Find Academic Supervisors

Akanksha SainiView profile

Lecturer

• Cybersecurity
• Health Informatics
• Distributed Computing
• +4 more

Dr. Akanksha Saini is a Lecturer at RMIT University's School of Accounting, Information Systems, and Supply Chain. Her research focuses on cybersecurity, distributed systems, health informatics, and blockchain applications in healthcare. She holds an ORCID identifier (0000-0002-7191-2854) and is open to supervising Masters and PhD students in cyber security and related fields. Research Interests: Cybersecurity and Privacy Blockchain Technology in Healthcare Artificial Intelligence Applications Quantum Computation Supply Chain Management Health Informatics Systems Key Contributions: Pioneering work on securing distributed networks for IoT intrusion detection Developed blockchain-based frameworks for medical data sharing and access control Established collaborations with industry and international researchers Publications Highlight: Recent articles (2021–2025) emphasize blockchain applications in healthcare, federated learning, and cybersecurity challenges in the GenAI era. Over 30+ peer-reviewed papers in journals like Journal of Information Security and Applications and IEEE Internet of Things Journal . Supervision and Collaboration: Available to supervise research in cyber security and AI Industry partnerships align with national research priorities Co-authored papers with global collaborators in cryptography and health informatics Labs and Teams: Engaged in interdisciplinary projects at RMIT's School of Accounting, Information Systems, and Supply Chain, with a focus on real-world industry applications.

Michael DevetsikiotisView profile

Professor

• Telecommunication Networks
• Smart Grid Communications
• Cyber-Physical Systems
• +5 more

Michael Devetsikiotis is a Professor and Chair of the Department of Electrical and Computer Engineering at the University of New Mexico (UNM), part of the School of Engineering. He holds a Ph.D. from North Carolina State University (1993). His career includes roles as an Assistant/Associate Professor at Carleton University (1996–1998), Associate/Professor at North Carolina State (2000–2016), and leadership in UNM's ECE Department since 2016. He specializes in telecommunication networks, smart grids, IoT, and quantum information science. Education: Ph.D. in Electrical Engineering, North Carolina State University, 1993 M.S. in Electrical Engineering, North Carolina State University, 1990 Dipl. Ing. in Electrical Engineering, Aristotle University of Thessaloniki, Greece, 1988 Research Interests: Focuses on network design, smart grid communications, cyber-physical systems, and quantum technologies. He has published over 180 refereed papers and secured funding from NSF, NSERC, Cisco, and IBM. Notable projects include leading UNM’s Quantum Information Science program and managing the $20M NSF EPSCoR “SMART” Grid initiative. Articles Trends: Recent work emphasizes AI-driven network management (e.g., LSTM models for 5G/6G), blockchain for secure IoT/satellite systems, and quantum computing. Earlier contributions addressed EV charging infrastructure and smart grid resilience. Scientific Awards: IEEE Fellow (2012) NC State ECE Alumni Hall of Fame (2017) Advising & Grants: Directed UNM’s NSF Quantum Computing Faculty Fellowship (2020), enabling hires in quantum engineering. Previously managed a 800-student ECE graduate program at NC State. Active in IEEE leadership roles, including Distinguished Lecturer (2008–2011) and Chair of flagship conference committees. Labs & Teams: Spearheaded UNM’s IBM Q-Hub affiliation (2020), advancing quantum research collaboration. Leads interdisciplinary teams for smart city defense, blockchain energy markets, and 6G network automation.

Jimmy BellView profile

Professor

• Optimal Health
• Accelerated Ageing
• Mitochondrial Function
• +5 more

Professor Jimmy Bell at the University of Westminster leads the Research Centre for Optimal Health, focusing on mechanisms of phenotypic flexibility, metabolic dysfunction, and accelerated ageing. His interdisciplinary research integrates quantum biology, metabolic phenotyping, and AI-driven analytics. As Principal Investigator for the UK Biobank Enhanced Phenotyping study, he develops novel assessment technologies for metabolic health. Research interests span mitochondrial function, adipose tissue biology, obesity pathogenesis, and metabolic disorders. His work bridges quantum-scale biological processes with population-level health outcomes, emphasizing technological innovation in health assessment. Publications demonstrate strong focus on metabolic imaging, genetic epidemiology, and computational modeling. Recent work utilizes deep learning for disease prediction, MRI-based phenotyping, and targeted cancer therapies. Longitudinal analyses in cohort studies reveal mechanisms linking adiposity to chronic diseases. Professional activities include grant review for major UK research councils, PhD examination internationally, and leadership in large-scale biobank operations. Leads multidisciplinary teams at the Research Centre for Optimal Health and collaborates with Health Data Science groups to develop novel assessment frameworks for metabolic health.

Jeremy SingerView profile

Associate Professor

• Systems Software
• Garbage Collection
• Compilers
• +4 more

Jeremy Singer is a Reader in Programming Language Implementation at the School of Computing Science, University of Glasgow. He specializes in systems software, compilers, garbage collection, and secure runtime environments. His research focuses on advancing memory management techniques, many-core parallelism, and edge computing. Singer holds a PhD from the University of Cambridge (2006) in Static Program Analysis based on Virtual Register Renaming. He is a Senior Member of the ACM and a Fellow of the BCS. His academic roles include supervising PhD students in areas such as quantum memory management, federated graph neural networks, and secure memory systems. He has led multiple EPSRC-funded projects, including M4Secure (2023-2026), Capable VMs (2020-2024), and FRuIT (2017-2019). He teaches courses like COMPSCI1016 (Computational Thinking) and COMPSCI4021 (Functional Programming in Haskell). Singer’s research spans compiler design, runtime systems, and security. Notable contributions include work on SSA-based compiler techniques, Raspberry Pi cluster systems, and secure microPython implementations. He has authored over 80 publications and co-developed MOOCs on functional programming and data science. His awards include Fellow of the BCS and Senior ACM Membership. Current research interests include secure memory management, compiler optimizations for heterogeneous architectures, and edge computing security.

Bongjin KimView profile

Associate Professor

• Secure Hardware Design
• Machine Learning
• Data Mining
• +6 more

Prof. Bongjin Kim is an Associate Professor in the School of Electrical Engineering at KAIST. Previously, he held a position as Assistant Professor at UCSB. His research focuses on secure hardware design, machine learning, and alternative computing architectures, including Ising machines and processing-in-memory systems. He leads the Kim Circuit Research Lab, which designs novel VLSI circuits for AI, robotics, and optimization problems. Education: PhD, University of Minnesota (ECE); MS, Pohang University of Science and Technology (ECE). He has advised over 20 graduate and undergraduate students, with notable advisees including Dr. Jooyoung Bae (PhD 2025) and Dr. Yihao Wu (PhD 2025). His work has been recognized with awards such as the NSF CAREER Award (2023) and the NRF Outstanding Young Scientist Grant (2025). Recent research includes developing a 28nm Ising machine for combinatorial optimization (A-SSCC 2024), a scalable bit-serial accelerator for PDEs (TCAS-I 2024), and a reconfigurable compute-in-memory macro (JSSC 2024). He serves on technical committees for ISSCC, A-SSCC, and ESSERC, and chairs sessions at ESSERC 2025 and A-SSCC 2025. Lab activities include the Basic Research Lab (NRF-funded) for Ising Foundation Model development and the C2 research project on ML ASIC accelerators. His group collaborates with institutions like SLAC, IME (A*STAR), and KAIST, fabricating over 30 test chips using 28nm/65nm processes.

Ammar BelatrecheView profile

Senior Lecturer

• bio-inspired intelligent systems
• machine learning
• spiking neural networks
• +5 more

Dr. Ammar Belatreche is a Senior Lecturer in Computer Science and Programme Leader for the MSc Advanced Computer Science at Northumbria University's Department of Computer and Information Sciences. He joined Northumbria University in May 2016 after previous positions as a Research Associate and Lecturer at Ulster University. He is an active member of the Computational Intelligence and Visual Computing (CIVC) research group. Dr. Belatreche earned his PhD in Computer Science from Ulster University in 2007. His professional qualifications include: Member of the Association of Computing Machinery (ACM) since 2012 Fellow of the Higher Education Academy (FHEA) since 2010 Member of the Institute of Electrical & Electronic Engineers (IEEE) since 2009 His research focuses on bio-inspired intelligent systems, machine learning, spiking neural networks, face detection and recognition, structured and unstructured data analytics, capital markets engineering, and image processing. Dr. Belatreche has extensive experience across academic and R&D in these areas, leading numerous research and consultancy projects. His recent work demonstrates a strong emphasis on neuromorphic computing, particularly spiking neural networks and their applications in computer vision, financial analysis, and biometrics. Analysis of his recent publications shows a clear trend toward advancing spiking neural network architectures, with particular focus on quantization, pruning, and binary implementations to improve efficiency. His research spans multiple domains including computer vision (face recognition, palm-vein recognition), financial technology (stock price manipulation detection), and neuromorphic engineering. Many of his recent papers (2024-2025) appear in top-tier conferences like ICLR and journals like IEEE Transactions on Neural Networks and Learning Systems. Dr. Belatreche has received professional recognition including: Fellowship with the Higher Education Academy (FHEA) Role as Associate Editor for the journal Neurocomputing He has successfully supervised or co-supervised 8 PhD students to completion and serves as a Program Committee Member and reviewer for numerous international conferences and journals. As Programme Leader for the MSc Advanced Computer Science, he plays a significant role in shaping postgraduate education in computer science at Northumbria University. His research group work bridges theoretical advances in neural computation with practical applications across multiple domains. Based in CIS 305 at Northumbria University's Newcastle campus, Dr. Belatreche continues to advance research in neuromorphic computing and its applications while contributing to academic leadership through his programme leadership role.

Christopher AyalaView profile

Professor

• Superconductor Electronics
• Adiabatic Computing
• Quantum Computing
• +2 more

Christopher Ayala is a Professor at Yokohama National University's Institute of Advanced Sciences, where he directs research in the Quantum Information Research Center. His work focuses on energy-efficient superconductor computing architectures, particularly adiabatic quantum-flux-parametrons (AQFPs) for next-generation computing systems. Dr. Ayala's group develops superconducting processors, memory systems, and control architectures for quantum computing applications. Research areas include: Adiabatic superconductor microprocessors Fully homomorphic encryption hardware Quantum computing control systems Superconductor logic families Cryogenic computing architectures His team pioneered the world's first adiabatic superconductor microprocessor, recognized by IEEE Spectrum and Superconductor Week. Dr. Ayala received the Best Young Scientist Paper Award at the European Solid-state Device Research Conference for his work on nanoelectromechanical switches.

Anthony DanalisView profile

Academic

• High-Performance Computing (HPC)
• Performance Analysis and Optimization
• System Benchmarking
• +4 more

Anthony Danalis is a Research Assistant Professor at the University of Tennessee's Innovative Computing Laboratory (ICL), affiliated with the Department of Electrical Engineering and Computer Science. His research focuses on high-performance computing (HPC), including performance analysis, system benchmarking, compilers, MPI, and accelerators. He holds a Ph.D. and two M.S. degrees in Computer Science from the University of Delaware and the University of Crete, along with a B.S. in Physics from the University of Crete. Education: Ph.D. in Computer Science, University of Delaware M.S. in Computer Science, University of Delaware M.S. in Computer Science, University of Crete B.S. in Physics, University of Crete Research Interests: High-Performance Computing (HPC) Performance Analysis and Optimization System Benchmarking Compilers and Runtime Systems Parallel Programming Models (e.g., MPI) Accelerator Technologies Publications Highlight Trends in: Advancements in the PAPI library for exascale computing Dataflow-based execution for scientific applications Hardware performance counter analysis Compiler-driven optimizations Scientific Awards: Best Research Poster Finalist at SC 2017 Advising and Grants: No formal advisees listed Contributions to ICL's leadership and collaborative projects Labs and Teams: Innovative Computing Laboratory (ICL) Participation in projects like DAGuE, DPLASMA, and SHOC

Kin K. LeungView profile

Professor

• Wireless Communications
• Communication Networks
• Machine Learning
• +4 more

Kin K. Leung is the Tanaka Chair Professor in the Electrical and Electronic Engineering and Computing Departments at Imperial College London. He serves as the Head of the Communications & Signal Processing Group (2009-2024) and Deputy Director of the University Defence Research Centre in Signal Processing. Previously, he held senior technical roles at AT&T Bell Labs and Lucent Technologies. Education: B.S. from Chinese University of Hong Kong (1980), M.S. and Ph.D. from University of California, Los Angeles (1982, 1985). Research Interests: Focuses on wireless technologies, communication networks, stochastic modeling, machine learning, optimization, and emerging quantum computing applications. His work integrates theoretical frameworks with practical implementations in multi-antenna systems, cross-layer network designs, and distributed quantum architectures. Publication Trends: Recent works (2021-2025) demonstrate a strong focus on quantum computing integration with networking systems, federated learning optimizations for edge devices, and reinforcement learning solutions for resource allocation in wireless environments. Awards and Honors: Fellow of Royal Academy of Engineering (2022) IEEE Fellow (2001) IET Fellow (2021) Royal Society Wolfson Research Merit Award (2004-2009) IEEE Communications Society Leonard G. Abraham Prize (2021) IEEE Best Survey Paper Award (2022) Grants and Leadership: Principal Investigator for EPSRC TITAN/HASC Com Hubs, DCIT Centre, and DQC & App (distributed quantum computing). Leads the Communications & Signal Processing Group and co-directs the School of Convergence Science in Space, Security and Telecoms.

Yulong HuangView profile

Adjunct Assistant Professor

• Magnetic Materials
• Superconductivity
• Nanomaterials
• +3 more

Yulong Huang is an Adjunct Assistant Professor of Research in the Department of Chemical and Biological Engineering and a Research Scientist in the Department of Mechanical and Aerospace Engineering at the University at Buffalo, State University of New York. His work focuses on advanced materials science, particularly magnetic materials, superconductivity, and nanomaterials with applications in energy, electronics, and biomedical systems. Research interests include molecular conductors, 2D materials, thermal insulation composites, and functional materials for wearable and flexible electronics. He has contributed to breakthroughs in lithium-ion battery technology, magnetic receptor studies, and high-temperature ceramic aerogels. Huang's interdisciplinary approach bridges chemical engineering, mechanical engineering, and applied physics. Key achievements include developing printable copper conductors, proton-controlled ferroelectrics, and pressure-tuned magnetic systems. His lab emphasizes scalable fabrication techniques for next-generation materials with tailored properties for extreme environments.

Bernd MeyerView profile

Professor

• Computational Chemistry
• Materials Science
• Surface Chemistry
• +6 more

Prof. Dr. Bernd Meyer is a Professor of Computational Chemistry at the Department of Chemistry and Pharmacy, Friedrich-Alexander University Erlangen-Nuremberg. His research bridges theoretical and experimental approaches to investigate nanomaterials, surface chemistry, and molecular dynamics. Computational Chemistry Materials Science Surface Stability Molecular Dynamics Nanomaterials Photovoltaics Organic-Inorganic Hybrids Recent publications focus on adsorption mechanisms of molecules on metal oxides, design of porphyrin-based hybrids with tunable optoelectronic properties, and algorithm optimizations for ab initio molecular dynamics. His work integrates first-principles simulations with experimental validation to address challenges in energy materials and surface engineering. Contact: bernd.meyer@fau.de | Room 2.308, Nägelsbachstraße 25, Erlangen | Phone: +49 9131 85-20403

Juan UriagerekaView profile

Professor

• Syntax
• Biolinguistics
• Formal Language Theory
• +3 more

Juan Uriagereka is a Professor of Linguistics at the University of Maryland, College Park, affiliated with the School of Languages, Literatures, & Cultures. His work bridges syntax, biolinguistics, and interdisciplinary science, particularly the intersection of language with physics and neurobiology. He co-edited Biolinguistic Investigations and the Formal Language Hierarchy and contributed to foundational research on matrix syntax and third-factor explanations in Minimalist Program theory. Research interests include algebraic syntax, formal language theory, and the neurophysiological underpinnings of linguistic structures. Recent publications explore domestication genomics, syntactic features in vector spaces, and the application of matrix mechanics to syntax. His outreach includes the Maryland Initiative for Literacy and Equity (MILE), advocating for linguistic diversity. He collaborates with researchers like Román Orús (physics) and Antonio Benítez-Burraco (biology), integrating computational models with linguistic theory. His work on 'matrix syntax' proposes novel frameworks for analyzing long-range syntactic correlations, linking syntax to quantum-inspired mathematical models.

• Quantum Computing
• Quantum Physics
• Atomic Physics
• +7 more

Servaas JJMF Kokkelmans is a full Professor at Eindhoven University of Technology (TU/e), where he leads the Coherence and Quantum Technology group within the Department of Applied Physics and Science Education. He serves as scientific director of the Center for Quantum Materials and Technology Eindhoven (QT/e), which he founded in 2018, and is a co-founder of the Eindhoven Hendrik Casimir Institute established in 2021. Kokkelmans also coordinates action line 1: Research and Innovation at Quantum Delta NL, demonstrating his national leadership in quantum technology. Professor Kokkelmans earned his MSc in Physics from TU/e in 1996 and completed his PhD on interacting atoms in clocks and condensates in 2000. Following postdoctoral research at JILA, University of Colorado (USA) and Laboratoire Kastler Brossel, ENS (France), he returned to TU/e in 2004 as an Assistant Professor, became Associate Professor in 2017, and was promoted to full Professor in 2023. His research focuses on strongly-interacting quantum gases and neutral atom quantum computing, with particular expertise in manipulating interatomic interactions. Kokkelmans' work impacts quantum materials development, quantum computing, and fundamental understanding of superfluidity. His expertise spans many-body properties of Fermi and Bose gases, ultracold collisions, Feshbach resonances, ultracold molecules, Efimov trimers, ultracold plasmas, and Rydberg atoms. Analysis of his recent publications reveals a strong progression from fundamental quantum gas studies to practical quantum computing implementations, with increasing emphasis on optical tweezer arrays, Rydberg atom systems, and hybrid quantum architectures. Professor Kokkelmans has received numerous prestigious awards: NWO Vici Award: 'From neutron star to quantum computer' (2015) NWO Vidi Award: 'Atomic gases with strong interactions' (2003) Teacher Award of Appreciation Applied Physics (2021) Visiting Scientist Fellowship JILA (2016) Eindhoven University of Technology Fund for Excellence (2010) As principal investigator of the KAT-1 project 'Rydberg Atom Quantum Computing' (2020-2028), Kokkelmans leads a major research initiative in neutral atom quantum computing. His research group has secured substantial funding from NWO and university sources, supporting numerous PhD students and postdoctoral researchers. His educational contributions include teaching 'Hybrid quantum computing,' 'Quantum Optics and Quantum Information,' and 'Ultracold quantum physics' courses. Professor Kokkelmans founded the Center for Quantum Materials and Technology Eindhoven (QT/e) as a hub for quantum research at TU/e. His Coherence and Quantum Technology group combines experimental and theoretical approaches to quantum systems, with particular strength in ultracold atomic physics. The group's work bridges fundamental quantum phenomena with practical quantum technology applications, positioning TU/e as a significant player in the global quantum computing landscape.

• Information Visualization
• Software Systems
• Cybersecurity
• +3 more

Bill Buchanan is a Professor at the School of Computing Engineering and the Built Environment, Edinburgh Napier University, and a member of the Centre for Algorithms, Visualisation and Evolving Systems. His work spans Information Visualization , Software Systems , Cybersecurity , and AI , focusing on innovative solutions for complex data challenges. Research Interests: Information visualization for hierarchical data, cybersecurity frameworks, machine learning in industrial IoT, and post-quantum cryptographic systems. Projects: Supervised PhD projects on visualizing overlapping classification hierarchies and biological network inference. Currently leads research in AI-driven human-robot interaction and secure Dockerized architectures. Publications: 15+ recent works on quantum agents, GANs for anomaly detection, homomorphic encryption, and advanced cryptographic techniques. Collaborations: Engages with biologists, AI researchers, and cybersecurity experts across institutions.

Wim CasteelsView profile

Lecturer

• Data Science
• Machine Learning
• Artificial Intelligence
• +4 more

Wim Casteels is a Lecturer and researcher at AP University College, specializing in AI and data science. He transitioned from quantum physics research at the University of Antwerp and Paris to roles in data science at Argenta's Data Analytics Office and imec's IDLab research group. His work focuses on applying AI to education, transportation, and environmental monitoring. He leads projects like AI4UX (user pattern detection), LAP! (learning analytics dashboards), and AI4Care (AI for youth care support). Education: PhD in Physics (University of Antwerp), followed by postdoctoral research on quantum systems in Antwerp and Paris. Transitioned to data science roles in industry and academia. Research Interests: Machine Learning, Deep Learning, Learning Analytics, and AI applications in education and transportation. Projects include developing AI-driven road weather models using vehicle sensor data, predictive student success models, and energy-efficient building control systems. His work emphasizes ethical AI implementation and data-driven decision-making. Key Projects: AI4UX (2023–2025), AHUMAIN (2023–2025), LAP! (2019–2023), and AI4Care (2024–2026). His research is supported by grants like the Industrial Research Fund. Labs/Teams: Part of AP University College's Media, Design and IT Knowledge Center, previously affiliated with imec's IDLab group and Argenta's Data Analytics Office.