Assoc. Prof. Ivan Ivanov is affiliated with the Faculty of Theology at the University of Sofia , where he holds the academic rank of Associate Professor . His research spans interdisciplinary domains, including Medical Research , Artificial Intelligence , Public Health , and Theology . Email: ivan.ivanov@theo.uni-sofia.bg Research Interests: His work addresses diverse topics such as: Medical Research: Cancer prognosis, Ki-67 assessment, dental treatments, and infectious diseases. Artificial Intelligence: Energy consumption prediction and AI in programmer training. Public Health: Co-infections in pandemic contexts, substance abuse interventions, and epidemiological studies. Biomechanics: Analysis of human movement and therapeutic applications. Education: AI-driven educational tools and language acquisition. Theology: Historical and liturgical interpretations. Publications: His recent works focus on interdisciplinary applications in healthcare, AI, and theological studies, reflecting a broad methodological approach. Additional Contributions: Ivanov actively engages in software-defined radio research, cybersecurity, and educational technology development.
Peter Alexander is a Lecturer at the School of Informatics and Cybersecurity within TU Dublin, where he has taught since 2016 after 11 years as a Cisco technical solutions specialist in industry. A graduate of TU Dublin himself, he holds both bachelor's and master's degrees from the institution and emphasizes "giving back" through education while mentoring students in technical disciplines. His educational background includes: M.Sc. in Computing (Advanced Software Development) - 2:1 Honours, TU Dublin (City Centre Campus) Honours Bachelor of Computer Engineering - First Class Honours, TU Dublin (Blanchardstown Campus) Cisco Certified Network Associate (CCNA) Cisco Networking Academy Certified Instructor – CCNA1, CCNA2, CCNA3, CCNA Security, IT Essentials Specializing in networking, network security, and virtualisation, his research spans cloud computing, Internet of Things (IoT), Software-Defined Networking (SDN), and data visualisation. He has taught diverse courses including databases, web development, and computer systems while supervising multiple master's projects in cyber security, reflecting his industry-academic bridge approach to technical education. No scientific awards were documented in the provided materials. He has supervised several master's projects in cyber security but no research grants or external funding sources were referenced. His teaching philosophy emphasizes student engagement with academic challenges as foundational to professional growth in technology fields.
Dr. Wencong Su is a Professor and Chair of the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn , where he leads research in power systems, transportation electrification, and cyber-physical systems. He earned his B.S. (2008) from Clarkson University, M.S. (2009) from Virginia Tech, and Ph.D. (2013) from North Carolina State University. Research Interests: Power and energy systems, renewable integration, electric vehicles, machine learning, and smart grid technologies. Editorial Roles: Associate Editor for IEEE Transactions on Smart Grid , IEEE Access , and IEEE DataPort . His research focuses on optimizing power electronics, enhancing grid stability with distributed energy resources, and applying AI to energy systems. Recent work includes surrogate modeling for converter design, safe reinforcement learning in power grids, and cyber-physical solutions for digital substations. Publications span topics like second-life battery applications, high-frequency AC microgrids, and AI-driven energy management. His articles emphasize machine learning, optimization, and robust control in renewable integration and transportation electrification. Awards include IEEE Fellowships, Top 2% Scientist recognition (Stanford), and multiple IEEE best paper awards. He has secured grants from NSF, DoE, Ford, Toyota, and DTE Energy. Labs operate in the Institute for Advanced Vehicle Systems (IAVS-2060, IAVS-1060, ELB-1026, ELB-1042), focusing on power electronics, smart grid validation, and electrified transportation.
Radu Vintan is a Doctoral Assistant and PhD student at École polytechnique fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, affiliated with the Institute of Computer Science and the Theory of Computation Laboratory 2 (THL2). He is part of the Doctoral Program in Computer and Communication Sciences (EDIC). Education: Bachelor's and Master's in Computer Science, Technical University of Munich (TUM), Germany PhD in Computer Science, École polytechnique fédérale de Lausanne (EPFL), Switzerland (ongoing) His primary research interests lie in theoretical computer science , particularly online algorithms and approximation algorithms . He also has experience in machine learning and software engineering . His work often involves algorithmic design and analysis for graph and network problems. The recent publications reflect a strong focus on online edge coloring and network update algorithms , with contributions to top-tier conferences such as FOCS, STOC, SODA, and INFOCOM. These works explore both theoretical limits and practical algorithmic solutions, often bridging deterministic and randomized approaches. Scientific Awards: No awards mentioned. Advising and Grants: Radu Vintan is advised by Professor Ola Svensson. There is no mention of him advising students or receiving independent grants. His research is conducted within the Theory group at EPFL, supported through his Doctoral Assistant position. Laboratories and Teams: He is an active member of the Theory of Computation Laboratory 2 (THL2) at EPFL, contributing to foundational algorithmic research in collaboration with leading experts in theoretical computer science.
Jun Luo is an Associate Professor in the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He earned his PhD in Computer Science from EPFL under the supervision of Prof. Jean-Pierre Hubaux and completed postdoctoral research at the University of Waterloo. He joined NTU in 2008 as an Assistant Professor and was promoted to Associate Professor in 2014. He served as Deputy Director of the Centre for Multimedia and Network Technology from 2010 to 2013. Education: PhD in Computer Science, Swiss Federal Institute of Technology in Lausanne (EPFL), 2006 MS in Electrical Engineering, Tsinghua University, 2000 BS in Electrical Engineering, Tsinghua University, 1997 Research Interests: Jun Luo's research focuses on mobile and pervasive computing, wireless networking, machine learning, and applied operations research. His primary research thrusts include: Contact-free Sensing Driven by Deep Learning : Leveraging RF, acoustic, and visible light signals for human activity recognition, respiration monitoring, and localization without wearable devices. Visible Light Communication and Sensing : Exploring LED-camera systems for data transmission, occupancy inference, and indoor broadcasting. Indoor and Outdoor Localization and Tracking : Developing systems using WiFi, geomagnetism, and crowdsourced data for precise positioning. Machine Learning for Mobile Networking : Applying deep learning and optimization to improve wireless network performance, mobile crowdsensing, and resource allocation. Publication Trends: His recent publications (2021–2023) demonstrate a strong focus on deep learning-enhanced sensing using RF and acoustic signals, particularly for health monitoring (e.g., respiration, heartbeat), multi-person tracking, and privacy-preserving techniques. He frequently collaborates with researchers in signal processing, computer vision, and networking, publishing in top venues like IEEE Transactions on Mobile Computing, MobiCom, and INFOCOM. His work emphasizes practical deployment on commodity devices and integration of sensing with communication systems. Scientific Recognition: IEEE Fellow Advising and Grants: Dr. Luo has advised numerous PhD and Master's students, as evidenced by the extensive list of student co-authors across his publications. He has led significant research projects in wireless sensor networks, mobile computing, and IoT systems, likely supported by competitive grants from Singaporean and international funding agencies. His role as Deputy Director of a research center indicates leadership in managing research teams and collaborative efforts. Labs and Teams: He leads a research group focused on mobile and distributed computing, deep learning, and computer vision. His team actively publishes in top-tier conferences and journals, working on projects involving RF sensing, acoustic platforms, visible light communication, and privacy-aware systems. The group collaborates with researchers both within NTU and internationally, particularly in Canada and China.
Dr. Vicky Liu is a Senior Lecturer in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. Her work spans network security, IoT ecosystems, smart grid security, and network performance optimization. She leads research projects in secure energy markets, IoT for power industry optimization, and precise positioning systems. PhD, Queensland University of Technology Master of IT (Research), Queensland University of Technology Bachelor of Business (Computing), Queensland University of Technology Her research interests focus on network security and performance in emerging technologies. Key areas include IoT security (especially MUD, LoRa, Wi-Fi HaLow), smart city architectures, software-defined networking, and cybersecurity for smart grids and national energy markets. She investigates how to balance security with performance in resource-constrained environments. The recent publications highlight a strong trend in IoT and smart grid security , with extensive work on LoRa and Wi-Fi HaLow for energy and urban applications. Her research integrates experimental validation, architectural design, and compliance frameworks. Topics include DoS/DDoS detection, authentication schemes, energy modeling, and secure trading systems. Vice-Chancellor's Performance Award (International Collaboration), 2008 Dr. Liu actively supervises HDR students at Honours, Masters, and PhD levels, with completed theses on IoT smart grids, secure energy trading, DTN routing, and VANET security. She has secured competitive grants including from IMCRC and Geoscience Australia. She led a Capital Equipment Grant to establish a state-of-the-art network laboratory at QUT for hands-on teaching and research. Her work bridges academia and industry, particularly in energy and telecommunications. She leads and contributes to research teams focused on IoT security and smart infrastructure. Her lab supports practical experimentation with real-world networking equipment and protocols. Current and future work includes enhancing IoT profiling assurance, optimizing Wi-Fi HaLow under variable conditions, and strengthening legal compliance in critical communication systems.
Professor Brighten Godfrey is a faculty member in the Department of Computer Science and an affiliate of the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He earned a Ph.D. in Computer Science from UC Berkeley (2009) and a B.S. from Carnegie Mellon University (2002). His research spans networked systems with a focus on low-latency networking , software-defined networks , microservices , and machine learning for networks . Ph.D. (2009) and B.S. (2002) in Computer Science Professor at UIUC since 2021 Technical Director at VMware (acquired Veriflow in 2019) His recent publications address microservice tracing , cluster verification , and mobile acceleration , with high-impact applications in XR systems and low-latency networks . Awards include the ACM SIGCOMM Rising Star Award , Sloan Research Fellowship , and multiple best paper and dataset awards . He has chaired program committees for SIGCOMM and HotNets . Teaching honors include Excellent Teacher and Outstanding Advising Awards . His research group has produced alumni now at institutions like Meta, Google, and ETH Zurich. Current projects include Service Layer Traffic Engineering (SLATE) and Learning-Based Congestion Control (Aurora, PCC).
Cem Ersoy is a full Professor at the Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey. He serves as the Vice Director of TETAM and leads the Computer Networks Research Laboratory (NetLab), driving forward research in wireless networks, pervasive health, IoT, 5G, SDN, and emerging air computing paradigms. His research spans cutting-edge domains such as air computing, edge intelligence, wearable stress monitoring, indoor localization, and smart city neurocomputing challenges. By integrating deep reinforcement learning, probabilistic modeling, and IoT systems, his work aims to create unobtrusive, scalable, and adaptive computing solutions for real-life environments. Recent publications reveal a strong focus on air computing as a novel computation paradigm, leveraging multi-agent deep learning and simulation frameworks. Another major trend is wearable-based affect and stress monitoring , where semi-supervised learning and explainable AI reduce labeling burdens while enhancing real-life applicability. Additional work addresses edge computing orchestration , network slicing , and live video streaming optimization using SDN and reinforcement learning. Prof. Ersoy actively advises graduate researchers and leads funded projects in national and international arenas, although specific grant titles and student names are not listed in the source. His lab, NetLab, provides a collaborative environment for innovations in computer networks, IoT, and pervasive health technologies.
Dr. Dimitrios Efstathiou serves as a Professor at the Department of Informatics, Computer and Telecommunications Engineering of the International Hellenic University (Serres Campus), bringing over 25 years of expertise in telecommunications systems with emphasis on baseband/intermediate frequency design. His industrial tenure includes critical roles at Nokia Mobile Phones and Analog Devices where he pioneered satellite receiver and base station technologies. His educational foundation includes a B.E. in Electrical Engineering from the University of Patras (1989), M.Sc. in Digital Electronics (1991), and Ph.D. in Digital Communication Systems (1996), all from King's College London. Efstathiou's research spans digital telecommunications theory, 4G/5G/6G systems, software-defined radio, IoT security, and physical layer countermeasures against jamming. His work addresses fundamental challenges in signal integrity, network efficiency, and wireless security through innovative algorithm design for timing circuits and digital PLLs. Recent publications demonstrate sustained leadership in WBAN standards and OFDM security enhancement. His 50+ publications reveal evolving expertise from early software radio implementations to contemporary physical layer security frameworks, with consistent focus on practical baseband solutions for multi-carrier systems across 3G to 6G generations. He has supervised 71 bachelor theses and numerous graduate projects while maintaining active industry collaboration. His IEEE leadership includes Chairing the Vehicular Technology and Aerospace Electronic Systems Joint Greece Chapter (2012-2020) and serving as Senior Member since 2006.
Dr. Husnain Rafiq is a Lecturer in Cyber Security at Edge Hill University, where he conducts research on machine learning applications in cybersecurity. He earned his PhD in Cyber Security from Northumbria University in December 2022, focusing on ML-based mobile malware defense. With over seven years of teaching experience, he currently supervises graduate research projects in mobile security, adversarial ML, and malware detection. Research Focus His research spans: Machine Learning for Security: Developing adversarial-aware malware detectors and evasion-resistant models Mobile Systems Protection: Specializing in Android malware detection using image processing and deep learning Cyber Defense Innovations: Creating GAN-based botnet detectors and DGA detection systems Trustworthy AI: Exploring explainable AI for fraud detection and content moderation Publication Trends Recent works demonstrate strong focus on adversarial machine learning (77% of publications) with applications in malware detection (57%), network security (35%), and trust-aware AI systems (21%). Emerging themes include explainable fraud detection, sustainable risk frameworks, and low-data regime solutions.
Michael Stübert Berger is an Associate Professor at the Department of Electrical and Photonics Engineering, Technical University of Denmark (DTU). His research focuses on Mobile Networks, Radio Access Networks, Carrier Ethernet, Multicasting, Control Plane, Software-Defined Networking (SDN) , and Energy Engineering . He actively contributes to advancements in 5G communication , Internet of Things (IoT) , and secure infrastructure design . Current Projects : Deterministic and Secure 5G Communication (Supervisor), Reliable and Secure M2M/IoT Communication (Supervisor). Collaborations : Extensive international work in Poland and Denmark on Broadband Trials and Coaxial Modem Development . Research Trends : His recent publications emphasize green networking through SDN/NFV, energy-efficient 5G/LTE comparisons, and emergency service architectures leveraging cross-domain communication. Key subfields include Cloud-RAN , teleoperated driving , and secure infrastructure . Supervision : He advises multiple PhD students including R. Singh, E. Gottschalk, and S. C. Nwabuona on topics spanning SDN, 5G, and IoT.
Ronan Farrell is a Professor in the Department of Electronic Engineering at Maynooth University’s Faculty of Science & Engineering and currently serves as Vice President Academic and Registrar. He earned a BE and PhD from University College Dublin (1993, 1998) and previously worked at ICI/Zeneca Chemicals (1993–1995) and Parthus Technologies (1998–2001) as a mixed-signal ASIC designer. His academic career at Maynooth spans from Lecturer to Professor (2016), with leadership roles as Head of Department (2012–2019) and Director of the Callan Institute (2008–2015). He leads SFI research initiatives in radio frequency electronics and sensor networks. Education: BE (1993), PhD (1998) – University College Dublin Leadership: Head of Electronic Engineering (2012–2019), Director of Callan Institute (2008–2015) Research Focus: Wireless system design, RF/mixed-signal electronics, technology transfer, and innovation. His work bridges theoretical advancements (e.g., MIMO capacity optimization) with practical applications (e.g., 5G transmitters, digital predistortion techniques). Publication Trends: Recent articles emphasize 5G wireless systems, power amplifier linearization, OFDM signal processing, and behavioral modeling. Collaborations span institutions in Ireland, Europe, and Asia, with a focus on hardware implementation and system optimization. Students & Collaborations: Mentions co-authors in publications but no explicit student list provided. Collaborates with researchers in Ireland, Germany, and China.
Rohan Padhye is an Assistant Professor at the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science . He leads the PASTA Lab and is affiliate faculty at CyLab . Ph.D. in Computer Science from UC Berkeley Master's degree in Computer Science from IIT Bombay His research spans software engineering, programming languages, systems, and security . He develops techniques for automated bug detection using dynamic program analysis and coverage-guided fuzz testing. His work includes tools like ChocoPy for compilers education and Fray for concurrency testing. Recent publications focus on: date/time bugs in Python, LLM-generated property-based tests , exception dependency analysis , and distributed system fuzzing . He has received multiple NSF grants and Amazon Research Awards . 2025: NSF Grant for Practical Controlled Concurrency Testing 2025: Amazon Research Award for property-based testing 2022: Goldwater Scholarship for John Billos (PASTA Lab member) He advises PhD students including Ao Li and Vasudev Vikram, and has mentored numerous undergraduate researchers through the REUSE program . His group's work is funded by NSF, CyLab, and Amazon .
Prof. Kurt Rothermel is a faculty member at the University of Stuttgart, specifically affiliated with the Institute for Parallel and Distributed Systems (IPVS) within the Faculty of Computer Science, Electrical Engineering, and Information Technology. His research focuses on distributed systems with particular expertise in time-sensitive networking, networked control systems, and complex event processing. Prof. Rothermel's research interests span multiple areas in distributed computing and networking: Distributed Systems and Networked Control Systems Time-Sensitive Networking and Deterministic Networking Quality of Service (QoS) Management and Optimization Complex Event Processing and Stream Analytics Edge Computing and Real-Time Video Analytics Digital Twin Systems and Proximity-based Services His recent publications (2022-2025) demonstrate a strong focus on time-sensitive networking, with numerous papers addressing scheduling algorithms, conflict graph creation, and latency management for time-triggered communication. There's also significant work on load shedding techniques for resource-constrained environments, particularly for real-time video analytics at the edge. His research increasingly incorporates digital twin systems and explores novel approaches for distributed mobile simulation, as evidenced by his "Persival" framework for handling 3D meshes on AR devices. Prof. Rothermel has made substantial contributions to the field of complex event processing, developing multiple shedding strategies (gspice, hSPICE, pspice) to manage resource constraints while maintaining utility. His work bridges theoretical networking concepts with practical applications in industrial settings, particularly evident in his research on networked control systems and time-sensitive software-defined networks.
Hercules Avramopoulos is a full Professor at the National Technical University of Athens (NTUA) within the School of Electrical and Computer Engineering, where he heads the Photonics Communications Research Laboratory (PCRL). His work bridges academic research and industrial application in photonics, with leadership in European collaborative projects. His educational background includes a BSc and MSc in Physics and Applied Optics from Imperial College London, followed by a PhD in Physics (1989) focusing on nonlinear effects in lasers and optical fibers. Prior to NTUA, he conducted research at AT&T Bell Laboratories. Avramopoulos' research spans photonic integrated circuits , quantum communications , optical interconnects , and biophotonics sensing . Current work emphasizes monolithic/hybrid photonic integration (silicon, InP, polymers), quantum key distribution (QKD) for satellite/terrestrial networks, and photonic sensors for composite manufacturing. His group develops advanced modulation formats, DSP techniques, and all-optical switching systems. Recent publications show strong focus on quantum-classical coexistence in fiber/FSO networks, 6G X-haul architectures combining fiber/mmWave/FSO, and embedded photonic sensors for industrial processes. Key trends include satellite QKD feasibility, SDN-controlled hybrid transport, and machine learning-enhanced optical signal processing. He has supervised 26 completed PhD theses with 12 current doctoral students. Alumni include 10 faculty members at Greek/European universities and professionals at Cisco, Nokia, and the European Patent Office. PCRL has participated in over 60 European projects (coordinating ~30), including current initiatives like POLYNICES and TWILIGHT. PCRL maintains a 30-member team developing photonic solutions across five domains: optical interconnects, DSP, PIC design, biophotonics, and quantum communications. The lab holds 5 patents and has produced 500+ publications (200+ journal articles). Current infrastructure supports quantum communications research for IYQ2025 (International Year of Quantum 2025) initiatives.
