops solutions for smart infrastructure, including AI-driven energy forecasting, autonomous drones for grid maintenance, and hyperspectral imaging techniques. His research interests span: AI/ML Systems : Neural networks, probabilistic forecasting, and FPGA-accelerated deep learning Robotics : Autonomous drones with computer vision for industrial and energy applications Sustainable Energy : Solar-based systems, smart grid optimization, and consumption prediction Security : Chaos-based cryptographic systems for secure communications Recent publications (2020-2024) demonstrate strong trends in practical AI implementations. Key themes include energy forecasting using adaptive neural networks (11 papers), robotics for infrastructure maintenance (4 papers), computer vision for biometrics and imaging (3 papers), and cryptographic systems (2 papers). Methodologies frequently involve hybrid approaches combining ANN, fuzzy logic, and hardware acceleration. No awards, students, or grant details were mentioned in the source material. Research collaborations include institutions in Turkey and the Middle East.

Sergio Salinas MonroyView profile

Associate Professor

• Cyberphysical Systems
• Network Security
• Additive Manufacturing Security
• +6 more

Sergio Salinas Monroy is an Associate Professor at Wichita State University's College of Engineering, School of Computing. His research focuses on cyberphysical systems, network security, and privacy enhancement in critical infrastructures like additive manufacturing, power grids, and edge computing networks. He currently leads the Graduate Certificate in Information Assurance and Cybersecurity program and spearheaded the NSA/DHS CAE-CD designation for WSU. Academic Rank: Associate Professor Department: School of Computing University: Wichita State University Email: sergio.salinasmonroy@wichita.edu His research spans secure resource allocation in supply chains, cyberfraud investigation, and federated deep learning systems. Recent publications emphasize adversarial machine learning, intrusion detection, blockchain applications in manufacturing, and privacy-preserving algorithms. His work integrates deep learning, anomaly detection, and cryptographic protocols for industrial cybersecurity. Research trends in his articles include cyberphysical systems security (4 entries), privacy preservation in distributed networks (3 entries), and machine learning optimization for threat detection (5 entries). He also explores blockchain integration, edge computing economics, and energy-based attack detection in IoT-enabled systems. Professor Salinas Monroy actively contributes to academic service as an organizer and technical program committee member for IEEE conferences. His office hours are held in Jabara Hall (239) on Wednesdays from 3:30–5:00 PM.

• Databases
• Data Modeling
• Software Security
• +3 more

Roger Midtstraum is a Professor at the Department of Computer Science , Norwegian University of Science and Technology (NTNU), and currently serves as the Vice Dean for Education at the Faculty of Information Technology and Electrical Engineering. He previously held leadership roles including Dean of Engineering Education (2013-2017), Chairman of UHR-MNT (2016-2018), and Chairman of NRT (2013-2016). His career spans academia and technical innovation, with affiliations across institutions like Universitetet i Nordland, Tapir Akademisk Forlag, and ACM Publications. Research interests include software security , digital rights management (DRM) , multimedia systems , and data modeling . His work explores tamper protection in online clients, anti-cheating mechanisms in gaming, secure dissemination of temporal media, and metadata-driven search methodologies (e.g., the SESAM framework). Publications reflect interdisciplinary applications in supply chain management , mobile services , and image processing , with trends toward integrating security , QoS , and semantic networks . Notable collaborations include co-authors Gisle Grimen , Christian Mönch , and Alf Inge Wang . Teaching includes courses like TDT4145 - Data Modelling, Databases and Database Management Systems . He emphasizes curriculum innovation , as seen in his 2012 Textbook: IT Grunnkurs , and leadership in educational policy through roles in national councils (UHR-MNT, NRT).