Find Academic Supervisors

• Signal Processing
• Communications Engineering
• Radar Systems
• +5 more

Assoc. Professor Qinghua Guo holds a position at the University of Wollongong's School of Electrical, Computer and Telecommunications Engineering. He earned his PhD from City University of Hong Kong (2008) and has been affiliated with the University of Wollongong since 2019. His research focuses on signal processing, communications, radar systems, machine learning, and optical sensing, with notable contributions to graphical models and Bayesian inference. Prof. Guo is recognized as a top 2% influential scientist globally (Stanford University) and a leader in Electronics and Computer Science (Research.com). He serves as an Associate Editor for IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters, among other roles. His teaching spans undergraduate to postgraduate levels, including specialized subjects in engineering and information sciences. His recent research emphasizes integrated sensing and communication systems, federated learning, and secure beamforming in 5G/6G networks. He has supervised over 30 PhD and Master’s students in areas like MIMO systems, signal processing for IoT, and quantum sensing. Key funded projects include AFDM-SCMA (2025–2028) for IoT connectivity and Grant-Free Multiple Access for LEO satellite networks (2023–2027). His work bridges theoretical advancements with practical applications in robotics, energy systems, and defense technologies.

• Blockchain Technology
• Internet of Things (IoT)
• Data Security
• +3 more

Ramachandran Gowri is a researcher specializing in blockchain technology, IoT security, and distributed systems. Her work focuses on advancing blockchain applications for social good, optimizing energy efficiency in mining, and enhancing cybersecurity in decentralized systems. She collaborates with institutions such as Queensland University of Technology (QUT) and has published extensively in top-tier conferences and journals like IEEE and Springer. Her research bridges theoretical frameworks with practical implementations, addressing challenges in smart contracts, data storage optimization, and supply chain management. Key research areas include privacy-preserving blockchain architectures, decentralized identity systems, and edge computing integration. She has contributed to frameworks like the 'Reference Architecture for Blockchain-based Social Good Applications' and developed protocols such as nPPoS for blockchain storage efficiency. Her work on cryptocurrency mining strategies and quantum-resilient IoT protocols showcases her interdisciplinary approach. Recent publications highlight her focus on mitigating cybersecurity threats in software supply chains and optimizing energy consumption in blockchain networks. Collaborations with experts in computer science and engineering underscore her role in advancing real-world applications of distributed ledger technologies.

Gulhan BizelView profile

Assistant Professor

• Data Science
• Marketing Analytics
• Digital Marketing
• +2 more

Dr. Gulhan Bizel serves as Assistant Professor, Director & Chair of the Data Science Institute at Saint Peter's University, overseeing six MS/PhD programs. She holds a Ph.D. in Management from Maltepe University, an MBA from Yeditepe University, and a B.S. in Chemistry from Bogazici University. With extensive industry experience at Whirlpool, Indesit Company, and Kenwood, she brings practical insights to her academic work. Her research focuses on data science applications in marketing analytics, healthcare, social media trends, and business intelligence. She has published extensively on topics including COVID-19 impacts, social determinants of health, and digital marketing strategies. Dr. Bizel teaches courses spanning marketing principles, business operations, data analytics, and digital marketing at both undergraduate and graduate levels. Her scholarly contributions demonstrate strong interdisciplinary approaches combining data science with business applications. Awards & Certifications: NSF I-Corps Hub: Northeast Region NJIT Propelus Program Upsilon Pi Epsilon Society Membership IBM Skills Academy Instructor Badges (IoT, AI, Data Science, Quantum Computing) She actively serves on university committees including Faculty Senate and Enrollment Committee, and volunteers for SCORE Small Business Organization.

• High-Energy Physics
• Particle Physics
• Proton-Proton Collisions
• +5 more

Muammer Altan Çakır is a Professor in the Department of Physics Engineering at Istanbul Technical University, actively engaged in high-energy physics research with significant contributions to the CMS Collaboration at CERN. His work focuses on proton-proton collisions, Higgs boson physics, and top quark studies using Large Hadron Collider data. His research interests span experimental particle physics with emphasis on proton-proton collisions , Higgs boson characterization , lepton physics , and transverse momentum analysis . Recent work explores charm baryon production, Drell-Yan processes, and muon identification techniques using advanced multivariate methods in the CMS detector. Analysis of his 15 most recent publications reveals a strong focus on precision measurements in high-energy collisions, particularly in Higgs physics (3 publications), top quark physics (2), and detector optimization (2). His work consistently addresses fundamental questions in the Standard Model through advanced statistical techniques and large-scale data analysis. Doktora sonrası araştırma bursu (2010) Landes Baden Württenberg Doktorarbeit Stipendium (2006) LPC Fall Guest Visitor Faculty (2017) Multiple Performans ödülü awards (2012, 2013, 2015) Professor Çakır has supervised 15 students and leads multiple research projects including GPU-based distributed computing platforms for big data processing, real-time predictive maintenance systems, and deep learning applications for top quark spin correlation studies. His current projects integrate generative AI with domain-specific physics research while developing scalable open-source big data architectures for industrial applications. His laboratory work centers on CMS detector data analysis, with recent focus on online data visualization tools and multivariate techniques for particle identification. Current projects explore GPU-accelerated computing frameworks and generative AI applications for physics-informed design systems.

Gregor WeihsView profile

Professor

• Quantum Photonics
• Quantum Information
• Semiconductor Optics
• +3 more

Gregor Weihs is Vice-Rector for Research at the University of Innsbruck, holding a full professorship in Photonics at the Institute for Experimental Physics. He directs the Cluster of Excellence Quantum Science Austria and previously served as Austrian Science Fund (FWF) Vice-President and interim President. His academic journey includes roles at Stanford University, the University of Tokyo, and the University of Waterloo, where he held a Canada Research Chair in Quantum Photonics. Education: MSc (1994, University of Innsbruck), PhD (2000, University of Vienna) awarded 'sub auspiciis praesidentis.' He completed habilitation in Experimental Physics in 2005 at the University of Vienna. Research focuses on quantum photonics, semiconductor optics, and foundational quantum mechanics. Key projects include entangled photon pair generation from nonlinear waveguides, quantum dots, and semiconductor microcavities. He explores quantum communication, many-body interference, and hypercomplex quantum mechanics testing. Awards: Wilhelm Exner Medal, ERC Starting Grant, Canada Research Chair Leadership: Department Head of Experimental Physics (2013–2021), Faculty Council Chair, IQOQI Events Director His work bridges theory and experiment, with contributions to integrated quantum devices and precision tests of quantum foundations.

• Distributed Systems
• Networks
• Security
• +5 more

Patrick Thomas Eugster is a Full Professor of Computer Science at the Università della Svizzera italiana (USI), leading the Software Systems (SWYSTEMS) group within the Computer Systems Institute, which he co-founded. Previously, he held faculty positions at Purdue University (2005-2016) and TU Darmstadt (2014-2017), with a visiting role at MIT (2012/2013). His research focuses on distributed systems, networking, security, and programming languages, with over 160 publications and significant industry collaborations with companies like Amazon, Google, and Facebook. Education: He holds an M.S. (1998) and Ph.D. (2001) in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL). Research Interests: His work addresses distributed systems challenges such as fault-tolerance, security, and efficient resource management. Recent topics include datacenter reliability, quantum network verification, and confidential computing. His team explores intersections between systems, languages, and networks to build robust and secure distributed applications. Publications: Recent work spans topics like failure detection in datacenters, formal verification of systems, and network congestion control. Key venues include USENIX ATC, ACM SIGMETRICS, IEEE Network, and TACAS. His 2025 work on failure detection and TCAM encoding exemplifies contributions to system resilience and hardware optimization. Awards: Jean-Claude Laprie Award (2025), TACAS Best Paper (2025), ERC Consolidator Grant (2014), NSF CAREER Award (2007). Advising & Grants: Supervised over 20 PhD and postdoctoral researchers. Active grants include EU Horizon Europe CloudStars, Swiss National Science Foundation, and industry partnerships with Cisco and SAP. Labs & Teams: Directs the SWYSTEMS group, collaborating on projects like secure cloud analytics, quantum network verification, and datacenter monitoring. Former students hold roles at universities, tech firms, and startups.

Frank LeymannView profile

Professor

• Software Architecture
• Pattern Languages
• Service-Oriented Computing
• +8 more

Frank Leymann is a Professor of Computer Science at the University of Stuttgart, where he serves as Director and Founder of the Institute of Architecture of Application Systems. His career spans academia and industry, including 20 years at IBM Germany as a Software Architect. Research Focus: Workflow Management, Service Computing, Cloud Computing, Quantum Computing, Pattern Languages, Digital Humanities. Standards: Co-author of BPEL, BPMN, WS-RF, TOSCA, Human Task specifications. His work on quantum computing emphasizes hybrid quantum-classical applications and practical integration challenges. He pioneered the OASIS cloud standard TOSCA and developed the open-source OpenTOSCA platform, which has over 1,000 downloads. Scientific awards include an Honorary Doctorate from the University of Crete (2015), IBM Distinguished Engineer (2000), and IBM Academy of Technology membership (1996). Google Scholar cites his work over 43,300 times (H-Index 89), ranking him among the world's top computer scientists.

Mark A IwenView profile

Associate Professor

• Computational Harmonic Analysis
• Mathematical Data Science
• Signal Processing
• +4 more

Mark A Iwen is an Associate Professor at Michigan State University, holding dual appointments in the Department of Mathematics and the Department of Computational Mathematics, Science and Engineering (CMSE) . His research focuses on computational harmonic analysis, mathematical data science, signal processing, and algorithms for analyzing high-dimensional datasets. He has contributed to advancements in sparse Fourier transforms, compressive sensing, and sublinear-time algorithms for large-scale data. Key research themes include: Efficient algorithms for high-dimensional PDEs and spectral methods Phase retrieval and inverse problems in imaging Optimization of tensor decompositions and dimensionality reduction techniques Development of sparse approximation methods with theoretical guarantees His recent work emphasizes applications in: Sublinear-time algorithms for function approximation Terminal embeddings for manifold data Fast JL embeddings with bi-Lipschitz properties Tensor completion and low-rank approximations Notable contributions include: Development of Sparse Harmonic Transforms for functions of many variables Advancements in distributed SVD algorithms for large networks Empirical and theoretical analysis of phase retrieval techniques Efficient sparse FFT implementations (e.g., DMSFT, GFFT) Iwen collaborates on open-source code projects, including sparse FFT libraries and phase retrieval tools. His work bridges mathematical theory with practical applications in engineering and computational science.

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.

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.

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.

Frauke LiersView profile

Professor

• Optimization under Uncertainty
• Distributionally Robust Optimization
• Quantum Computing
• +5 more

Prof. Dr. Frauke Liers holds the Professorship of Optimization under Uncertainty & Data Analysis at the Department of Data Science (DDS), Friedrich-Alexander-University Erlangen-Nürnberg. Her research focuses on robust and distributionally robust optimization, mathematical programming, and applications in energy systems, healthcare logistics, and quantum computing. Email: frauke.liers@fau.de ResearchGate: Frauke Liers Research Interests span optimization under uncertainty, data-driven mathematical programming, and interdisciplinary applications. Key areas include: Distributionally robust optimization with scenario reduction and chance constraints Quantum computing optimization for gate routing and noise suppression Energy system modeling (photovoltaics, gas networks, electricity networks) Healthcare logistics (patient transport scheduling under uncertainty) Nanoparticle technology and chemical process optimization Recent Publications emphasize: Advancements in quantum circuit optimization (2025) Explainable optimization methods (2024) Robust approaches for particle precipitation control (2024) Dynamic trajectory optimization (2023) Time-expanded models for network flows (2022)

Rui HeView profile

Professor

• Optical Studies of Nanostructures
• Raman Spectroscopy
• Condensed Matter Physics
• +3 more

Rui He is a Professor in the Department of Electrical & Computer Engineering at Texas Tech University, holding the Ed and Linda Whitacre Faculty Fellowship. His research focuses on optical and magnetic phenomena in nanostructures, particularly leveraging Raman spectroscopy to study low-dimensional materials and quantum systems. Education PhD in Applied Physics (2006), Columbia University MS in Applied Physics (2003), Columbia University BS in Engineering (1999), Fudan University His work spans two-dimensional magnets, spin-phonon coupling, and magnetic particle imaging technologies. Recent articles highlight computational modeling of magnetic sensors, phonon dynamics in van der Waals solids, and additive manufacturing of magnetic materials for healthcare applications. Scientific Award Ed and Linda Whitacre Faculty Fellow (2022)

• 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.