Find Academic Supervisors

• Software Defined Networking
• Network Functions Virtualisation
• Network Security
• +6 more

Nicholas Race is a Professor of Networked Systems at Lancaster University's School of Computing and Communications, where he also serves as Associate Dean for Research for the Faculty of Science & Technology since 2020. His academic career at Lancaster spans over two decades, progressing from Research Assistant (2000-2001) to his current professorship (2017-present), with previous roles including Reader in Networking (2015-2017) and Senior Lecturer (2008-2015). His educational background includes a Doctor of Philosophy from Lancaster University (2000) and a 1st Class B.Sc. Hons in Computer Science from the same institution (1996). Race leads significant research initiatives including NG-CDI (an EPSRC/BT funded Prosperity Partnership), AI4ME (an EPSRC/BBC funded project), and MANY, building on previous leadership roles in projects such as 5GRIT, INITIATE, MPAT, and several EU-funded initiatives. Race's research focuses on Software Defined Networking (SDN) and Network Functions Virtualisation (NFV) for developing next-generation networking services. His work spans network security (including the TENNISON framework for distributed SDN security), media distribution with Quality of Experience optimization, and autonomic network management. His recent publications reveal a strong emphasis on intent-based networking, security automation, quality of experience in adaptive streaming, and the integration of 5G with other networking technologies. His scholarly output shows consistent contributions across multiple venues, with recent work addressing challenges in low-latency streaming, network security evaluation frameworks, and the practical implementation of software-defined networking concepts. The publications demonstrate an interdisciplinary approach bridging theoretical networking concepts with practical implementations. Race serves on the editorial board of Computer Communications and has held leadership roles in major conferences including as Programme Co-Chair of DE2013: Open Digital and as PC Member for ACM Multimedia, Multimedia Systems, and EWSDN. As a research supervisor, he mentors multiple PhD students working on topics related to SDN, network security, and media delivery. His projects attract significant funding from EPSRC, BT, BBC, and EU sources, demonstrating the applied relevance of his work to both industry and academic communities. Race is affiliated with several research groups including the Cyber Security Research Centre (Networking), Data Science Institute Foundations, Security Lancaster (Networks), and other specialized centers focusing on network security and systems.

Shyam GollakotaView profile

Professor

• Artificial Intelligence
• Computing + Biology
• Human-Centered Computing
• +6 more

Shyam Gollakota is a Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. His research spans Artificial Intelligence, Human-Centered Computing, and Wireless Systems , with interdisciplinary collaborations in Biology and Medicine. He leads the Mobile Intelligence Lab , co-founded Sound Life Sciences (acquired by Google), and developed battery-free computing technologies. Education: Ph.D. from MIT (2013), B.Tech from IIT Madras Awards: Infosys Prize 2024, Moore Inventor Fellow, NSF CAREER, ACM Grace Murray Hopper Award His research focuses on machine learning for mobile systems, battery-free sensing, and human auditory augmentation . Recent work includes proactive in-ear assistants (ACL 2025), spatial speech translation (CHI 2025), and sound bubbles for personalized audio (Nature Electronics 2024) . Publications span Human-Computer Interaction, Wireless Networking, and Medical AI . Scientific achievements include: Best Paper Awards: MOBICOM, SIGCOMM, UbiComp, SenSys, NSDI, CHI Breakthroughs: Battery-free phones, ambient backscatter, smartphone-based medical diagnostics His team co-developed underwater GPS (SIGCOMM 2023), AI-enabled ClearBuds (MobiSys 2022), and wireless blood clot testing (Nature Communications 2022) . Collaborations include the Washington Department of Agriculture for monitoring invasive hornets.

Gen-Huey ChenView profile

Professor

• Graph Theory
• Combinatorial Optimization
• Algorithm Analysis and Design
• +1 more

Gen-Huey Chen is a Distinguished Professor in the Department of Computer Science and Information Engineering at National Taiwan University, where he has served since 1987 (Associate Professor 1987-1992, Professor since 1992). He previously held leadership roles as Dean of the College of Science and Technology (2001-2005) and Department Chair (2001-2002) at National Chi Nan University. Education Ph.D. in Computer Management Decision, National Tsing Hua University, 1987 B.S. in Computer Science and Information Engineering, National Taiwan University, 1981 Research Interests Professor Chen's work centers on Graph Theory , Combinatorial Optimization , and Algorithm Analysis and Design , with significant contributions to discrete mathematics and network theory. His research bridges theoretical foundations and practical applications, particularly in structural graph problems and wireless network protocols, emphasizing efficient algorithmic solutions for complex computational challenges. Publications Trends His 2007-2009 publications reveal a cohesive research trajectory focused on graph-theoretic applications in networking. Key patterns include structural analysis of specialized graphs (chordal/circular-arc), fault tolerance in multiprocessor topologies (grids/tori), and bandwidth-optimized routing in mobile ad-hoc networks. These works consistently apply combinatorial optimization to solve real-world networking constraints while advancing theoretical graph algorithms. Advising and Grants No specific information regarding student advising or research grant funding is provided in the source material. Laboratory He directs the Discrete Algorithm Lab at National Taiwan University, which specializes in discrete algorithm development and wireless network protocol research.

Wen-Chin ChenView profile

Professor

• Design and Analysis of Algorithms
• Multimedia Systems
• Quantum Algorithms
• +7 more

Wen-Chin Chen is a Professor at National Taiwan University in the Department of Computer Science and Information Engineering. With a PhD in Computer Science from Brown University (1984), his expertise spans algorithms , multimedia systems , and quantum computing . Previously at GTE Laboratories (1984–1987), he has taught foundational courses such as Algorithms , Mathematical Analysis of Algorithms , and Quantum Algorithms . Education: BS in Mathematics, National Taiwan University (1976) PhD in Computer Science, Brown University (1984) His research integrates design and analysis of algorithms with applications in multimedia synchronization and quantum computing . Publications reflect deep engagement with data structures , combinatorics , and real-time system design , including work on audio-video synchronization models , heap-ordered trees , and genetic algorithm optimization . Recent projects involve quantum algorithms (e.g., Shor's, Grover's) and linear algebra for geometric and matrix operations, indicating ongoing contributions to theoretical computer science and applied mathematics .

• Audio Engineering
• Computer Networking
• Mobile Computing
• +3 more

Deshinder Singh Gill serves as a Principal Lecturer at the School of Architecture, Technology and Engineering, University of Brighton, with contact email D.S.Gill@brighton.ac.uk. His research career spans from 2000 to 2016, demonstrating sustained contributions across engineering and computing disciplines through 12 documented research outputs and supervision of 2 students. His research profile centers on Audio Engineering (specializing in loudspeaker design, directivity control, and transducer arrays), Computer Networking (focusing on mobile IPTV infrastructure and bandwidth-efficient routing algorithms), and Educational Technology (particularly open-source software applications in electronic engineering education). Additional expertise includes Product Design methodologies and practical case study implementations addressing real-world engineering challenges. Publication trends from 2014-2016 reveal concentrated innovation in mobile video streaming optimization, including adaptive CDN architectures and unicast routing protocols for resource-constrained devices. Concurrently, his educational research pioneered CAD teaching frameworks using open-source tools, establishing interdisciplinary connections between networking theory and pedagogical practice. Dr. Gill's academic supervision encompasses 2 graduate students, reflecting his commitment to mentoring within engineering education, though specific student names and grant details remain undocumented in the source material.

Kylie LuskaView profile

Assistant Professor

• Biological Chemistry
• Environmental Chemistry
• Organic Chemistry
• +3 more

Kylie Luska is an Assistant Professor, Teaching Stream at the University of Toronto, located at the Downtown Toronto (St. George) campus. She is affiliated with the Lash Miller Chemical Laboratories and focuses on enhancing educational methods in chemistry through student-centered approaches and inquiry-based laboratory activities. Her research integrates sustainable chemistry principles into undergraduate curricula to foster critical thinking and problem-solving skills. Education background includes a Ph.D. in Chemistry (2012) with a thesis on Catalytic Application of Ionic Liquid-Stabilized Metal Nanoparticles and Molecular Complexes , and a M.Sc. in Chemistry (2007) focusing on Ruthenium-Based Ionic Hydrogenation Catalysts... . Her professional experience spans over a decade in both academic and industrial catalysis research. Research interests emphasize innovative pedagogy: classroom problem-solving sessions with video recordings, inquiry-based labs replacing traditional 'recipe-based' experiments, and sustainable chemistry integration. Her lab-developed activities include chromatography and liquid-liquid extraction experiments for second-year organic chemistry. Publications (15+ since 2015) highlight expertise in supported ionic liquid phase (SILP) catalysts for hydrogenation/hydrodeoxygenation, nanoparticle synthesis, and catalytic selectivity. She collaborates on undergraduate research projects (CHM299Y/399Y/499Y) and CTFP initiatives. Currently leads a teaching-focused team within the Chemistry Department, advocating for curricular reforms that align with modern chemical education practices. Her work bridges traditional catalysis research with pedagogical innovation, aiming to prepare students for academic and industrial lab environments through experiential learning.

• Computer Networking
• Internet Video Streaming
• Quality of Service
• +4 more

Hui Zhang is a Professor in the School of Computer Science at Carnegie Mellon University, where he has made significant contributions to networking research for over two decades. He received his PhD from the University of California, Berkeley in 1993 and has maintained a prominent research career focusing on internet protocols, video streaming, and network management. His research interests span computer networking, internet video streaming, quality of service, content delivery networks, network protocols, multimedia communication, and network management. Professor Zhang's work has been particularly influential in developing adaptive video streaming technologies and content delivery mechanisms that power much of today's internet video infrastructure. His recent publications demonstrate continued innovation in networked systems, with a focus on improving video quality of experience through machine learning techniques and advanced network control mechanisms. The research trends show an evolution from foundational network protocol design to more application-focused solutions for video delivery and user experience optimization. Professor Zhang has mentored numerous successful researchers who have gone on to make their own significant contributions to the field. His collaborative work spans multiple institutions including Carnegie Mellon University, University of California, and various industry research labs. His research has been supported by substantial grants from NSF, industry partnerships, and has resulted in technologies that have been widely adopted in commercial video streaming services. Professor Zhang maintains an active research laboratory focusing on next-generation networked multimedia systems.

• Machine Learning
• Reinforcement Learning
• Artificial Intelligence
• +3 more

John Langford is a researcher at Microsoft Research, USA. His work focuses on foundational areas in machine learning, including reinforcement learning, contextual bandits, and optimization. He has contributed to advancements in scalable and efficient learning systems, with applications in human-computer interaction, robotics, and AI policy learning. Research Interests: Langford's research spans reinforcement learning (e.g., belief state estimation, latent state discovery), contextual bandits (e.g., decision-making under uncertainty), and model efficiency (e.g., inference-time scaling for complex tasks). His recent work emphasizes developing robust frameworks for AI systems that generalize across diverse tasks and environments. Publications: His articles address cutting-edge topics like gaze-tracking interfaces, belief state transformers, and ensemble methods for large language models. These contributions highlight his interest in bridging theory and practical applications in AI. Labs/Teams: His primary affiliation is with Microsoft Research, where he collaborates on projects advancing machine learning and its interdisciplinary applications.

• Privacy-preserving technologies
• Educational technology
• Cybersecurity
• +5 more

Zikai Alex Wen is an Assistant Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. Previously, he earned his PhD from Cornell University in 2021 with a dissertation on educational video games and intelligent tutoring systems. His research bridges multiple domains including privacy-preserving technologies, educational technology, cybersecurity, and accessibility. Wen's primary research interests focus on differential privacy, educational technology for students with learning disabilities, phishing detection and prevention, and game design for accessibility. His work uniquely combines theoretical privacy foundations with practical applications in education and security. He has made significant contributions to understanding how privacy mechanisms can be effectively explained to users and how to design systems that protect sensitive data while maintaining utility. His publication record demonstrates consistent output in top venues including IEEE S&P, CHI, ASSETS, and VLDB. Recent work shows increasing focus on generative AI applications for household safety, enhanced differential privacy mechanisms, and continued innovation in educational technology for diverse learners. His research often involves interdisciplinary collaboration across computer security, human-computer interaction, and educational psychology. Wen has received recognition through publications in prestigious venues but specific awards aren't documented in the available records. His work has been supported by research grants focused on privacy technologies and educational accessibility, though specific grant details aren't provided in the source material. He maintains active collaborations with researchers worldwide, particularly with Changyu Dong, Wei Cai, and Shiri Azenkot. His research group focuses on developing practical privacy-preserving systems and accessible educational technologies, with ongoing projects exploring the intersection of AI, security, and inclusive design.

Sabita MaharjanView profile

Professor

• Green Networks
• Smart Grid
• Vehicular Networks
• +7 more

Sabita Maharjan is a Full Professor at the Department of Informatics, University of Oslo, Norway, and a Senior Research Scientist (adjunct) at Simula Metropolitan Centre for Digital Engineering. She holds a PhD in Networks and Distributed Systems from the University of Oslo (2013) and has been active in research and academic leadership since. Her roles include Associate Editor for IEEE Internet of Things Journal and Guest Editor for several high-impact journals. Education: Ph.D. in Networks and Distributed Systems (2013), University of Oslo; M.Sc. in Antenna and Propagation (2008), Tokyo Institute of Technology. Prior roles include Postdoctoral Fellow at Simula Research Lab (2014–2016) and Visiting Scholarships at Zhejiang University and UIUC. Research focuses on Green Networks, Energy Efficiency, Smart Grid, Vehicular Networks, and Machine Learning applications. Key interests include network security, privacy-preserving systems, and edge computing. Recent work emphasizes digital twins, federated learning, and resilience in smart grids. Publications span 5G/6G, blockchain for energy systems, and AI-driven network optimization. Notable contributions include privacy-preserving pricing schemes and secure vehicular edge computing frameworks. Awards include three Best Paper Awards (IEEE SCALCOM 2015, IEEE CS CLOUD 2016, IEEE ICCT 2019) and the 2020 IEEE TCGCC Outstanding Young Researcher Award. She is an IEEE Senior Member since 2019. Leadership roles: Vice-Chair of IEEE TCGCC SIG on Green AI (2020–present), Member of UiO’s AI/ML Study Programs Working Group. Supervises students in Energy Informatics and leads projects like CRISP (NFR-funded) and PriTEM. Research groups: Digital Infrastructure and Security (DIAS) at UiO and Simula’s Center for Resilient Networks. Active in organizing summer schools on Energy Informatics and Green Computing.

• Nanoelectronics
• Analog and Digital Circuits
• Signal Processing
• +3 more

Jørgen Andreas Michaelsen is an Associate Professor at the Department of Informatics, University of Oslo. He is affiliated with the Nanoelectronics (NANO) research group. His research focuses on nanoelectronic systems, analog and digital circuit design, radar systems, wireless sensor networks, and multimedia networking. He holds a Cand.Scient. (Master's equivalent) in Informatics from the University of Oslo, as evidenced by his 2006 thesis titled Suppression of ΔΣ DAC Quantisation Noise by Bandwidth Adaptation . His recent work (2017) includes low-power radar SoC designs for non-contact vital signs detection. Earlier contributions span topics like VCO linearization for ADCs (2013), low-power sensor interfacing (2011), and multimedia streaming optimization (2006–2007). His publications often appear in top-tier conferences such as IEEE ISSCC, NEWCAS, and Norchip, reflecting expertise in both hardware and system-level design. Michaelsen collaborates extensively with industry partners and colleagues on interdisciplinary projects, bridging nanoelectronics with practical applications in healthcare monitoring and wireless communication. His work emphasizes energy-efficient, high-performance circuit solutions for emerging technologies.

• Electrical Engineering
• Computer Engineering
• Signal Processing
• +7 more

Ming Zhu is an Assistant Professor in Residence in the Department of Electrical and Computer Engineering at the University of Nevada, Las Vegas (UNLV). His work bridges electrical engineering and computer science to solve real-world problems in transportation, industrial systems, and healthcare. His research interests include Signal Processing , Machine Learning , Unmanned Aerial Vehicles (UAVs) , and Edge Computing . He applies these to Rail Infrastructure Monitoring , Industrial Fault Detection , and Health Monitoring Systems , using technologies like LiDAR, acoustic sensors, and generative models. Analysis of recent publications reveals a focus on non-invasive rail track measurement (using UAVs and LiDAR), sound-based malfunction detection in machinery, and efficient edge computing for video streaming and healthcare applications. His work demonstrates a strong trend towards practical, real-time systems for critical infrastructure.

Hammad MazharView profile

Assistant Professor

• IoT Systems
• Security
• Privacy
• +4 more

Hammad Mazhar is an Assistant Professor in the Department of Mathematical Sciences at the University of Northern Colorado (UNC), affiliated with the College of Natural and Health Sciences. He holds a Ph.D. in Computer Science from The University of Iowa and a B.S. in Computer Science from Lahore University of Management Sciences (LUMS), Pakistan. His research focuses on IoT Systems, Security, Privacy, and Formal Verification. Professional experience includes roles as Co-Instructor at The University of Iowa (2023), Graduate Research Assistant (2016–2023), and Security Research Intern at Minim Inc. (2019). He has also served as a Teaching Assistant and Research Assistant at LUMS (2014–2016). His research emphasizes practical security solutions for IoT devices, including policy enforcement mechanisms, vulnerability analysis in enterprise networks, and characterizing smart home IoT traffic. Key publications include work on Maverick (a platform-agnostic IoT policy system) and studies on WPA2-Enterprise security flaws. No scientific awards are explicitly listed, but his active publication record in top venues like WiSec, CCS, and INFOCOM highlights his contributions to cybersecurity and IoT research. Grant information is not detailed in the provided text.

• Data Privacy
• Mobile Applications
• Web Analytics
• +4 more

George Prezerakos is a Professor at the Department of Electrical and Computer Engineering, National Technical University of Athens. His work focuses on data privacy, mobile applications, web analytics, and network engineering. He holds the email prezerak@uniwa.gr . Research interests include analyzing the societal impact of digital technologies, predicting human behavior through web data, evaluating market competition policies in telecommunications, and addressing the digital divide exacerbated by economic crises. He has published extensively on topics ranging from secure distributed systems to context-aware service engineering. His research demonstrates a unique blend of technical innovation and socio-economic analysis. For example, his work on predicting election outcomes via Google Trends data bridges computational methods with political science, while studies on mobile app privacy critique modern digital economy practices. He also investigates infrastructure challenges in deploying next-generation networks in complex geographic regions like Greece. Advising and grants: No specific advising or grant details are provided in the text. His contributions are primarily through academic publications and conference presentations. Labs/Teams: Affiliated with the Department's research groups focusing on telecommunications, cybersecurity, and context-aware systems, though specific lab names are not mentioned.

Viktoria Pammer-SchindlerView profile

Associate Professor

• Human-Computer Interaction (HCI)
• Educational Technology (EdTech)
• AI in Education
• +7 more

Assoc. Prof. Viktoria Pammer-Schindler is an Associate Professor in Human-Computer Interaction (HCI) and Educational Technology (EdTech) at Graz University of Technology. She is Deputy Head of the Institute of Human-Centred Computing and a research area head at the Know-Center. Her work focuses on interactive AI for productivity, learning, and socio-technical systems design. She teaches courses such as 'Designing Interactive Systems' and 'Conversational Systems,' and has received recognition for teaching excellence. Her research spans language-based interaction, workplace learning, and ethical AI, with over 50 peer-reviewed publications. She actively serves in roles like Special Issue Editor for IEEE Transactions on Technologies for Learning and President of the International Alliance to Advance Learning in the Digital Era. Affiliations: Graz University of Technology (Institute of Human-Centred Computing), Know-Center Research Areas: HCI, EdTech, AI ethics, conversational agents, workplace learning analytics, and socio-technical systems Her awards include the 2023 Outstanding Paper Award at Bled eConference and multiple teaching nominations. She advises over 20 graduate students and leads projects funded by national and EU grants. Current research explores generative AI in creativity, voice-based interaction, and ethics in professional learning technologies. She has supervised impactful theses on topics like GenAI for creative collaboration and AI-enabled environments for well-being. Her work bridges theory and practice through field studies in call centers, apprenticeships, and SMEs, emphasizing user-centered design principles.