جست‌وجوی استاد و پژوهشگر

Katerina Kantaمشاهده پروفایل

مدرس

• Password Cracking
• Digital Forensics
• Cybersecurity
• +۳ مورد دیگر

Katerina Kanta is a Lecturer at the University of Portsmouth's School of Computing within the Faculty of Technology. She is actively affiliated with the Portsmouth AI and Data Science Centre and the Centre for Cybercrime and Economic Crime, contributing to interdisciplinary cybersecurity research. She holds a Ph.D. in Context-Based Password Cracking for Digital Investigation from University College Dublin, awarded on June 25, 2023. Her research spans password cracking, digital forensics, cybersecurity, authentication, and STEM education. She applies AI techniques to enhance forensic investigations and examines societal impacts through studies on password portrayal in media and mobile health security. Her work aligns with UN Sustainable Development Goals for security and quality education. Recent publications reveal a strong trend toward context-based password cracking using generative models, alongside investigations into cybersecurity frameworks for 6G networks and mobile health applications. This demonstrates technical innovation blended with practical societal applications across digital forensics and security domains. As a Co-Investigator on the active XTRUST-6G project (2025-2027), she contributes to developing security solutions for next-generation telecommunications. She has no listed doctoral advisees but participates in collaborative research teams through university centers. She actively engages with the Portsmouth AI and Data Science Centre and Centre for Cybercrime and Economic Crime, working within teams that address real-world security challenges through applied research and industry partnerships.

• Artificial Intelligence
• Cloud Computing
• Internet of Things
• +۷ مورد دیگر

Aamir Akbar serves as an Assistant Professor in the Department of Computer Science & Information Systems at Abdul Wali Khan University Mardan (AWKUM), where he also co-directs both the AWKUM AI Lab and AWKUM Robotics initiatives while coordinating final year projects. His academic journey culminated in a PhD from Aston University, Birmingham, UK, with research focused on energy-efficient methods for hybrid mobile cloud computing. His educational background includes a PhD in Computer Science from Aston University (2015-2019, awarded February 2020), where his dissertation explored energy-efficient approaches for hybrid mobile cloud computing systems. Dr. Akbar's research spans multiple cutting-edge domains in computer science, with particular emphasis on Artificial Intelligence , Cloud and Fog Computing , Internet of Things , and Software Defined Networks . His multidisciplinary approach combines evolutionary computation, multi-objective optimization, and machine learning to develop resource-efficient intelligent systems. His work frequently addresses challenges in Cyber-Physical Systems, Mobile-Cloud Computing, and IoT/IoV applications, demonstrating strong practical relevance to real-world problems. Analysis of his recent publications (2021-2024) reveals a clear research trajectory toward increasingly sophisticated AI applications in networking and distributed systems. His work shows strong focus on reliability, energy efficiency, and security across multiple domains including medical IoT, smart cities, and industrial automation. The growing citation impact (612 total citations, h-index: 14) demonstrates increasing recognition of his contributions to these fields. Dr. Akbar maintains active presence in the research community with 19 total publications showing accelerating output in recent years (6 in 2021, 2 in 2022, 5 in 2023, and 2 in 2024). His Google Scholar profile reflects substantial impact with an h-index of 14 and i10-index of 16. As an educator and researcher, Dr. Akbar brings both academic rigor and industry experience to his role. His technical expertise spans the full stack of modern computing systems, from frontend development (HTML, CSS, Angular, React) through backend frameworks (Flask, Django, Node.js) to database systems (MySQL, PostgreSQL, MongoDB) and cloud infrastructure (AWS, Kubernetes, Docker). This comprehensive skill set enables him to bridge theoretical research with practical implementation. He leads research initiatives through the AWKUM AI Lab and AWKUM Robotics, providing students with opportunities to engage in cutting-edge projects that combine theoretical foundations with real-world applications. His GitHub activity shows ongoing engagement with AI and systems development projects, including repositories focused on neural networks, Python programming, and network simulation.

Christoph Sorgeمشاهده پروفایل

استاد

• Legal Informatics
• Data Protection Law
• IT Security
• +۱۲ مورد دیگر

Christoph Sorge is a full Professor and Head of the Chair of Legal Informatics at Saarland University, where he leads interdisciplinary research at the intersection of law and computer science. His work focuses on data protection, IT security, and the legal implications of emerging technologies such as AI, blockchain, and wearables. He is actively involved in teaching courses like 'Recht der Cybersicherheit' and 'IT-Forensik für Juristen'. The Chair of Legal Informatics is engaged in numerous high-impact research projects funded by BMBF, DFG, and BMWK, including D'Accord , EDWI , K3I-Cycling , PAIRS , ScaleTrust , and research on botnet crime . These projects explore adaptive privacy systems, data spaces, AI governance, and cybersecurity compliance, often in collaboration with legal and technical partners. His research interests span data protection law , cybersecurity , AI and law , digital ecosystems , and applied cryptography . He has contributed to the legal classification of Bitcoin and digital signatures, and his team develops tools for transparent and compliant data processing. The recent publications reflect a strong trend toward interdisciplinary compliance solutions , combining legal analysis with technical design. Themes include GDPR-compliant privacy dashboards, secure data exchange in crises, ethical AI, and legal frameworks for data trusteeship. The work consistently emphasizes user rights , transparency , and technical feasibility in legal contexts. Notable scientific contributions include project-based research rather than individual awards, though the impact is evident in policy-relevant outputs and collaborations with public institutions like the Saarland State Chancellery. Prof. Sorge supervises research staff on topics such as algorithmic summaries of court rulings, legal issues of cryptography, wearable data protection, and cloud security. While formal PhD students are not listed, his team includes researchers like Aljoscha Dietrich and Bianca Steffes. The Chair also contributes to eGovernment education through the eGov Campus project, developing data protection training for administrative staff. Lab and team activities are centered around the Chair of Legal Informatics , which functions as a research hub for legal-technical innovation, hosting internal projects and participating in national and international collaborations.

Shambhu J. Upadhyayaمشاهده پروفایل

استاد

• Information Assurance
• Computer Security
• Behavioral Biometrics Authentication
• +۷ مورد دیگر

Shambhu J. Upadhyaya is a Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY . He also serves as Director of the SEAS/SOM Cybersecurity MS Program and the Center of Excellence in Information Systems Assurance Research and Education (CEISARE) , recognized by the NSA/DHS as a Center of Excellence. His research spans information assurance , computer security , behavioral biometrics , and fault-tolerant computing . Ph.D., Electrical & Computer Engineering, University of Newcastle, Australia (1987) M.E./B.E., Electrical Engineering, Indian Institute of Science, Bangalore (1982/1979) His research projects focus on insider threat assessment , continuous authentication , deception techniques , secure wireless communications , and game-theoretic security models . He has directed 300+ publications and mentored Ph.D./M.S. students like A. Sanzgiri , R. Mehresh , and M. Jadliwala , many of whom hold prominent roles in tech companies. Key scientific recognitions include: IEEE Fellow IEEE Region 1 Technological Innovation Award (2018) SUNY Chancellor's Award for Scholarship (2019) Best Poster at IEEE BTAS Conference (2016) IBM Faculty Partnership Fellowship (2000-01) He has taught courses like CSE566 Wireless Networks Security , CSE341 Computer Organization , and CSE552 VLSI Testing , while leading departmental initiatives such as ABET accreditation and internship coordination. His Electronic Test and Design Automation Lab was sponsored by IBM and supported research on VLSI testing.

Andrew Cramptonمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Computational Mathematics
• +۱۲ مورد دیگر

Andrew Crampton is Professor of Computational Mathematics and Associate Dean for Teaching and Learning at the University of Huddersfield, affiliated with the Department of Computer Science, School of Computing and Engineering. He is a member of the Centre for Autonomous and Intelligent Systems, the Centre for Planning, Autonomy and Representation of Knowledge, and an affiliate of the Centre for Cybersecurity. His research interests span Artificial Intelligence, Machine Learning, Computational Mathematics, Support Vector Machines, Radial Basis Function Networks, Data Classification, and Automated Planning . His work applies advanced computational techniques to real-world problems in engineering, cybersecurity, and intelligent systems, contributing to UN Sustainable Development Goals. He has supervised over ten PhD students in areas such as SCADA systems, network security, 3D printing, and neuro-fuzzy inference systems. The most recent research articles highlight a strong trend in applying deep learning, particularly convolutional neural networks, to defect detection in additive manufacturing processes like laser powder bed fusion. Additional work explores biometric authentication via keystroke dynamics and automated planning. These contributions reflect a shift from foundational mathematical approximation methods to applied AI and intelligent systems. Scientific Awards: No specific awards listed, but h-index of 15 (Google Scholar) and 11 (Scopus) indicate significant research impact. Andrew Crampton actively supervises PhD students and oversees the School’s Placement Unit as Academic Coordinator. His research has led to applications in industrial systems, cybersecurity, and advanced manufacturing, supported by collaborations and external engagements. He has presented at academic conferences and contributed to knowledge engineering in automated planning. He leads and contributes to multiple research centers, including the Centre for Autonomous and Intelligent Systems, where work on AI and intelligent control systems is conducted, and the Centre for Cybersecurity, focusing on authentication and intrusion detection.

Paloma Liuمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Connected and Autonomous Vehicles
• Data Analytics
• +۱۲ مورد دیگر

Dr. Paloma Liu is a Senior Lecturer in Project Management at Huddersfield Business School, University of Huddersfield. She serves as course leader for BSc programs in Business Data Analytics, Logistics & Supply Chain Management, and Business with Project Management. She is a core member of the Future Mobility Lab and the Sustainable Living Research Centre, contributing to interdisciplinary research in mobility and sustainability. Her research expertise lies at the intersection of cybersecurity, connected and autonomous vehicles (CAVs), data analytics, and public perception. She investigates the security risks of CAVs, keystroke biometrics, and urban mobility patterns using AI and computer vision. Her work aligns with UN Sustainable Development Goals, particularly in sustainable cities and responsible consumption. The recent publications highlight a strong trend in cybersecurity for intelligent transportation systems, biometric authentication, and data-driven mobility solutions. Her work combines technical depth with policy relevance, often involving collaboration with industry and government stakeholders. Fellow of the Higher Education Academy (FHEA) Certified Project Management Professional (PMP) by PMI Dr. Liu is actively supervising PhD students and currently offers an EPSRC-funded PhD position in Post Quantum Cybersecurity, jointly supervised with Professor Simon Parkinson. She also serves as an External Examiner at Queen Margaret University (2025–2029), MSc Dissertation Supervisor at University College London (since Apr 2023), and Visiting Lecturer at Montpellier Business School (since Mar 2023), reflecting her growing academic influence. She leads the Future Mobility Lab, a research team focused on next-generation transport systems, where she mentors students and collaborates on projects involving AI, cybersecurity, and sustainable urban development.

Alex Alexandrouمشاهده پروفایل

دانشیار

• Cybersecurity
• Health Information Technology
• Mobile Device Security
• +۱۲ مورد دیگر

Dr. Alex Alexandrou is an Associate Professor in the Department of Security, Fire, and Emergency Management at John Jay College of Criminal Justice, City University of New York (CUNY). His academic and professional expertise spans cybersecurity, health information technology, mobile device security, cybercrime, digital forensics, and machine learning applications in security. He teaches undergraduate and graduate courses in cybersecurity, research methods, and security systems. Education: D.P.S. in Computing Studies, Pace University M.F.A., Brooklyn College, CUNY B.A., Youngstown State University Dr. Alexandrou's research centers on system security and privacy in healthcare, mobile forensics, biometric authentication, and the societal implications of cybercrime. His work bridges technical cybersecurity with policy and legal frameworks, particularly in health IT environments. He has published extensively on mobile device vulnerabilities, IoT security, and the impact of AI-generated content like deepfakes on digital evidence. His recent publications (2018–2023) reflect a strong focus on healthcare cybersecurity, risk perception models, network and mobile security, and the legal aspects of cybercrime. These works span journals and conference proceedings, with recurring themes in secure technology adoption, forensic investigation, and regulatory compliance. Scientific Awards: No awards listed in the provided text. Dr. Alexandrou has 18 years of experience in Health Information Technology leadership, blending academic and industry expertise. He has advised on software integration, virtualization, cloud networks, and security platforms. Though no formal students are listed, his capstone and research methods courses suggest mentorship roles. He has contributed to collaborative research and publications, particularly in biometrics and AI-driven security challenges. His work indicates ongoing engagement with grants and interdisciplinary projects, especially in healthcare IT security and digital forensics. Dr. Alexandrou served as a sergeant in the Hellenic Army, where he developed leadership and operational discipline. His multilingual ability in Greek (bilingual) supports cross-cultural research and collaboration. While no specific lab or research team is named, his publications suggest involvement in cybersecurity and health IT research initiatives at John Jay College and in collaboration with Pace University and other institutions.

Gleb Tcheslavskiمشاهده پروفایل

دانشیار

• Electroencephalogram (EEG) Analysis
• Digital Signal Processing
• Biomedical Signal Processing
• +۲ مورد دیگر

Dr. Gleb Tcheslavski is an Associate Professor in the Phillip M. Drayer Department of Electrical Engineering at Lamar University (Beaumont, TX), where he has taught since 2007. He holds a Ph.D. in Electrical Engineering from Virginia Tech and dual degrees from Bauman Moscow State Technical University. His academic trajectory includes roles as Assistant Professor (2008-2014) and Visiting Assistant Professor (2007-2008). Research Focus: Dr. Tcheslavski leads the Applied DSP Research Laboratory, specializing in EEG analysis for biomedical and cognitive applications. Core research areas include: EEG-based diagnosis of neurological disorders (alcohol dependence, autism) Biomedical signal processing for visual/auditory perception studies EEG biometrics and human-computer interaction Transportation safety using virtual reality and neural response analysis His work bridges signal processing theory with clinical and industrial applications. Publication Trends: Recent articles reveal two dominant themes: (1) EEG applications in neuroscience/medicine (e.g., biomarkers for autism, color perception studies) and (2) engineering education innovation. His NSF-funded research promotes collaborative online labs for active learning, reflecting a pedagogical focus. Awards & Honors: Dr. Anita Riddle Excellence in Engineering Teaching Fellowship (2018-2021) University of Houston Postdoctoral Fellowship (2006-2007) President’s Graduate Scholarship, Russia (1996-1997) Grants & Advising: Secured $294,097 NSF grant (2021-2023) for collaborative online labs. Mentored 20+ graduate students in EEG/signal processing projects, including biometrics and traffic safety. Current lab members include 1 M.S. candidate. Laboratory Leadership: Directs the Applied DSP Research Laboratory, focusing on EEG signal acquisition/analysis. Recent projects explore Autism diagnosis, EEG biometrics, and driver cognition in virtual environments.

Duke Gledhillمشاهده پروفایل

مدرس ارشد

• Surface Measurement
• Imaging Techniques
• Lighting
• +۷ مورد دیگر

Duke Gledhill is a Senior Lecturer in the Department of Computer Science at the University of Huddersfield. He is affiliated with multiple research centers including the Centre for Visual and Immersive Computing, Centre for Sustainable Computing, and Centre for Autonomous and Intelligent Systems. His research spans surface measurement, virtual reality, and digital media. Joined the University of Huddersfield in 1997 (student), graduated in 2001, and began teaching after doctoral studies in 2004. Active in UN Sustainable Development Goals (SDGs) through sustainable computing initiatives. Research Interests Gledhill's work focuses on surface measurement , virtual reality , and imaging techniques . He explores lighting effects in immersive environments, photogrammetry optimization for metaverse applications, and biometric authentication in VR. His SDG contributions emphasize sustainable digital engineering. Advising & Supervision Accepts PhD students in virtual reality and digital media domains. Supervised 6 students according to Huddersfield's records. Labs & Collaborations Key member of the Centre for Visual and Immersive Computing (CVIC) and collaborates with sustainable/AI research groups. Engages in cross-disciplinary projects involving orthopedics, educational technology, and games development.

Levent Arslanمشاهده پروفایل

استاد

• Speech Recognition
• Speech Synthesis
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Dr. Levent Arslan is a faculty member at Boğaziçi University, where he has served since 1998. He earned his Ph.D. from Duke University in 1996 and worked as a Research Engineer at Entropic Research in the USA before joining academia. He is also the founder and Chairman of the Board at SESTEK, a pioneering company in Turkish speech recognition and synthesis technologies. His research focuses on speech recognition, speech synthesis, assistive technologies, and natural language processing . His innovations have enabled computer access for visually impaired users through synthesized speech. His work bridges academic research and real-world applications in AI-driven voice systems. The analysis of his recent publications reveals a consistent focus on Turkish language speech technologies, including acoustic modeling, speaker adaptation, emotion detection, and robust feature extraction. His work combines deep learning, signal processing, and linguistic analysis to advance voice interfaces in challenging environments. Levent Arslan has made significant contributions to both research and industry. He holds 15 patents and has published extensively in speech technology. His work at SESTEK exemplifies technology transfer from academia to impactful commercial applications. He has advised multiple students and led research projects in speech processing, though specific names are not listed. His lab or research group likely focuses on spoken language systems and AI for accessibility. Future work may involve multilingual voice assistants, low-resource language modeling, and real-time emotion-aware systems.

• Data Management
• Data Analytics
• Spatio-temporal Databases
• +۹ مورد دیگر

Mohammed Eunus Ali is a Senior Lecturer in the Department of Software Systems & Cybersecurity within the Faculty of Information Technology at Monash University, Australia. He holds a PhD in Computer Science and Software Engineering from the University of Melbourne and has previously served as a Professor at the Bangladesh University of Engineering and Technology (BUET), where he led a research group in Data Science and Engineering for over a decade. He has also held research positions at Monash University, Swinburne University, the University of Melbourne, and RMIT University. PhD : Computer Science and Software Engineering, University of Melbourne (2010) M.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (2002) B.Sc. Engg. : Computer Science and Engineering, Bangladesh University of Engineering and Technology (1999) Dr. Ali’s research spans data management, analytics, and learning , with a strong focus on spatio-temporal data, geo-social networks, and multimodal high-dimensional data . His work enables applications in urban computing, intelligent transportation systems, and smart, sustainable cities . In recent years, he has expanded into Generative AI and large language models (LLMs) , exploring their role in enhancing geo-spatial query processing, SQL generation, and data engineering tasks. His publications appear in top-tier venues such as ACL, TKDE, VLDB, ICDE, SIGSPATIAL, and IEEE Access . His recent publications reflect a strong trend toward AI-driven solutions for real-world spatial and health problems , including blood glucose prediction for diabetics, seismic intensity forecasting, eco-friendly route planning, and LLM-based code generation. These works demonstrate a convergence of deep learning, spatio-temporal analytics, and real-world system design . Scientific Awards: Bangladesh University Grants Commission Award (2012) ADC Best Poster Award (2016) SSTD Best Demo Award (2017) ADC Best Paper Award (2022) Dr. Ali actively contributes to the research community as a Program Committee Member for premier conferences including SIGMOD, VLDB, ICDE, and SIGSPATIAL . He is a Senior Member of the ACM and currently supervises PhD students, focusing on cutting-edge topics in data science and AI. His collaborative research network spans institutions in Australia and Bangladesh, contributing to advancements in both academic and applied domains. His work aligns with the UN Sustainable Development Goals , particularly in the areas of sustainable cities, innovation, and quality education.

Fayez Gebaliمشاهده پروفایل

استاد

• Computer Communications
• Digital VLSI Design
• Digital Signal Processing
• +۱۰ مورد دیگر

Dr. Fayez Gebali is a Professor in the Department of Electrical and Computer Engineering at the University of Victoria. He holds a BSc from Cairo University, another BSc from Ain Shams University, and a PhD from the University of British Columbia. His research focuses on computer communications, digital VLSI design, signal processing, and cybersecurity. He is particularly known for contributions to networks-on-chips, hybrid communication systems (e.g., FSO/RF), and cryptographic solutions for IoT devices. Education: BSc, Cairo University BSc, Ain Shams University PhD, University of British Columbia His research interests span computer architecture , communication networks , and secure embedded systems . Recent work emphasizes digital health applications, including AI-driven medical imaging (e.g., TongueTransUNet for tongue contour segmentation) and zero-trust frameworks for healthcare data protection (ZTCloudGuard). He has also published extensively on IoT security, cryptographic algorithms, and hardware acceleration techniques. Notable contributions include pioneering work on networks-on-chips (NoC) optimization, hybrid FSO/RF transmission systems, and efficient modular multipliers for constrained devices. His publications cover over 15 years of impactful research, with a focus on bridging theoretical advancements and practical implementations in high-performance computing and cybersecurity.

• Artificial Intelligence
• Multi-Agent Systems
• Privacy and Security
• +۳ مورد دیگر

Arthur Jakobsson is a Course Instructor at the Computer Science Department of Carnegie Mellon University. His research focuses on multi-agent systems, privacy and security, and AI applications in robotics. He has contributed to improving pathfinding algorithms for autonomous systems and developing techniques to combat deepfakes and communication risks. Recent publications highlight his work on imitation learning for multi-agent pathfinding (MAPF), heuristic search enhancements, and AI-assisted methods for detecting deepfake audio. His privacy research includes permission management frameworks and mitigating tracking risks in digital communications. He holds a strong interest in cybersecurity applications of machine learning. No academic awards or grants were explicitly mentioned in the provided materials. Advising relationships remain unreported in the current dataset. His work bridges theoretical computer science with practical security implementations in autonomous systems.

Qiben Yanمشاهده پروفایل

دانشیار

• AI Security
• Blockchain System Security
• Mobile and IoT Security
• +۵ مورد دیگر

Qiben Yan is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University (MSU), leading the Secure and Intelligent Things (SEIT) Lab. He holds a Ph.D. from Virginia Tech and has prior experience as an Assistant Professor at the University of Nebraska-Lincoln and as a security researcher at Shape Security, where he contributed to the development of the pioneering 'botwall.' His research focuses on AI Security, Blockchain, IoT/Mobile Security, and Wireless Communication Security. He serves as an Associate Editor for IEEE Transactions on Information Forensics and Security (TIFS) and has been recognized with prestigious awards such as the NSF CRII Award (2016), ACM SenSys Best Paper Award (2021), and IEEE SECON Best Paper Award (2020). Educations: Ph.D. in Computer Science, Virginia Tech His research interests span adversarial machine learning, AI-driven cybersecurity solutions, blockchain system integrity, and privacy-preserving technologies. Recent work includes frameworks for decentralized carbon footprint tracking, defenses against adversarial attacks in autonomous systems, and LLM customization for moving target defense. His research has been supported by NSF (CPS, SaTC, NeTS, SpecEES), DoE, Ford, and Cisco. Awards: ACM CCS Best Paper Honorable Mention (2022) ACM SenSys Best Paper Award (2021) IEEE SECON Best Paper Award (2020) NSF CRII Award (2016) UNL Teaching Awards (2015, 2017) Grants and Labs: Lead researcher at SEIT Lab Funding from NSF, DoE, Industry Partners (Ford, Cisco) His lab explores cutting-edge topics like AI security, IoT privacy, and cyber-physical system defenses, with findings featured in BBC Radio, Scientific American, and Forbes.

• Smart Grid Security
• Privacy-Preserving Techniques
• Federated Learning
• +۵ مورد دیگر

Mohamed I. Ibrahem is an active academic researcher specializing in cybersecurity applications for smart grid infrastructure and Internet of Things systems. His work bridges computer science, electrical engineering, and artificial intelligence with a particular focus on privacy-preserving techniques and secure machine learning applications. Dr. Ibrahem's research interests center on smart grid security , where he has developed innovative approaches for electricity theft detection, false data injection prevention, and privacy-preserving monitoring systems. His work in federated learning security addresses critical vulnerabilities in distributed machine learning systems, particularly against Trojan attacks and evasion techniques. Additional research areas include explainable AI applications in healthcare diagnostics, IoT security mechanisms, and deep learning optimization for resource-constrained environments. His recent publication trends reveal a growing emphasis on practical security implementations for real-world energy infrastructure, with increasing attention to explainability and robustness in AI-driven security systems. The interdisciplinary nature of his work connects cybersecurity principles with specific domain challenges in power systems and healthcare applications. Dr. Ibrahem has secured research funding for multiple projects focused on smart grid protection systems and privacy-preserving machine learning frameworks, though specific grant details are not visible in the publication metadata. His collaborative research network spans multiple international institutions with strong connections to Middle Eastern universities.