جستجوی استاد راهنمای دانشگاهی

Charles Gillanمشاهده پروفایل

مدرس ارشد

• High Performance Computing (HPC)
• Artificial Intelligence (AI) in Healthcare
• Quantum Computing
• +۴ مورد دیگر

Charles Gillan is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the High Performance and Distributed Computing department and the Institute of Electronics, Communications & Information Technology. His research bridges HPC systems, AI applications in healthcare, and computational physics. Key projects include managing ICU patient care via neural networks, exascale-ready mathematical packages, and edge computing architectures. Research interests focus on high-performance computing (HPC), quantum computing, real-time data analytics, and electron-molecule scattering simulations. Notable contributions include developing microserver architectures for edge analytics and advancing AI-driven clinical decision support systems. Gillan has collaborated on interdisciplinary projects like food authenticity testing using spectroscopy and improving ventilator management in intensive care units. Publications span AI in healthcare, HPC system design, and computational methods for physics problems. He has secured funding for initiatives such as the KTP partnership with Foods Connected Ltd and the HANDHELD olfactory detection project. Gillan's work emphasizes practical applications of advanced computing across healthcare, engineering, and cybersecurity domains.

Mitchell L. Neilsenمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Distributed Systems
• Scientific Computing
• +۷ مورد دیگر

Mitchell L. Neilsen is a Professor in the Department of Computer Science at Kansas State University's College of Engineering, where he also serves as the graduate program director. He holds the Warren and Gisela Kennedy - Carl and Mary Ice Keystone Research Scholar position and maintains an active research program with multiple ongoing projects. His educational background includes a Ph.D. in Computer Science (1992), M.S. in Computer Science (1989), and M.S. in Mathematics (1987), all from Kansas State University, plus a B.S. in Mathematics Education from the University of Nebraska-Kearney (1982). After beginning his career as an assistant professor at Oklahoma State University, he returned to K-State in 1996. Research Interests: Cyber-Physical Systems: Design, Analysis, Verification of systems integrating computing, networking, and physical processes Distributed Systems: Algorithms, design, and analysis of distributed computing systems Scientific Computing: Computational Fluid Dynamics, Finite Element Analysis, High Performance Computing, and Simulation Application Areas: Agriculture technology, Dam safety analysis, Mobile applications, Natural resources management, and Real-time Embedded Systems His research program shows clear evolution toward agricultural technology applications, particularly high-throughput phenotyping, while maintaining strong foundations in cyber-physical systems and scientific computing. Recent publications indicate increasing integration of machine learning and computer vision techniques into traditional research areas. Research Funding: National Science Foundation U.S. Department of Agriculture Sandia National Laboratories Department of Homeland Security Private industry partners Dr. Neilsen has mentored numerous graduate students through their M.S. and Ph.D. programs, with recent advisees focusing on applications in agricultural technology, dam safety, and embedded systems. His advising approach emphasizes practical applications of theoretical computer science concepts. Current Teaching (Fall 2024): CIS 450 - Computer Architecture and Operations CIS 625 - Concurrent Software Systems CIS 720 - Advanced Operating Systems

Latifur Khanمشاهده پروفایل

استاد

• Data Mining
• Cybersecurity
• Machine Learning
• +۲ مورد دیگر

Dr. Latifur Khan is a Professor in the Department of Computer Science at the University of Texas at Dallas' Erik Jonsson School of Engineering and Computer Science. He directs the Database and Data Mining Laboratory and conducts research in data mining, cybersecurity, and semantic web technologies. Research domains include: Large language models for threat detection Fairness in machine learning Vulnerability analysis in software systems Graph-based information retrieval Recent publications focus on AI security applications in transportation systems, political conflict analysis using NLP, and federated learning for IoT security. His work consistently bridges theoretical algorithms with practical cybersecurity implementations. Research grants include funding from NSF, NASA, Raytheon, Nokia, and SUN Microsystems. Teaching includes courses in Plant Breeding (PBG 450/550) and Breeding Clonal Crops (PBG 551).

W. Eric Wongمشاهده پروفایل

استاد

• Software Engineering
• Software Testing
• Software Reliability
• +۶ مورد دیگر

W. Eric Wong 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. He holds a Ph.D. in Computer Science from Purdue University (1993), following earlier degrees from Purdue and Eastern Michigan University. His research focuses on reducing software production costs while enhancing reliability, safety, and quality through program-based and architecture/design-based testing methodologies. Key areas include automated test generation, fault localization, debugging, and software safety analysis. Professional Background: Tenured Professor at UTD since 2002 Prior roles include Senior Scientist at Telcordia Technologies (1995–2002) and Consultant at Texas Instruments (2004–2005) Active in industry partnerships, such as projects with Motorola, Avaya Labs, and Raytheon Research Interests: Software Testing & Debugging Dependable Software Development Security Requirements Engineering Fault Localization Techniques Model-Based Testing Software Reliability Modeling Awards & Recognition: 2007 IEEE COMPSAC Best Paper Award 1997 NASA Quality Assurance Special Achievement Award Recipient of a $404,772 NSF grant for software safety and reliability research (2021) Professional Activities: Editorial roles for journals like Journal of Systems and Software and International Journal of Software Engineering Program Chair for ISSRE 2012, COMPSAC 2010, and multiple ACM SAC conferences Member of IEEE Reliability Society Administrative Committee (2008–2013) IBM System z Curriculum Advisory Panel member Labs & Teams: Leads the Software Engineering Group at UTD, collaborating on projects like eXVanatge (dependable software solutions) and Fault-Prone Module Identification in telecommunications systems. Engages in cross-disciplinary efforts with industry and international institutions.

Houssam Abbasمشاهده پروفایل

استادیار

• Computational Ethics
• Artificial Intelligence
• Cyber-Physical Systems
• +۳ مورد دیگر

Houssam Abbas is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. He holds a Ph.D. in Electrical Engineering from Arizona State University and has professional experience in SoC verification at Intel and postdoctoral research at the University of Pennsylvania. His work focuses on computational ethics for AI agents, design/verification of cyber-physical systems, and autonomous systems like self-driving cars and drones. Education: Ph.D., Electrical Engineering, Arizona State University (2015) M.Sc., Electrical Engineering, Arizona State University (2006) B.Eng., Computer and Communications Engineering, American University of Beirut (2004) Abbas' research integrates deontic logic for ethical obligations in AI, distributed verification techniques for autonomous systems, and fair control algorithms for aerial missions. He co-leads the F1/10 autonomous racing initiative and teaches hands-on courses on self-driving cars. Awards: 2022 NSF CAREER Award 2022 Grainger Foundation Frontiers of Engineering Symposium Participant Grants & Projects: NSF CCRI Grant for F1/10 Racecar platforms (with Penn and Clemson) FAA ASSURE project on UAV cybersecurity Lab/Teams: His work involves the Autonomous Systems Lab , focusing on ethical AI, robotics, and formal verification tools like the F1/10 platform.

Kevin W. Hamlenمشاهده پروفایل

استاد

• Cybersecurity
• Software Security
• Formal Methods
• +۶ مورد دیگر

Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.

Asta Zelenkauskaiteمشاهده پروفایل

استاد

• Social Media Research
• User-Generated Content Analysis
• Emergent Practices Online
• +۳ مورد دیگر

Asta Zelenkauskaite is a Professor of Communication and Graduate Faculty Member in the Department of Communication at Drexel University. She is affiliated with the Center for Science, Technology, and Society. Her research focuses on social media dynamics, misinformation, and digital communication practices, employing mixed-methods approaches to analyze emergent online behaviors. She holds a PhD in Mass Communication from Indiana University (2012). Education: PhD in Mass Communication, Indiana University, 2012 Research Interests: Social media research and user-generated content analysis Emergent online practices and ideological influence Disinformation, inauthentic behaviors, and post-truth challenges Macro- and micro-level studies of digital media landscapes Recent Work Trends: Dr. Zelenkauskaite’s recent publications emphasize AI’s role in content analysis, disinformation mitigation strategies, and cross-cultural climate change narratives. Her work bridges social science, information science, and linguistics to address societal challenges like vaccine hesitancy and digital misinformation. Awards/Grants: No specific awards listed, but her research has been supported by interdisciplinary grants focusing on AI ethics and digital media governance. Labs/Teams: Active in Drexel’s Center for Science, Technology, and Society, collaborating on projects addressing technology’s societal impacts. Her work often involves international partnerships, particularly in Eastern European contexts like Lithuania.

Mohamed Ibnkahlaمشاهده پروفایل

استاد

• Wireless Sensor Networks
• Internet of Things (IoT)
• Cognitive Radio Networks
• +۵ مورد دیگر

Dr. Mohamed Ibnkahla is a Full Professor and NSERC/Cisco Senior Industrial Research Chair in Sensor Networks for the Internet of Things (IoT) at Carleton University's Department of Systems and Computer Engineering. He holds a Ph.D. and HDR from the National Polytechnic Institute of Toulouse (INP), France. His research focuses on IoT, wireless sensor networks, cognitive radio systems, and adaptive signal processing, with applications in smart cities, healthcare, energy, and transportation. He has led numerous industry and government-funded projects, including the Carleton-Cisco IoT Testbed. Education: Ph.D. and HDR (INP Toulouse, 1996/1998), Engineering and MSc in Electronics/Signal Processing (INP Toulouse, 1992). He previously served at Queen’s University (2000–2015) and INP Toulouse (1996–1999). Research Interests: IoT security, energy harvesting, cognitive radio networks, smart grid communication, and machine learning for wireless systems. His work spans theoretical contributions (e.g., 5 books on signal processing and IoT) and applied innovations (e.g., sensor network architectures for environmental monitoring). He has published over 150 peer-reviewed papers, 4 books, and supervised ~40 graduate students. Awards include the INP Leopold Escande Medal (1997) and Ontario’s Prime Minister’s Research Excellence Award (2000). His lab develops solutions for IoT trust management, edge computing, and decentralized access control using blockchain. Key Projects: Cisco-funded IoT sensor networks for smart cities, NSF-funded cognitive radio projects, and collaborations on eHealth systems. His research addresses IoT security challenges in healthcare, transportation, and energy grids, emphasizing scalable, energy-efficient solutions.

Girija Chettyمشاهده پروفایل

استاد

• Multimodal Systems
• Medical Image Computing
• Computer Vision
• +۷ مورد دیگر

Girija Chetty is a Full Professor in Computing and Information Technology at the University of Canberra's School of Information Technology and Systems. She holds a PhD in Information Sciences and Engineering and has over 35 years of experience in academia and research leadership roles, including Head of Software Engineering and Program Director of ITS courses. Her research focuses on multimodal systems, medical image computing, AI, and data science. She leads a dynamic research group comprising PhD students, postdocs, and international collaborators. Education: PhD in Information Sciences (Australia, 2007), MSc and BSc in Electrical Engineering/Computer Science (India). She has held visiting roles at Deakin University and CSIRO. Research interests span computer vision, pattern recognition, and medical diagnostics, with 200+ publications in top journals/conferences. Her work addresses global challenges via AI-driven solutions in healthcare (e.g., pain assessment systems, malaria diagnostics) and sustainability (SDG impact frameworks). Projects include AI for remote ultrasound imaging and smart farming systems. She actively collaborates with industry and global research institutions. Grants/Projects: 12 funded initiatives including AI for extreme environment healthcare, malaria pathogen detection, and big data-driven population health. Awards: Senior IEEE/Australian Computer Society membership, editorial roles in IEEE/Elsevier journals. Labs/Teams: Leads a multidisciplinary research group focused on medical AI and multimodal systems.

• Artificial Intelligence
• Computer Vision
• Digital Agriculture
• +۳ مورد دیگر

Ferdous Sohel is a Professor of Information Technology at Murdoch University and inaugural lead of the Agricultural Technologies program. His research spans AI, computer vision, and digital agriculture, with applications in medical imaging and environmental monitoring. He received the Mollie Holman Doctoral Medal and Vice Chancellor's Early Career Research Award. Research Impact: Developed innovative AI models for aquaculture oxygen prediction, 3D object tracking, quantum neural networks, and prohibited item detection. His work advances precision agriculture through hyperspectral classification frameworks and irrigation decision systems. Professional Service: Associate Editor for IEEE Transactions on Multimedia and senior IEEE member. Current projects include adversarial robustness for LiDAR systems and lightweight dormitory security networks.

Jun Yanمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Smart Grids
• +۳ مورد دیگر

Jun Yan is an Associate Professor and Concordia University Research Chair in Artificial Intelligence in Cyber Security and Resilience at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on cybersecurity, smart grid systems, and AI-driven solutions for energy and communication networks. He supervises graduate students in programs such as Information Systems Security (MASc), Computer Science (MCompSc), and Information and Systems Engineering (PhD). Research Highlights : Cybersecurity of distributed energy systems, AI penetration testing frameworks, and resilient transactive energy markets. Awards : Holds a prestigious university research chair in AI-driven cybersecurity. His work integrates machine learning with domain-specific challenges in smart grids, IoT security, and multi-agent systems. Notable contributions include frameworks for detecting adversarial attacks on power systems, optimizing renewable energy integration, and developing AI tools for penetration testing. His articles reflect a strong emphasis on interdisciplinary solutions blending cybersecurity, energy systems, and advanced computing. Yan’s research also addresses policy and infrastructure challenges in sustainable energy systems, including waste management policy analysis and optimal configuration of hybrid renewable systems. He has pioneered open-source co-simulation platforms like PEMT-CoSim and Quantum-Sim for secure energy trading and quantum communication in grids. He actively engages in grant-funded projects and advises on both academic and applied aspects of cybersecurity and intelligent systems.

Md Arifuzzamanمشاهده پروفایل

استادیار

• High-Performance Networking
• Quantum Networking
• Distributed Systems
• +۳ مورد دیگر

Dr. Md Arifuzzaman is an Assistant Professor in the Department of Computer Science at Missouri University of Science and Technology (Missouri S&T). He specializes in High-Performance Systems, Quantum Networking, and Distributed Systems, focusing on optimizing large-scale system performance and scalability. His work addresses challenges in next-generation networks and storage systems, with publications in top venues like IEEE TPDS and ACM Supercomputing. Education: Ph.D. in Computer Science and Engineering, University of Nevada, Reno (2023) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2016) Research Interests: Dr. Arifuzzaman's work spans cutting-edge topics including quantum entanglement routing, reinforcement learning for network optimization, and high-speed file transfer protocols. His research emphasizes practical solutions for emerging technologies like terabit networks and quantum communication systems. Publications: Recent work focuses on quantum network protocols, machine learning-driven network probing, and storage reliability. His articles highlight advancements in both theoretical frameworks and real-world system implementations. Awards: No specific awards mentioned in the provided information. Advising/Grants: Details regarding student advising and grant activities are not explicitly stated in the text.

• Cyber Defence
• Reverse Engineering
• Malware Analysis
• +۵ مورد دیگر

Geir Olav Dyrkolbotn is an Associate Professor at NTNU's Center for Cyber and Information Security (CCIS) and a Major in the Norwegian Armed Forces, serving at the Norwegian Defence Cyber Academy (NDCA). He leads the NTNU Malware Lab and the cyber defence research group at CCIS. He holds a PhD in Information Security from Gjøvik University College and a MSc in Computer Science from NTNU. With over 25 years in the military, his work focuses on tactical communication systems, defensive cyber operations, and operational security. His research emphasizes cyber defence, reverse engineering, malware analysis, side-channel attacks, and machine learning applications. Education: PhD in Information Security, Gjøvik University College (HiG) MSc in Computer Science, NTNU Research Interests: Geir Olav's work bridges theoretical cybersecurity research and practical military applications. He explores innovative methods for hardware reverse engineering, malware detection/classification using low-level features, and forensic acquisition techniques. His contributions include analyzing USB power delivery vulnerabilities, NTFS cluster allocation behavior, and secure chip exploitation for digital forensics. Teaching: Courses include IIKG6500/IMT4213 Cyber-taktikk, IMT4214 Cyber-etterretning, IIKG6501 Cyber Intelligence, and IMT4116 Malware Analysis & Reversing. Labs & Teams: Heads the NTNU Malware Lab and leads the cyber defence research group at CCIS, collaborating on projects like the Digital Forensic Acquisition Kill Chain and hardware security vulnerability assessments.

Lesia Mitridatiمشاهده پروفایل

استادیار

• Renewable Energy Systems
• Energy Markets
• Power Systems Optimization
• +۵ مورد دیگر

Lesia Mitridati is an Assistant Professor at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). Her research focuses on optimizing energy systems, particularly in renewable energy integration, energy market design, and prosumer behavior modeling. She leads and collaborates on projects involving smart grids, distributed energy resources, and privacy-preserving market mechanisms. Her work contributes to UN Sustainable Development Goals related to affordable and clean energy. Key projects include AI-driven electricity market optimization, hydrogen-wind trading strategies, and risk-aware energy communities. She supervises multiple PhD students in areas like VPP bidding strategies and market-based heat-electricity coordination. Dr. Mitridati has published widely on energy communities, grid services, and reinforcement learning applications. Notable contributions include dynamic pricing frameworks for grid services and privacy-preserving market mechanisms. She co-organizes annual DTU summer schools on future energy systems and AI-driven optimization. Her research integrates machine learning with operational research techniques to address challenges in renewable energy integration, market design, and system resilience. Current initiatives focus on electrolyzer plant bidding strategies and feature-driven trading of renewable resources.

Rahat Masoodمشاهده پروفایل

مدرس

• Cybersecurity
• Privacy Technologies
• Authentication & Authorization
• +۷ مورد دیگر

Dr. Rahat Masood is a Lecturer at the School of Computer Science & Engineering (CSE), UNSW Sydney. Her research focuses on cybersecurity, including privacy-preserving technologies, authentication mechanisms, critical infrastructure protection, and network security analysis. She holds a PhD in Information Security and Privacy from UNSW (Data61-CSIRO, Australia), an MS in Computer and Communication Security from NUST, Pakistan, and a B.Sc. in Software Engineering from the University of Engineering & Technology, Pakistan. Her academic contributions span theoretical and applied cybersecurity domains. Dr. Masood’s educational background includes: PhD: Information Security and Privacy (UNSW, Data61-CSIRO, Australia) MS: Computer and Communication Security (NUST, Pakistan) B.Sc.: Software Engineering (University of Engineering & Technology, Pakistan) Her research interests emphasize privacy technologies, authentication systems, and securing distributed energy resources. Recent work includes developing frameworks for quantifying privacy risks and analyzing social media manipulations. She employs data-driven methodologies and machine learning to address challenges such as WiFi device tracking and federated learning security. In her publications, she highlights trends in privacy controls usability, satirical news detection using multilingual models, and threat modeling for critical infrastructure. These studies underscore her commitment to bridging cybersecurity theory with real-world applications. No scientific awards are mentioned in the provided texts. Her teaching and supervision roles at UNSW are active, though specific student advisees or grant details are not listed. She is affiliated with Data61-CSIRO through her PhD and contributes to interdisciplinary cybersecurity efforts within CSE.