Find Academic Supervisors

Carlo KoppView profile

Lecturer

• Modelling Deception
• Cognitive Cycle Modelling
• Ad Hoc Networks
• +9 more

Carlo Kopp is a Lecturer in the Department of Software Systems & Cybersecurity at Monash University's Faculty of Information Technology. His research focuses on information-theoretic models of deception in social and biological systems, perceptual errors, cognitive cycles, and distributed computing. He has held adjunct roles at Monash Asia Institute (2005–2010) and ADFA@UNSW (2004), and serves as Editor-in-Chief and Research Lead at Air Power Australia since 2004. He advises parliamentary committees and media on issues like high-power electromagnetic events (e.g., NCIS LA episode 3.11). Education: PhD in Computer Science, Monash University (2000) MSc (Research) in Computer Science, Monash University (1996) BEng (Hons) in Electrical Engineering, University of Western Australia (1984) Research Interests: Modelling deception in complex systems, ad hoc networks, radar propagation, and strategic military analysis. He explores topics like disinformation effects, renewable energy in cloud computing, and cognitive biases. Awards: Best Paper Award (2002) Outstanding Teaching Award (2015) Australian Industry Certificate Award (2010) Teaching: Chief Examiner and Lecturer for courses including Network Architecture (FIT2020), Distributed Computing (FIT3142), and Advanced Network Design (FIT5011). Previously led curriculum design for Computer Networks and Telecommunications Management units. Industry Experience: 20+ years as a software/hardware engineer, project manager, and consultant in embedded systems, operating systems, and strategic technology planning. Managed ISO9001 accreditation for an Australian computer manufacturer. Community Work: Advised US Congressional bodies and testified before Australian parliamentary committees on disinformation and cybersecurity. Serves as a Fellow of the Lean Systems Society and Associate Fellow of AIAA.

• Software-Defined Networking
• Cloud Computing
• Network Security
• +4 more

Ameen Chilwan serves as an Assistant Professor in the Department of Information Security and Communication Technology within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). His office is located at Elektro A, A-262, Gløshaugen, with contact information including email ameen.chilwan@ntnu.no and phone +4746355118. Dr. Chilwan's research spans multiple domains in network technologies with particular expertise in software-defined networking (SDN), cloud computing infrastructure, and real-time internet services. His work demonstrates consistent evolution from foundational network architecture research toward contemporary applications in 5G edge clouds and smart grid systems. The interdisciplinary nature of his research bridges computer networking with energy systems and underwater communications. Analysis of his publication record from 2011-2024 reveals a clear progression from theoretical network modeling toward practical implementation challenges. Early work focused on OpenFlow-based SDN architectures (2012-2015), followed by expansion into cloud service availability (2011-2012), then underwater sensor networks (2014), and most recently machine learning applications for smart grids (2024). This trajectory demonstrates both technical depth in networking fundamentals and increasing breadth across application domains. Dr. Chilwan teaches courses including DCSG2001 - Sammenkoblede nettverk og nettverkssikkerhet, TTM4180 - Nettverkshåndtering, and DCSG1006 - Datakommunikasjon og nettverk, reflecting his expertise in network security, management, and communications. His academic service includes outreach activities through conference presentations and academic lectures at international venues including EUNICE, FIT, and ICCCN.

• Computer Networking
• Network Performance Analysis
• Stochastic Network Calculus
• +5 more

Yuming Jiang is a full Professor at NTNU's Department of Information Security and Communication Technology (Faculty of Information Technology and Electrical Engineering). He holds a BSc from Peking University, MEng from Beijing Institute of Technology, and PhD from National University of Singapore (NUS). His research focuses on network performance analysis, stochastic network calculus, and quality of service guarantees in communication networks. He authored the seminal book Stochastic Network Calculus (Springer, 2008). He has held roles including Study Programme Leader for NTNU's Master of Science in Digital Infrastructure and Cyber Security, and is a member of the Norwegian Academy of Technological Sciences (NTVA). Prof. Jiang has extensive experience in academic leadership, serving as conference chair (e.g., IFIP Networking 2014, IEEE Vehicular Technology Conference 2008) and committee roles in major networking communities. His work spans theoretical advancements (e.g., stochastic network calculus properties) and practical applications (e.g., UAV-assisted IoT security, NFV reliability). Key research contributions include modeling wireless channel capacity, analyzing time-sensitive networks (TSN/DetNet), and developing security frameworks for emerging communication systems. His publications (over 150 papers) bridge theoretical foundations and real-world network challenges in areas like energy-efficient communication, cyber-physical systems, and blockchain performance.

• Cybersecurity
• Smart Grids
• Critical Infrastructure Protection
• +6 more

Stephen Dirk Bjørn Wolthusen is a Professor in the Department of Information Security and Communication Technology at NTNU (Norwegian University of Science and Technology) located in Gjøvik. His research focuses on cybersecurity, smart grids, critical infrastructure protection, and adversarial attack analysis in cyber-physical systems. He has published extensively in top-tier venues like IEEE Transactions, LNCS, and IFIP series. Wolthusen's work spans theoretical frameworks (e.g., π-calculus modeling, queueing networks) and applied domains such as SCADA systems, smart grid resilience, and IoT security. He has collaborated on projects involving tactical service-oriented architectures, software-defined networks, and privacy-preserving healthcare systems. His recent research emphasizes adversary-resistant topology design, dynamic policy enforcement, and resilience metrics for critical infrastructure. Key contributions include frameworks for threat modeling in industrial control systems, formal verification of CPS protocols, and analysis of adversarial attacks on communication protocols like IEC 61850. His work bridges theoretical computer science with practical engineering challenges in cybersecurity and networked systems.

Kamran EntesariView profile

Professor

• Radio Frequency Integrated Circuits
• RF Photonics
• Microwave Sensing Systems
• +5 more

Kamran Entesari is a Professor of Electrical and Computer Engineering at Texas A&M University, holding the Texas Instruments Engineering Professorship. His research focuses on RF/microwave/mm-wave integrated circuits, integrated RF photonics, and biochemical sensing systems. He leads projects in silicon photonics, millimeter-wave communication, and dielectric spectroscopy. Education: Ph.D., Electrical Engineering, University of Michigan, Ann Arbor (2005) M.S., Electrical Engineering, Tehran Polytechnic University (1999) B.S., Sharif University of Technology (1995) Research Interests: RFIC and mm-wave systems for 5G and beyond Photonic-integrated circuits for next-gen communication Biomedical sensing via microwave dielectric spectroscopy Low-power, high-linearity transceiver architectures His work bridges silicon photonics with traditional RF systems to enable high-speed, low-power solutions. Recent Research Trends: Recent publications emphasize hybrid CMOS-silicon photonics for mm-wave front-ends, full-duplex transceivers, and ultra-wideband sensing systems. Key innovations include reconfigurable photonic filters, beamforming networks, and interferometric sensors. Awards: IEEE Fellow (2025) Qualcomm Faculty Award (2017, 2018) NSF CAREER Award (2011) Outstanding Faculty Award (2012) Grants & Labs: Leads the SpecEES Initiative for energy-efficient mm-wave platforms. Collaborates with Texas Instruments on silicon photonics integration. His lab develops prototypes ranging from chip-scale sensors to phased array systems. Facility Affiliations: Based in the Wisenbaker Engineering Building (WEB 315C), part of Texas A&M's College of Engineering. Active in the Department's photonics and RFIC research clusters.

Alex SprintsonView profile

Professor

• Networking
• Network Coding
• Security and Privacy
• +4 more

Prof. Alex Sprintson is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, affiliated with the College of Engineering. He currently serves as a rotating Program Director at the NSF, managing networking research programs such as NeTS, SaTC, RINGS, and MLWiNS. His research focuses on algorithmic and information-theoretic aspects of networking, network coding, security, privacy, distributed storage systems, wireless communication, and software-defined networking. Sprintson holds a Ph.D., M.S., and B.S. in Electrical Engineering from Technion-Israel Institute of Technology (2003, 2001, 1995). His academic accolades include the Wolf Award, Viterbi Fellowship, TAMU Outstanding Contribution Award, and NSF CAREER Award. He has served on editorial boards (e.g., IEEE Transactions on Wireless Communications) and conference committees (e.g., IEEE Infocom). His work spans theoretical frameworks for secure communication, privacy-preserving protocols, and efficient distributed systems. Research highlights include pioneering contributions to private information retrieval, network coding applications, and coded computing. He leads projects on securing next-generation wireless networks and optimizing distributed storage systems. His NSF roles involve advancing research in machine learning for wireless systems and resilient cyber-physical infrastructure.

• Control Systems
• Optimization
• Engineering Education
• +7 more

Dr. Paul N Beuchat is a Senior Lecturer - Education Specialist in the Department of Electrical and Electronic Engineering at the Faculty of Engineering and Information Technology. His expertise spans control systems, optimization techniques, and engineering education, with a focus on approximate dynamic programming and its applications in robotics and autonomous systems. Education : PhD in Automatic Control from ETH Zurich (2019) M.Sc. in Robotics, Systems and Control from ETH Zurich (2014) B.Eng. in Mechanical Engineering and B.Sc. in Physics from University of Melbourne (2008) Research Interests : Paul's research integrates control theory with educational innovation. He develops approximate dynamic programming algorithms for large-scale systems, particularly in building control and quadcopter coordination . His work also explores project-based learning pedagogies, leveraging hardware-accelerated computing and IoT technologies to enhance engineering education. Recent Publications emphasize interdisciplinary teaching methods , quadcopter control systems , and data-driven optimization for autonomous vehicles. His projects include 5G URLLC Factory of the Future (2022-2023), reflecting his commitment to bridging theoretical control systems with practical educational frameworks. Advising & Grants : Paul contributes to educational grant initiatives such as the 5G URLLC Factory of the Future research contract. He actively participates in curriculum development and pedagogic research , focusing on student engagement and competency-based learning in engineering.

Sebastian HuntView profile

Senior Lecturer

• Software Engineering
• Systems Engineering
• Information Flow Security
• +7 more

Dr. Sebastian Hunt is a Senior Lecturer in the Department of Computing at City St George's, University of London. He has been a faculty member since 1992, progressing from Lecturer to Senior Lecturer in 2005. His academic foundation includes a BSc in Physics and Philosophy from the University of Bristol and an MSc and PhD in Computing from Imperial College London. Research Interests: His primary research lies in Software and Systems Engineering, with a strong emphasis on information flow security, semantics of security policies, and enforcement mechanisms. He investigates how security policies can be formally defined and enforced in programming languages, particularly focusing on information erasure, termination-insensitive noninterference, and quantitative information flow. His work bridges theoretical computer science with practical security concerns in software systems. Publication Trends: His recent publications, spanning from 2001 to 2023, demonstrate a consistent focus on formal methods in security. He frequently publishes in high-impact venues like PACMPL, IEEE CSF, and ESOP. A key trend is the evolution from qualitative to quantitative models of information flow, culminating in recent work that reconciles Shannon's information theory with Scott's domain theory for a more robust model of computable information. Scientific Awards and Memberships: Educational Affiliate Employee, British Computer Society (2011–present) Programme Committee Member, 14th International Conference on Verification, Model Checking and Abstract Interpretation (VMCAI 2013) Programme Committee Member, 8th International Conference on Information Systems Security (ICISS 2012) Advising and Grants: While specific advisees are not listed, his long-standing research collaborations with prominent figures like David Sands and Isabella Mastroeni suggest a strong mentoring role. His research has been supported by funding bodies such as the Swedish Science Council (SSF), as acknowledged in his recent work. His program committee roles indicate significant service to the academic community. Labs and Teams: The provided text does not mention specific labs or research teams. However, his extensive collaborative work, particularly with researchers from other institutions, suggests active participation in international research networks focused on programming languages and security.

• Cyber Security
• Big Data Analytics
• Software Engineering
• +2 more

Dr. Faheem Ullah is an Assistant Professor in the School of Computer and Mathematical Sciences at the University of Adelaide. He holds a dual role as Lecturer/Assistant Professor and is part of the Centre for Research on Engineering Software Technologies (CREST), where he leads R&D in big data analytics and cloud computing. His research focuses on cybersecurity, big data analytics, software engineering, cloud computing, and machine learning. He has applied these skills in healthcare, oil & gas, defense, and green computing domains. Dr. Ullah is eligible to supervise Masters and PhD students as a co-supervisor, emphasizing collaborative research endeavors. He actively contributes to the design and evaluation of cybersecurity systems, including frameworks for microservices, distributed data processing, and adaptive security analytics. His work bridges theoretical advancements with industry applications, addressing challenges such as vulnerability analysis in microservices, AI-driven threat detection, and optimizing cloud infrastructure. He is a sought-after expert in cybersecurity and cloud-native technologies, with a strong publication record in top-tier venues.

Adrián PekárView profile

Research Fellow

• Computer Networks
• Network Traffic Optimization
• Software-Defined Networks (SDN)
• +3 more

Adrián Pekár is a Senior Research Fellow at the Department of Networked Systems and Services, Budapest University of Technology and Economics (BME). He holds a PhD in Computer Networks from the Technical University of Kosice (TUKE), Slovakia (2014), and a bachelor's degree from TUKE (2011). His research focuses on optimizing network traffic measurement, monitoring platforms, and enhancing techniques for traffic classification, data reduction, and visualization in traditional and software-defined networks. Adrian's career includes roles as a Virtual Infrastructure Network Engineer at TUKE's Institute of Computer Technology (post-PhD), a Postdoctoral Fellow at Victoria University of Wellington (2016–2019), and an Assistant Professor (Lecturer) at BME (2019–2022). His current work continues to address challenges in network measurement and monitoring systems, leveraging both academic and practical expertise. No scientific awards or grants are explicitly mentioned in the provided text. His research interests emphasize interdisciplinary approaches to network efficiency and scalability.

Juha KontinenView profile

Professor

• Mathematical Logic
• Theoretical Computer Science
• Computational Complexity
• +3 more

Juha Kontinen is a Professor and Docent in the Department of Mathematics and Statistics at the University of Helsinki. He serves as a Supervisor for the Doctoral Programme in Mathematics and Statistics. His research focuses on mathematical logic, theoretical computer science, computational complexity, and formal methods. Key areas include dependence logic, team semantics, and their applications in areas like database theory and artificial intelligence. He has been actively involved in numerous research projects funded by organizations such as the Magnus Ehrnrooth Foundation and the Academy of Finland. His work spans foundational studies of computational complexity, formal logics for team semantics, and interdisciplinary applications. Recent projects include exploring discrete differential equations for circuit complexity and probabilistic team semantics with Boolean negation. Kontinen has authored/co-authored over 90 publications, including articles in prestigious journals and conference proceedings. His work bridges theoretical foundations with practical computational challenges, addressing topics like neural network training complexity and hyperproperties in temporal logics. He has also contributed to conference organization, peer review, and doctoral supervision, highlighting his role as a leader in the academic community.

• Computer Networks
• Software-Defined Networking (SDN)
• Telecommunications
• +5 more

José Manuel Arco Rodríguez is an Associate Professor in the Department of Automation at the Universidad de Alcalá (Spain). He holds a Doctorate from the same institution for his thesis Propuesta de optimización de la interconexión de redes con calidad de servicio para aplicaciones multimedia (2000), supervised by Dr. Daniel Meziat Luna. His research focuses on intelligent networks, software-defined networking (SDN), edge computing, and telecommunication systems, with particular emphasis on network optimization, protocol design, and AI integration in network architectures. He leads the NetIS research group (Networks and Intelligent Systems), exploring cutting-edge solutions for scalable, reliable data center networks and industrial IoT ecosystems. Key research areas include in-band network control, hybrid SDN architectures, multi-hop edge computing with IoT devices, and low-latency bridging protocols. His work spans theoretical frameworks to hardware implementations (e.g., NetFPGA), with a strong emphasis on practical applications in data centers, campus networks, and industrial environments. Recent contributions address AI-driven network management, plug-and-play routing protocols, and zero-configuration network architectures. Publications highlight advancements in SDN topology discovery (TEDP), scalable addressing (GA3), and path exploration protocols (ARP-Path, All-Path Bridging). His research bridges theoretical networking principles with real-world deployment challenges, often emphasizing interoperability between legacy and modern systems. Arco Rodríguez has collaborated on EU-funded projects and contributed to international standards for network protocols. His lab (NetIS) actively develops open-source tools for network analysis and simulation. Current research trends include AI-enhanced softwarized networks and cloud-edge continuum architectures for IIoT.

Diego López PajaresView profile

Lecturer

• Networking
• Software-Defined Networking (SDN)
• Internet of Things (IoT)
• +5 more

Diego López Pajares is a Lecturer at the Department of Automática within the Universidad de Alcalá, Spain. His research focuses on Software-Defined Networking (SDN), Internet of Things (IoT), edge computing, and AI-driven network optimization. He is a member of the NetIS research group (Networks and Intelligent Systems), which explores programmable networks and intelligent systems for future communication infrastructures. He earned his Doctorate in Engineering from Universidad de Alcalá with a thesis titled Nuevos conmutadores de red para redes integradas con SDN (New SDN-enabled network switches for integrated networks), supervised by Dr. Juan Antonio Carral Pelayo and Dr. Elisa Rojas Sánchez. His work addresses challenges in scalable network protocols, hybrid SDN architectures, and AI applications in telecommunications. Key research trends include edge computing IIoT systems, fault prediction in smart grids, and 6G-enabling technologies. His publications emphasize in-band control protocols, disjoint path algorithms, and P4-programmable switches. Collaborative efforts with industry and academia aim to bridge theoretical advancements with practical network deployments. Notable contributions include the BareFlow protocol for Layer-2 plug-and-play routing, MDTA algorithm for dynamic environments, and eHDDP for heterogeneous network discovery. These innovations address scalability, security, and interoperability in modern network ecosystems. López Pajares' work intersects with military deployable networks, autonomous vehicle traffic systems (SYROPS), and cloud continuum architectures. His research bridges traditional networking domains with emerging paradigms like AIoT and software-defined infrastructures.

Elisa Rojas SánchezView profile

Professor

• Networking
• Software-Defined Networking (SDN)
• Edge Computing
• +7 more

Elisa Rojas Sánchez is a tenured professor at the University of Alcalá, affiliated with the Department of Automation within the School of Telematics Engineering. Her primary research focuses on advanced networking technologies including Software-Defined Networking (SDN), edge computing, IoT integration, and network architecture optimization. She leads the NetIS research group (Networks and Intelligent Systems), exploring innovations in programmable networks and intelligent systems for future communication infrastructures. Her academic background includes a doctoral thesis on high-performance transparent Ethernet switch architectures. She has contributed significantly to protocols like ARP-Path and Torii-HLMAC, advancing scalable routing and fault-tolerant data center designs. Her work bridges theoretical networking research with practical implementations in 6G, industrial IoT, and cloud-edge continuum systems. Recent publications highlight breakthroughs in data-driven protocols (e.g., BareFlow), AI-driven fault prediction in smart grids, and topology-aware resource management in dense networks. She also explores educational innovations like gamification in engineering teaching and hybrid SDN methodologies. Key Research Themes: SDN protocols, edge computing frameworks, IoT scalability, network resilience, AI in networking Notable Achievements: Developed open-source tools like NetIDE, contributed to OpenFlow standards, and pioneered multi-path routing algorithms Her work frequently addresses real-world challenges such as latency reduction in programmable ASICs (Tofino P4), secure in-band control channels, and collaborative resource-sharing in edge environments. She actively participates in international conferences as a program chair and continues advancing the next generation of network architectures.

Muhammad Fermi PashaView profile

Senior Lecturer

• Computational Neuroimaging
• Intelligent Network Security
• Digital Health
• +15 more

Muhammad Fermi Pasha is a Senior Lecturer at the School of Information Technology, Monash University, Malaysia. He holds a PhD in Brain-inspired Computing from Universiti Sains Malaysia and has been actively contributing to research and teaching since joining Monash. His academic roles include lecturing and serving as Chief Examiner for courses such as FIT1008, FIT2085, FIT9123, FIT5152, and FIT3175, focusing on computer science, business information systems, and usability. PhD in Brain-inspired Computing, Universiti Sains Malaysia (2010) MSc in Computer Science, Universiti Sains Malaysia (2006) BCompSc (Hons) in Software Engineering, Universiti Sains Malaysia (2003) Dr. Pasha's research spans computational neuroimaging, intelligent network security, digital health, and big data analytics. His work integrates artificial intelligence with healthcare applications, including Alzheimer's diagnosis, mHealth platforms, and secure medical data systems. He emphasizes evolving systems, machine intelligence, and neocortex memory modeling. His projects often involve interdisciplinary collaboration and community engagement. The recent publications highlight a strong trend in AI-driven healthcare solutions, secure data systems, and behavioral analysis using deep learning. His work combines computer vision, natural language processing, and cybersecurity to address real-world challenges in medicine and public health. Themes such as microexpression recognition, EHR clustering, blockchain for IIoT, and flood modeling using CNNs reflect his diverse yet cohesive research vision. Awards for software solutions and research projects as team lead or member (specific names not provided) Dr. Pasha supervises multiple PhD students and leads significant research grants, including projects on microexpression recognition, Alzheimer's prediction, and flood modeling. He collaborates with national and international researchers and contributes to UN Sustainable Development Goals, particularly in health and education. His lab work involves developing intelligent systems for medical and environmental applications. He leads or participates in key research labs and teams focused on AI in healthcare, network security, and sustainable computing. These teams develop frameworks for early disease detection, secure data sharing, and environmental resilience using advanced machine learning and blockchain technologies.