جستجوی استاد راهنمای دانشگاهی

• Automatic Control
• Robotics
• Critical Infrastructure Protection
• +۴ مورد دیگر

Professor Stefano Panzieri is a Full Professor in the Department of Civil, Computer and Aeronautical Engineering at Roma Tre University. He has held academic positions since 1996, including Associate Professor (2003–present) and Assistant Professor (1996–2003). His research focuses on automatic control, robotics, critical infrastructure protection, and cyber-physical systems. He coordinates the Ph.D. program in Computer Science and Automation and leads initiatives like the CISIApro model for infrastructure resilience. Panzieri directs the Robotics Laboratory, MCIPlab, and Automation Lab, contributing to 10 Ph.D. students' supervision. His work spans distributed control, sensor networks, and smart grid technologies, with over 180 publications and projects funded by the EU and Italian Ministry of Economic Development. Key contributions include interlaced Kalman filters and anomaly detection frameworks. Research Interests: Automatic Control: Nonlinear techniques, iterative learning control, and MPC. Robotics: Mobile robotics, sensor fusion, and navigation. Critical Infrastructure: Protection strategies, cascading effects modeling, and decision support systems. Cybersecurity: False data injection defense, game-theoretic models, and resilient networks. Recent Articles Trends: Focus on distributed state estimation, cyber-physical system resilience, and adaptive filtering techniques. Recent work addresses adversarial attacks, multirate systems, and pandemic impact modeling. Grants & Projects: SMART Environments (2015): Smart city and infrastructure development. ATENA (2017): Secure IACS using Software-Defined Networking. URANIUM (2014): Resource allocation and game theory for critical infrastructure. Labs & Teams: Leads MCIPlab (Critical Infrastructure Protection) and the Automation Lab, collaborating on robotics and smart grid technologies.

Christodoulopoulos Konstantinosمشاهده پروفایل

استادیار

• Optical Communications
• Networking
• Machine Learning
• +۷ مورد دیگر

Christodoulopoulos Konstantinos is an Assistant Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on optical communications, networking, and machine learning applications in network optimization. He has contributed to advancements in resource allocation, quality of transmission (QoT), and cybersecurity through quantum key distribution (QKD). His work includes field demonstrations of encrypted networks, techno-economic studies in metro-core systems, and scalable industrial network solutions. Education details are not explicitly provided in the text, but his academic role suggests a Ph.D. in a related field. Key research interests span optical network design, SDN-enabled architectures, and hybrid optical-electrical data centers (e.g., NEPHELE projects). He has published extensively on topics like slotted optical datacenter networks, machine learning for QoT estimation, and marginless optical network operations. Notable contributions include experimental demonstrations of disaggregated white-box networks, real-time SDN control frameworks, and collaborative projects with institutions like the University of Patras. His work emphasizes practical implementations, such as industrial-grade PONs and fault localization in optical networks.

Yu Liمشاهده پروفایل

پژوهشگر

• Robotics
• Cyber-Physical Systems
• Machine Learning
• +۳ مورد دیگر

Yu Li is a Researcher affiliated with the Physics Institute at the University of Stuttgart . Their work focuses on advancing robotics and cyber-physical systems , with a particular emphasis on anomaly detection, risk assessment, and fault tolerance in autonomous systems. They specialize in applying machine learning techniques like MLSTM-FCN and transformers to enhance system reliability. Research interests include Robotic manipulation under uncertainty ROS-based fault injection frameworks Hybrid probabilistic risk modeling Real-time anomaly detection in industrial systems Recent work emphasizes automated risk assessment for software-defined robotic systems, leveraging SysML V2 models and continuous monitoring. Their publications span robotics, AI, and safety-critical system design, reflecting interdisciplinary collaboration across engineering and computer science domains.

Mohammed Amine Togouمشاهده پروفایل

استادیار

• 5G/6G Networks
• Software-Defined Networking
• Blockchain Applications
• +۳ مورد دیگر

Mohammed Amine Togou is an Assistant Professor in the School of Computing within Dublin City University's Faculty of Engineering and Computing. His research specializes in performance optimization and protocol design for next-generation networks including 5G/6G systems, SDN/NFV architectures, and blockchain-enabled solutions. With PhD in Computer Science from University of Montreal and MSc in Computer Networks from Al Akhawayn University, he has published over 40 peer-reviewed papers. Current research develops machine learning solutions for network management challenges including: interference mitigation in O-RAN architectures, adaptive streaming for immersive media, and blockchain-based network slicing. He serves as guest editor for Electronics journal's special issue on 5G Technology and IoT, and supervises PhD students in network optimization and distributed computing. Teaching responsibilities include distributed systems and network security courses, with pedagogical research on technology-enhanced learning methods in computing education.

Tim Curryمشاهده پروفایل

استادیار

• Optimization
• Cybersecurity
• Computer Science
• +۲ مورد دیگر

Tim Curry is an Assistant Professor at the University of Connecticut (Storrs Campus). His research focuses on Optimization and Cybersecurity , particularly in network systems and computational methods. Recent research trends include: Developing hybrid optimization frameworks for secure virtualized networks Advancing constraint programming applications in cybersecurity Designing dynamic configuration algorithms for Software-Defined Networks (SDN) Integrating attack graph analysis with network defense strategies His work intersects Computer Science , Network Engineering , and Operations Research , with publications emphasizing formal verification, algorithm design, and security automation in networked systems.

• Software Defined Radio
• AI/ML for Wireless Communications
• Cyber Security
• +۳ مورد دیگر

Ruolin Zhou is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth, part of the College of Engineering. She joined UMass Dartmouth in 2018 after serving as a tenured Associate Professor at Western New England University from 2012 to 2018. Her research focuses on software-defined radio (SDR), AI/ML-driven wireless communications, spectrum sensing, cyber & electromagnetic spectrum security, and hardware security. Her work has been supported by grants from NSF, ONR, AFRL, ARL, and industry partners like Lockheed Martin. Dr. Zhou holds a PhD in Engineering from Wright State University (2012), an MS in Electrical Engineering (2007), and a BS in Electrical Engineering from Dalian Jiaotong University (2003). She teaches courses including Foundations of Cybersecurity, Digital Logic Design, and Software-Defined Radio. Her research has led to innovations in FPGA-accelerated deep learning architectures, real-time spectrum monitoring, and secure communication systems. Her contributions have been recognized with awards including the 2024 IEEE Region 1 Outstanding Teaching Award, ONR Summer Faculty Research Fellowships (2022-2023), and Best Demo Awards at GLOBECOM 2010. She actively serves in IEEE roles, including Vice President for Technical Activities within the IEEE Reliability Society (2025) and steering committee memberships in IEEE Future Networks and IoT Technical Communities.

Chatchai Khunboaمشاهده پروفایل

استاد مهمان

• Wireless Sensor Networks
• Internet of Things
• Software Defined Networks
• +۳ مورد دیگر

Chatchai Khunboa is a Visiting Professor at the Shiley School of Engineering, University of Portland, and currently holds the position of Associate Professor in the Department of Computer Engineering at Khon Kaen University, Thailand. He is a Fulbright Scholar-in-Residence, focusing on sharing his expertise in IoT and encouraging students to engage with contemporary technological advancements. Dr. Khunboa's educational background includes a Bachelor of Electrical Engineering from Khon Kaen University (1992), a Master of Science in Telecommunications from the University of Pittsburgh (2000), and a Ph.D. in Information Technology from George Mason University (2005). His research interests are centered on Wireless Sensor Networks (WSN), Internet of Things (IoT), and Software Defined Networks (SDN). He actively explores applications and challenges in these fields, emphasizing their relevance in modern technological ecosystems. Fulbright Scholar-in-Residence His current Fulbright grant supports collaborative research and educational initiatives, particularly in highlighting the importance of IoT in contemporary environments. He has no listed advisees or grants beyond this residency program.

Abdussalam Salamaمشاهده پروفایل

مدرس

• Network Security
• IoT Security
• Cloud Security
• +۴ مورد دیگر

Dr. Abdussalam Salama is a Lecturer in Computer Networks and Cybersecurity at Sheffield Hallam University's School of Computing and Digital Technologies. He holds a PhD in Computer and Communication Networks (2020) and industry certifications such as CCNP and CCSP. His expertise spans network security, IoT security, cloud security, and Quality of Service (QoS) in wireless networks. He actively contributes to EU-funded projects like Digital Innovation for Growth (DIfG), focusing on SME digital transformation. Education: PhD in Computer and Communication Networks, Sheffield Hallam University (2020) MSc Telecommunication and Electronic Engineering, Sheffield Hallam University (2015) BSc Electrical and Electronic Engineering, University of Tripoli (2001) Research Interests: Network security, IoT security, cloud security, QoS/QoE optimization, Software-Defined Networks (SDN), and eHealth applications. He leads projects on SASE/SD-WAN for SMEs and adaptive eHealth systems. Collaborations: EU-funded Digital Innovation for Growth (DIfG) project Rotherham Foundation Trust - NHS for eHealth applications Awards: Fellow of the Higher Education Academy (FHEA) Member of the Institute of Engineering and Technology (MIET) Grants/Postgraduate Supervision: Supervises doctoral researchers in network security, cloud computing, and SASE architectures. Manages projects funded by EU initiatives and industry partnerships. Labs/Teams: Member of RIKE and ERCIF groups, collaborating on applied research and industry partnerships.

Quamar Niyazمشاهده پروفایل

استادیار

• Cybersecurity
• Computer Networks
• Applied Machine Learning
• +۳ مورد دیگر

Dr. Quamar Niyaz is an Assistant Professor in the Department of Electrical and Computer Engineering at Purdue University Northwest (PNW), located in Hammond, Indiana. He is affiliated with the College of Engineering and Sciences, focusing on cybersecurity, computer networks, and applied machine learning. His work emphasizes both technical innovation and educational tool development, including testbeds for hands-on learning. Dr. Niyaz holds a Ph.D. in Computer Science & Engineering from The University of Toledo, an M.S. and B.S. in Computer Engineering from Aligarh Muslim University, India. His research spans intrusion detection systems, malware analysis, and cybersecurity education frameworks, with a focus on making cybersecurity accessible to high-school and university students through interactive tools like visualization aids and smartphone-based learning modules. His research interests include network security, machine learning applications, and cybersecurity pedagogy. Notable projects include developing NATICUSdroid (Android malware detection), Permission-Educator (mobile permission education app), and PortableVN (network security testbeds). He also explores the societal impact of cybersecurity education on career choices and student attitudes. Teaching courses in C++/Matlab, software engineering, and computer networks, Dr. Niyaz emphasizes practical skills and ethical considerations in technology. His recent work highlights trends in hybrid cybersecurity education models, augmented reality for engineering training, and combating modern threats like GPS spoofing and UAV jamming attacks. Dr. Niyaz’s contributions bridge academia and industry through collaborative research on secure software frameworks, AR/ML integration, and autonomous systems security. His efforts aim to prepare students for challenges in a rapidly evolving technological landscape while addressing global cybersecurity needs.

Percy Shuo Liangمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +۵ مورد دیگر

Percy Shuo Liang is an Associate Professor of Computer Science and Courtesy Associate Professor of Statistics at Stanford University. He directs the Center for Research on Foundation Models (CRFM) and is affiliated with Human-Centered Artificial Intelligence (HAI), the Artificial Intelligence Lab, and the Natural Language Processing Group. His research focuses on foundational aspects of machine learning, natural language processing, and reproducible research methodologies. He co-developed CodaLab Worksheets, a platform for experiment reproducibility, and leads the Marin community for open foundation model development. Education: B.S. (2004) and MEng (2005) in Electrical Engineering and Computer Science from MIT, advised by Michael Collins. Ph.D. (2011) in Computer Science from Berkeley under Michael Jordan and Dan Klein. Postdoctoral researcher at Google (2012). Research interests include foundation models, copyright challenges in AI, data weighting strategies, model interpretability, and ethical AI. Over 30 students and postdocs have been advised, many now holding prestigious academic and industry roles. Awards include the Presidential Early Career Award (2019), Sloan Fellowship (2015), and ACM ICPC World Finals 2nd place (2002). Labs/Teams: CRFM, HAI, AI Lab, NLP Group, Machine Learning Group. Notable contributions include CodaLab Worksheets and Marin platform. Active in programming contests and piano competitions (KDFC Classical Star Search winner, 2008).

Konstanty Bialkowskiمشاهده پروفایل

دانشیار

• Wireless Communication
• Radar Systems
• Signal Processing
• +۴ مورد دیگر

Associate Professor Konstanty Bialkowski is affiliated with the School of Electrical Engineering and Computer Science at The University of Queensland (UQ). His research focuses on communication systems, passive radar, and signal processing, particularly leveraging software-defined radios (SDRs) for applications in wireless communication, biomedical imaging, and sensor integration. Key contributions include sensor architectures for multi-modal data collection (RF, vibration, acoustic), passive radar algorithms enabling 3D target localization, and low-cost biomedical imaging devices. Education: Bachelor of Science, University of Queensland Bachelor (Honours) of Engineering, University of Queensland Doctor of Philosophy, University of Queensland Research Interests: Dr. Bialkowski’s work spans communication systems , passive radar , biomedical imaging , and antenna design . He pioneers the use of SDRs for high-reliability communication, wireless sensing, and applications like stroke detection via microwave tomography. His team develops wearable electromagnetic imaging systems and low-cost clinical scanners for acute stroke diagnosis. Key Projects: Electromagnetic brain scanner prototypes for clinical use Passive radar systems for low-Doppler target detection Flexible antenna arrays for wearable medical diagnostics Lab & Team: Collaborates with interdisciplinary teams on projects involving electromagnetic imaging, sensor networks, and biomedical engineering. Notable collaborators include Prof. Amin Abbosh and Dr. Lei Guo.

Félix do Carmoمشاهده پروفایل

مدرس ارشد

• Translation Technologies
• Machine Translation
• Translation Process Research
• +۳ مورد دیگر

Dr. Félix do Carmo is a Senior Lecturer in Translation and Natural Language Processing at the University of Surrey's Centre for Translation Studies, part of the School of Arts, Humanities and Creative Industries. He holds a PhD from the University of Porto and has over two decades of industry experience as a translator, reviser, and translation company owner. His research focuses on automation of translation processes, post-editing of machine translation, and human-computer interaction in translation workflows. Key projects include the KAITER initiative exploring interactive translation editing systems and the ADAPT Centre post-doctoral work on translation technology. Teaching responsibilities include leading modules on 'Translation as Human-Computer Interaction' and 'Professional Translation Practice II'. He actively collaborates with industry partners and has published extensively on machine translation evaluation, emotion translation challenges, and translation process research. His work bridges theoretical translation studies with practical applications of AI and NLP technologies. Research highlights include studies on MT quality estimation for user-generated content, emotion-loaded text translation challenges, and the ethical implications of translation workflow automation. He co-authored the influential book 'Conducting Research in Translation Technologies' and has contributed to international conferences such as the Machine Translation Summit. Current projects emphasize improving translator-machine collaboration through intelligent tools and exploring GenAI integration in translation education. Dr. do Carmo's academic affiliations extend to the Surrey Institute for People-Centred Artificial Intelligence (PAI) and he maintains strong connections with the translation industry through consultancy and conference organizing. His work consistently emphasizes real-world applicability of research findings, fostering innovation while addressing labor and ethical considerations in an increasingly automated translation landscape.

Andrew Gilbertمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Generative Modelling
• +۶ مورد دیگر

Dr. Andrew Gilbert is an Associate Professor in Machine Learning at the University of Surrey, co-leading the Centre for Creative Arts and Technologies (C-CATS). His work bridges computer vision, generative AI, and creative industries, focusing on interpretable and human-centered systems. He leads a multidisciplinary team of 17 PhD students and has published over 100 papers in top venues like CVPR, ECCV, and BMVC. Education & Research: Gilbert earned his PhD in Computer Vision from the University of Surrey (2008) and has pioneered advancements in video understanding, style modeling, and AI-driven media production. His research integrates technical innovation with creative applications, such as AI-generated narratives and blockchain-based content rights. Research Trends: Recent work emphasizes long-term video analysis (DANTE-AD), motion-focused self-supervision (MOFO), and human-AI benchmarking (Human vs. Machine Minds). His projects often involve industry partnerships to address real-world challenges in media production and digital arts. Achievements: Best Paper at CVMP 2023, active BMVA committee member, and contributor to standards in explainable AI. His lab’s annual Gilbertine Weekend Away fosters collaborative research culture. Advising: Supervised 14 PhD completions, with ongoing projects in video diffusion models, decentralized content rights, and multimodal scene understanding. Seeks exceptional candidates for funded UK-based PhD opportunities. Key Labs: C-CATS lab explores AI’s creative applications, while his group develops tools for style transfer (NeAT), action recognition, and 3D performance capture.

Azer Bestavrosمشاهده پروفایل

استاد

• Networking
• Distributed Systems
• Cloud Computing
• +۶ مورد دیگر

Azer Bestavros is a Professor and Associate Provost for Computing & Data Sciences at Boston University, affiliated with the Department of Computer Science within the Arts & Sciences School. He joined BU in 1991 after earning his PhD from Harvard. His research focuses on networking, distributed systems, cloud computing, and cybersecurity, with notable contributions to web content distribution models, cloud resource management, and privacy-preserving analytics. He led the establishment of the BU Hariri Institute for Computing and the Open Cloud Exchange initiative to advance cloud marketplaces. Education: PhD in Computer Science from Harvard University. Research Interests: His work integrates technical and policy dimensions, addressing challenges in secure multiparty computation, formal methods for network verification, and interdisciplinary applications of computing. Recent projects include frameworks for privacy-preserving analytics and mechanisms for efficient cloud resource allocation. Grants & Advising: Advised 16 PhD students, contributed to 6 patents, and spun off 3 startups. His research has yielded over 13,000 citations and informs policy through initiatives like the Cloud Computing Caucus. Labs & Teams: Spearheaded the Hariri Institute’s cloud computing, big data, and cybersecurity programs. Currently oversees the Faculty of Computing & Data Sciences, fostering interdisciplinary collaboration across BU.

Rajan Shankaranمشاهده پروفایل

مدرس ارشد

• Network Security
• Mobile Communication Protocols
• Internet of Things
• +۴ مورد دیگر

Rajan Shankaran is a Senior Lecturer at Macquarie University's School of Computing, part of the Faculty of Science and Engineering. He serves as Course Director for postgraduate programs in Networking and IoT, and chairs the IEEE VTS NSW Chapter. His roles include membership in the University Academic Senate Curriculum Subcommittee and representation on the FSE Faculty Board. Education: MBA (MIS) from Maastricht School of Management; M.Sc. (Hons.) and Ph.D. in Network Communications and Security from University of Western Sydney. Research focuses on Network Security, Mobile Communication Protocols, IoT, Network-on-Chip, and Medical Implant Security. He has led projects like 'Digital Health Records Storage and Analysis for Global Patients' and organized IEEE events such as NOMS 2017. Notable awards include IEEE Senior Member status. Recent work includes publications on wireless network security, optimization algorithms, and IoT-enabled healthcare systems. He advises on over 70 research outputs and has contributed to 4 major projects addressing cybersecurity and network efficiency. Labs/Teams: Active in the Future Communications Research Centre, collaborating on 5G/IoT security and edge computing applications.