جست‌وجوی استاد و پژوهشگر

Maher Salemمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Blockchain Technology
• Machine Learning
• +۴ مورد دیگر

Dr. Maher Salem is a Senior Lecturer (Assistant Professor) in Cybersecurity at King's College London, affiliated with the Department of Informatics within the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD in Security Engineering from Kassel University (2014) and is a HEA Fellow. His research focuses on intrusion detection systems, cyber threat intelligence, machine learning-based security solutions, and blockchain applications in cybersecurity and finance. He has 15+ years of industrial experience with firms like AUDI AG and E-Plus, and has secured funding from the German Federal Ministry of Education and Research (BMBF). Dr. Salem leads the Computing Education Research Centre (CERC) at King's, advancing cybersecurity education through pedagogical tools and PhD supervision. His work bridges academia and industry, addressing challenges in online learning equity, cloud security, and automotive/IoT security via blockchain. Notable contributions include frameworks for threat intelligence detection, privacy-preserving cloud search, and decentralized transportation authentication systems. Education: PhD in Security Engineering (Kassel University, 2014) Affiliations: Former roles at Higher Colleges of Technology (UAE) and Fulda University of Applied Sciences (Germany) Labs/Teams: Security Hub (King's College), CERC His awards include the Emirates Skills First Rank Award (2017) and HEA Fellowship (2019). Research outputs span 25+ peer-reviewed articles, focusing on AI-driven penetration testing, blockchain applications, and cybersecurity education innovations. He collaborates globally on projects like dynamic cloud congestion management and APT detection frameworks.

• Data Mining
• Web Mining
• Recommendation Systems
• +۱۲ مورد دیگر

Prof. Şule Öğüdücü is a full-time Professor in the Department of Artificial Intelligence and Data Engineering at Istanbul Technical University (ITU), Faculty of Computer and Informatics. She has been serving as the Department Chair since 2019 and has held various administrative roles including Associate Dean (2012–2015) and Faculty Board Member. Her academic journey began with a B.Sc. in Electronics and Communication Engineering from ITU, followed by an M.Sc. in Biomedical Engineering from Boğaziçi University, and a Ph.D. in Computer Engineering from ITU. During her doctoral studies, she was a Research Associate at the University of Waterloo’s Database Laboratory (2001–2003), supported by NSERC and Tinçel Foundation grants. B.Sc., Electronics and Communication Engineering, Istanbul Technical University, 1987–1991 M.Sc., Biomedical Engineering, Boğaziçi University, 1991–1995 Ph.D., Computer Engineering, Istanbul Technical University, 1999–2003 Her research is centered on data mining, web mining, recommendation systems, social network analysis, big data, community detection, and forecasting applications in finance and demand. She is recognized internationally, ranking 27th in Google Scholar in recommendation systems and 1st in Turkey. Her recent work emphasizes AI-driven solutions in network security, explainable AI, and industrial applications such as oil industry flash point prediction and e-commerce demand forecasting. The analysis of her recent publications (2022–2025) reveals a strong trend toward integrating deep learning and graph neural networks (GNNs) into recommendation and network anomaly detection systems. There is a growing focus on explainability (XAI), semi-supervised learning, and real-world applications in critical infrastructure (e.g., backbone networks, traffic, oil industry). Her work bridges theoretical AI advancements with practical implementations in cybersecurity, smart cities, and industrial automation. Her scientific honors include: Siemens Excellence Award, 2004 TÜBİTAK Threshold Award, 2024 Prof. Öğüdücü has led numerous research projects, including TÜBİTAK-funded initiatives and ITU Research Fund grants. She is the Principal Investigator (PI) of multiple ongoing projects such as 'Explainable AI Methods for Earthquake Prediction,' 'AI-Based Demand Forecasting for the Fashion Industry,' and 'Black Hole Anomaly Detection in Backbone Networks.' She also engages in sectoral collaborations with companies like Ericsson, KariyerNet, and IDEA Technology, providing academic consultancy in dynamic pricing, financial analysis, and real-time system scaling. She has supervised 33 academic works, reflecting her active role in mentoring students. Additionally, she founded the IEEE Turkey WIE Affinity Group in 2010, contributing significantly to the promotion of women in engineering. She leads research teams working on AI and data engineering applications, particularly in network security, recommendation systems, and industrial AI. Her labs focus on developing benchmark datasets (e.g., IBB Traffic Graph Data), predictive models, and explainable AI frameworks. Current teams are engaged in projects funded by TÜBİTAK and industry partners, emphasizing real-time, scalable, and interpretable AI solutions.

Gary B Lamontمشاهده پروفایل

استاد

• Evolutionary Algorithms
• Multi-Objective Optimization
• Computational Intelligence
• +۷ مورد دیگر

Dr. Gary B. Lamont is a Professor in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), part of Air University. His work bridges computational intelligence, evolutionary algorithms, and defense systems engineering, with extensive applications in aerospace, cybersecurity, and autonomous systems. Ph.D., University of Minnesota Institute of Technology, 1970 Master of Science in Electrical Engineering, University of Minnesota Institute of Technology, 1967 Bachelor of Physics, University of Minnesota Institute of Technology, 1961 Dr. Lamont’s research centers on multi-objective evolutionary algorithms (MOEAs) , with applications in UAV swarm mission planning, network intrusion detection, image processing, and protein structure prediction. He has pioneered the use of evolutionary computation in military and defense contexts, including radar waveform design, satellite constellation planning, and autonomous agent behavior generation. His work often integrates swarm intelligence, artificial immune systems, and distributed optimization techniques. The recent publications highlight a strong trend toward military and defense applications of computational intelligence, particularly in electronic warfare, space surveillance, and cyber defense. His work frequently employs multi-objective optimization to balance competing constraints in real-world systems such as radar, UAV swarms, and network security architectures. Image processing and signal transformation using evolved algorithms also remain active areas, especially for defense imaging and compression. IEEE Fritz Russ Bio-Engineering Award, 2008 IEEE Senior Life Member, 2004 Eta Kappa Nu AFIT Teacher of the Year, 2002 WPAFB Professional Employee of the Year, 1981 Best Presentation Award, Institute of Navigation, 2008 BEST PAPER AWARD, Gameon North America '09 Best Paper Award Nominee, IEEE SSCI 2007 Dr. Lamont has advised numerous graduate students, including Jeremy Stringer, Mark Kleeman, and Dustin Nowak, many of whom have co-authored significant publications with him. His research has been supported by the U.S. Air Force and other defense agencies, enabling high-impact work in autonomous systems, network security, and optimization under uncertainty. He has led projects involving multi-agent systems, self-organized swarms, and parallel evolutionary algorithms, often in collaboration with institutions like Wright-Patterson Air Force Base. His research group at AFIT operates at the intersection of computational intelligence and defense engineering, focusing on self-organized UAV swarms , evolutionary intrusion detection systems , and adaptive signal processing . The team utilizes high-performance computing environments and simulation platforms like Swarmfare to test swarm behavior and mission planning algorithms. The lab emphasizes software engineering discipline in AI systems, as seen in tools like jREMISA, and integrates biological metaphors such as immune systems and genetic algorithms into robust cyber defense frameworks.

Paul Byrneمشاهده پروفایل

دانشیار

• Comparative Planetary Geology
• Planetary Science
• Venus Geology
• +۵ مورد دیگر

Paul Byrne is an Associate Professor in the Department of Earth, Environmental, and Planetary Sciences at Washington University in St. Louis. He is affiliated with the McDonnell Center for the Space Sciences and the Remote Sensing Laboratory. His work focuses on comparative planetary geology, analyzing planetary surfaces and interiors to understand geological systems across the solar system and beyond. Byrne holds a BA and PhD in geology and planetary geology from Trinity College Dublin. He previously served as an assistant and associate professor at North Carolina State University, and held postdoctoral fellowships at the Carnegie Institution for Science and the Lunar and Planetary Institute. His research integrates remote sensing data, numerical models, and Earth-based fieldwork to study phenomena like Venusian volcanism, Martian tectonics, and Mercury's contraction. Key interests include planetary surface evolution, extraterrestrial resource potential, and exoplanet geology. Notable recent studies address Venus' geological activity, Mercury's crustal dynamics, and mission concepts for planetary exploration. Byrne has contributed to over 100 peer-reviewed articles, emphasizing Venus surface imaging techniques, Mars fault analysis, and Mercury's geological history. His work often bridges planetary geology with astrobiology and space resource utilization.

Dragos Truscanمشاهده پروفایل

استاد

• Software Testing
• Model-Based Testing
• AI in Test Automation
• +۷ مورد دیگر

Prof. Dragos Truscan is a Professor of Computer Science at the Faculty of Natural Sciences and Engineering within Åbo Akademi University , focusing on Information Technology and Mission Critical Software Systems . Research interests include validation and verification , automated test generation using model-based technology and AI , test left-shifting , and runtime monitoring of industrial software systems Active in Security Requirements Engineering , DevOps , Deep Learning , and Software Component analysis Recent work explores: 2025 - Reinforcement learning for security testing and visual fault localization 2024 - Explainability in network attack detection and hyperparameter optimization 2023-2024 - Model-based requirements engineering in large collaborative projects Scientific Recognition Best Paper Award (2024) Best Paper Award (2013) Academic Activities Organizing member of IEEE International Conference on Software Services Engineering (2025) Hosted scholars like Victoria Zsók and Dr. Dumitru Iulian Nastac

John Zimmermanمشاهده پروفایل

دانشیار

• Value of Digital Things
• Service Design and Social Computing
• Ubiquitous/Mobile Computing
• +۳ مورد دیگر

John Zimmerman serves as Associate Professor with a joint appointment between Carnegie Mellon University's School of Design and Human Computer Interaction Institute, teaching interaction design studios and mobile service innovation courses while leading impactful research across four core domains. His educational foundation includes an MDes in Interaction Design from CMU's School of Design, building on prior industry experience as Senior Researcher at Philips Electronics where he designed interactive television and home technologies. Zimmerman's research investigates why digital possessions are often undervalued compared to physical objects through projects like interactive teen bedrooms and memory-postcard services. His service design work engages citizens in public planning via social computing, notably a crowdsourced transit system earning FCC and ITS America awards with 150,000+ location traces. In ubiquitous computing, he develops smartphone systems for family routines and mental health monitoring, while his Research through Design methodology explores speculative futures through practice, culminating in the co-authored book Design Research Through Practice . Analysis of his 15 most recent publications (2024-2025) reveals a strategic pivot toward AI ethics and public-sector applications, with 60% focusing on responsible AI development, equity in government systems, and educational technology, while maintaining foundational work in service design and digital possessions. His scientific recognition includes: FCC award for crowdsourced transit innovation Intelligent Transportation Society of America award for real-time transit system Zimmerman secures research funding for projects spanning public technology, educational tools, and AI ethics, though specific grants aren't detailed in source materials. He mentors MDes students at CMU's School of Design, emphasizing practical design skills and ethical technology development as reflected in his teaching of interaction design studios and mobile service courses. His collaborative work extends through CMU's interdisciplinary ecosystem and public-sector partnerships, particularly evident in transit system development with local transportation authorities and classroom analytics projects with K-12 educators.

SANDRA MARIA GOMEZ CANAVALمشاهده پروفایل

دانشیار

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

Sandra María Gómez Canaval is an Associate Professor at the Universidad Politécnica de Madrid , affiliated with the Department of Computer Systems . Her research focuses on: Artificial Intelligence and Machine Learning Bio-Inspired Computational Models Distributed and High-Performance Computing Generative Models and Network Security Data Mining and Time Series Forecasting Her recent work explores machine learning applications for: Network traffic prediction Harmful algal bloom forecasting Energy-efficient deep neural networks Automated guided vehicle control Cryptomining attack detection Her publications highlight expertise in Generative Adversarial Networks (GANs), cloud-based security, and Industry 4.0 systems. She actively contributes to: Data augmentation techniques Parallel computing architectures Network digital twin development