Find Academic Supervisors

H. Metin AktulgaView profile

Associate Professor

• High Performance Computing
• Parallel Computing
• Big Data Analytics
• +3 more

H. Metin Aktulga is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University's College of Engineering. His research focuses on high-performance computing, parallel algorithms, and numerical methods for large-scale scientific applications. He leads interdisciplinary projects involving collaborations with computational physicists and materials scientists to develop scalable software systems. His work includes the development of PuReMD, a reactive molecular dynamics code, and DOoC+LAF, a task-based middleware for data analytics. He explores parallel computing on emerging architectures, emphasizing energy efficiency and performance optimization. His research spans applications in molecular modeling, nuclear physics, and computational biology. Awards and grants are not explicitly listed, but his contributions are highlighted through collaborations with projects like MFDn (nuclear structure) and SHINES (electronic structure computations). He advises students in computational methods and leads efforts to automate force field optimization using machine learning and big data analytics. Labs and teams include the High-Performance Computing group at MSU, with active participation in interdisciplinary initiatives to bridge simulation and data-driven discovery in materials science and quantum systems.

Florian SchmausView profile

Researcher

• Operating Systems
• Distributed Systems
• Concurrency Platforms
• +4 more

Florian Schmaus is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-University Erlangen-Nuremberg. He is associated with the Faculty of Engineering and focuses on system software for future many-core architectures, runtime support systems, and concurrent programming platforms. His work is part of the SFB/TRR 89 Invasive Computing project, specifically Project C1 (iRTSS). Education includes a Master's in Computer Science from FAU, with thesis topics such as 'Porting Cilk to OctoPOS' and 'Development of a Customizeable Caching Service in Haskell.' Research interests span distributed systems, operating systems, concurrency platforms, and real-time systems. His work emphasizes invasive computing, runtime systems for many-core architectures, and hardware-software co-design. Recent publications focus on systems like iRTSS, Nowa, and SHARQ, addressing challenges in resource arbitration and parallel processing. Teaching activities include courses on real-time systems and applied system software, with roles in both lectures and practical labs since 2012. He has supervised multiple theses on topics like microparallelism runtimes and kernel-space system calls. Labs/Teams: Active in the ergoo group and the Invasive Computing SFB/TRR 89 project, contributing to the OctoPOS operating system and related research platforms.

Timo HönigView profile

Professor

• Operating Systems
• System Software
• Energy-Aware Computing Systems
• +3 more

Prof. Timo Hönig is a Professor leading the Bochum Operating Systems and System Software (BOSS) Research Group at Ruhr-Universität Bochum (RUB). Previously, he served as an Assistant Professor at Friedrich-Alexander-University Erlangen-Nürnberg (FAU), where he was part of Department of Computer Science 4. His research focuses on Energy-Aware Computing Systems, Operating Systems, and System Software design with applications in embedded and real-time systems. Key research projects include the DFG Collaborative Research Center/TR 89 (Invasive Computing) and the DFG SPP 1914 (Latency- and Resilience-Aware Networking). He has received notable awards such as the SOSP SRC Gold Medal (2019) and the ISORC Best Paper Award (2017). He actively contributes to conferences like ACM EuroSys and USENIX ATC, and has led initiatives like the Albatross runtime system for energy-efficient HPC clusters. Teaching includes courses on Energy-Aware Computing and Operating Systems Technology. His work bridges theoretical system software design with practical applications in energy efficiency and heterogeneous architectures. The BOSS group explores future system software challenges for many-core and NVM-based systems.

Barry C. SandersView profile

Professor

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +3 more

Barry C. Sanders is a Professor and Director of the Institute for Quantum Science and Technology at the University of Calgary. He holds additional roles as Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Technologies, a Thousand Talents Chair at the University of Science and Technology China, and Vajra Visiting Faculty at the Raman Research Institute. His research focuses on quantum computing, quantum algorithms, and optical implementations of quantum information tasks. Sanders has a PhD from Imperial College London (1987) and has held faculty positions at Macquarie University and the Australian National University. Education: BSc (University of Calgary, 1984), PhD (Imperial College London, 1987) Affiliations: Institute for Quantum Science and Technology, Alberta Major Innovation Fund Project His research interests include quantum-limited measurement, nonclassical light, quantum cryptography, and quantum algorithm development. He has pioneered work on Schrödinger cat states, qudit systems, and quantum error correction. Awards include Fellowships from the Institute of Physics, Optical Society of America, and Royal Society of Canada. His work bridges theory and application, with contributions to quantum technology commercialization and interdisciplinary collaborations. Editor-in-Chief, New Journal of Physics Past leadership roles: President of the Australian Optical Society, Founding Co-Chair of the Canadian Association of Physicists Division His recent publications explore quantum speedup in machine learning, topological quantum walks, and fault-tolerant quantum computing architectures.

Bingyao LiView profile

Assistant Professor

• Computer Architecture
• High-Performance Computing
• Multi-GPU Systems
• +4 more

Bingyao Li is an incoming tenure-track Assistant Professor at the University of California, Riverside's Computer Science and Engineering Department, starting Fall 2025. She is currently a fourth-year Ph.D. student at the University of Pittsburgh, advised by Dr. Xulong Tang. Her research focuses on computer architecture, particularly multi-GPU systems, virtual memory management, and address translation for high-performance computing. Educational Background: She holds a B.E. (2017) and M.S. (2020) from Tianjin University's College of Intelligence and Computing. Her Ph.D. work at Pitt emphasizes GPU architecture and system-level optimizations for large-scale applications. Research Interests: Her work spans advanced computer architectures, multi-GPU optimization, and parallel computing systems. She explores solutions like object-aware page management (OASIS), TLB enhancements (STAR), and dynamic page placement (GRIT) to improve multi-GPU performance. She also investigates system-level optimizations for large language models and GPU ecosystems from hardware to applications. Awards: She has received the CS50 Outstanding Research Fellowship (2022, 2023) and the SCI Fellowship from the University of Pittsburgh. Her contributions include internships at NVIDIA's Architecture Research Group and talks on multi-GPU computing at NVIDIA and Tianjin University. Future Work: As a faculty member, she plans to mentor PhD students in Winter/Spring/Fall 2026, focusing on next-generation GPU systems and high-performance computing challenges. Her lab will address scalability, efficiency, and emerging applications in parallel computing.

Rabah AoufiView profile

Senior Lecturer

• Digital Signal Processing
• Microcontroller Systems
• Control Systems
• +3 more

Rabah Aoufi is a Senior Lecturer in the Department of Engineering Technology & Industrial Distribution at the College of Engineering, Texas A&M University. His primary affiliation includes the Electronic Systems Engineering Technology program. He can be reached at raoufi@tamu.edu and is located in FERM 304AA. His work focuses on digital signal processing, microcontroller systems, control systems, and engineering entrepreneurship. Research interests span embedded systems design, real-time data processing, and innovative educational projects. His publications reflect expertise in both foundational engineering principles (e.g., signal processing fundamentals) and applied technologies (e.g., microcontroller programming and big data frameworks). His articles demonstrate a career-long engagement with evolving technologies—from foundational 1980s multiprocessor architectures to modern big data systems. No scientific awards or grants are explicitly mentioned in the provided materials.

• High-performance computing
• Modelling of Acoustic Wave devices
• Embedded system design
• +3 more

Dr. Glenn Matthews is a Senior Lecturer in the School of Engineering at RMIT University, specialising in Electrical and Computer Engineering. He holds positions in both academic and research capacities, including Principal Investigator roles at CSIRO and Smart Services CRC. His teaching responsibilities include coordinating undergraduate courses such as Introduction to Engineering Computing and Engineering Design modules. Dr. Matthews' research focuses on high-performance computing, acoustic wave device modeling using Finite Element Method (FEM), and embedded system design. Notable projects include developing FEM software for SAW device analysis and investigating asynchronous computing architectures for high-throughput systems. He has supervised numerous research projects spanning machine learning applications in clinical analysis, gas sensing technologies, and neuromorphic learning. His work integrates hardware-software co-design principles, with contributions to radar SLAM systems, mercury vapor sensors, and neural network frameworks like SwiftSpike. Dr. Matthews collaborates with industry partners through ARC Linkage Grants and maintains affiliations with IEEE and DSP/Embedded Systems groups. His research outputs include over 20 peer-reviewed articles, with impactful contributions to sensor technology, circuit design, and biomedical applications.

Ruth BreuView profile

Professor

• Quality Engineering
• Model Engineering
• Security Engineering
• +12 more

Ruth Breu is a Full Professor and Dean of the Faculty of Mathematics, Computer Science and Physics at the Universität Innsbruck, where she also leads the Quality Engineering research group. She has been a key figure in the Department of Computer Science since 2002 and served as its Head from 2013 to 2024. Her academic journey began with a PhD summa cum laude from the University of Passau in 1991, followed by a habilitation at the Technical University of Munich in 1999. Her research interests include: Quality Engineering Model and Security Engineering Requirements and Software Development Processes Enterprise Architecture Management Threat Intelligence and Digital Twins Her recent publications reflect a strong focus on model-based systems, automated programming assessment, security engineering, and digital twins in construction and energy systems. She frequently collaborates with researchers such as Michael Felderer, Clemens Sauerwein, and Philipp Zech, contributing to advancements in software testing, threat intelligence sharing, and cyber-physical systems. Notable awards include her PhD awarded summa cum laude. She has also been actively involved in national research governance, serving on the board of the Austrian Science Fund (FWF) from 2011 to 2020. She co-founded Txture GmbH in 2017 and holds advisory roles at Universität Passau and FH OST. Ruth Breu advises several students and leads a vibrant research group. Her leadership extends to organizing workshops and contributing to major conferences in software engineering and enterprise modeling. She is deeply engaged in both academic and applied research, bridging theory and practice in IT quality and security.

• Human-Computer Interaction (HCI)
• Interaction Design
• User-Centered Design
• +3 more

Dag Svanæs is a Professor of Human-Computer Interaction (HCI) at NTNU’s Department of Computer and Information Science. His research focuses on embodied interaction, emphasizing the physical, bodily, and social dimensions of human-computer interaction. He developed a usability laboratory for simulating multi-user, multi-device scenarios, particularly in healthcare contexts. His theoretical framework draws heavily from Maurice Merleau-Ponty’s phenomenology, exploring how perception and action shape interaction. Education: PhD in HCI from NTNU (2000). His research areas include interaction design, user-centered methods, and healthcare IT systems design. Key projects include the UNITY-Things IoT framework and exergame development for balance training in seniors. Research Highlights: Svanæs pioneered participatory design methodologies in healthcare IT, emphasizing end-user involvement through role-play and prototyping. His work on pandemic policy critiques and lockdown strategies demonstrates interdisciplinary collaboration between HCI and public health. Publications: Over 50 peer-reviewed articles in venues like Computer Supported Cooperative Work , Frontiers in Computer Science , and IEEE Transactions . Recent work addresses exergame design, pandemic response systems, and embodied interaction theory. Grants & Labs: Built NTNU’s Health Informatics Usability and Design Lab. Collaborates with academic and healthcare institutions on projects like the NSEP (Norwegian Center for Electronic Patient Records).

• Security
• Embedded Systems Security
• Cyber-Physical Systems Security
• +13 more

Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems. Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security. The analysis of his recent publications reveals a consistent focus on hardware and system-level security , particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats. Scientific Contributions: Over 100 peer-reviewed publications One book and one patent Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore) Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union. Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.

Greg MorrisettView profile

Professor

• Programming Languages
• Software Security
• Formal Verification
• +4 more

Greg Morrisett is the Jack and Rilla Neafsey Dean and Vice Provost of Cornell Tech, a graduate campus in New York City focusing on technology, business, law, and design. Previously, he served as Dean of Computing and Information Sciences at Cornell University and held the Allen B. Cutting Chair in Computer Science at Harvard University (2004–2015). He earned a B.S. from the University of Richmond and M.S./Ph.D. from Carnegie Mellon University. His research focuses on programming language technologies for secure, reliable software systems, including typed assembly language, proof-carrying code, and provably correct compilers. Notable projects include CertiCoq, GoNative, and CRASH-SAFE. He is an ACM Fellow and recipient of awards such as the Presidential Early Career Award and NSF Career Award. He has advised over 17 PhD students and mentored numerous postdocs. His work spans formal verification, cryptographic protocols, and secure systems design. Morrisett has served on editorial boards for journals like Communications of the ACM and advisory councils for NSF, DARPA, and Microsoft Research. Current research includes formal verification of cryptographic protocols with the INRIA Prosecco Team and advancing compiler correctness through projects like CertiCoq.

Sneha D. GoenkaView profile

Assistant Professor

• Computational Genomics
• Computer Systems Architecture
• High-Performance Computing
• +5 more

Sneha D. Goenka is an Assistant Professor at Princeton University in the Department of Electrical and Computer Engineering, with associated faculty status in the Computer Science department. She earned her Ph.D. from Stanford University (2024) and dual B.Tech./M.Tech. degrees from IIT Bombay (2017). Her research bridges computer systems architecture and computational genomics to develop accelerated genomic pipelines. Education : Ph.D. (Electrical Engineering, Stanford 2024), Dual Degree (IIT Bombay 2017) Her work focuses on optimizing genomic data processing through hardware-software co-design, achieving speedups in clinical and evolutionary genomics. She led the development of the world's fastest genome diagnosis technique using nanopore sequencing and cloud computing. Recent publications highlight her expertise in GPU/FPGA acceleration (SegAlign, Darwin-WGA) and ultra-rapid variant detection pipelines. Her research has been published in top venues like Nature Biotechnology , New England Journal of Medicine , and SC/HPCA conferences . Scientific Awards : Stanford Centennial TA Award (2024) ACM Heidelberg Laureate Forum Young Researcher (2024) Forbes 30 Under 30 (Science) (2023) NVIDIA Graduate Fellow (2022) Cadence Women in Technology Scholar (2021) She advises students in her lab and has collaborated with institutions like Stanford Medicine, NVIDIA Research, and D.E. Shaw Research. She also contributed to the Pratham satellite project at IIT Bombay.

François TrahayView profile

Professor

• High Performance Computing
• Runtime Systems
• Performance Analysis
• +4 more

François Trahay is a Full Professor in the Computer Science department at Télécom SudParis (Institut Mines-Télécom) and a member of the Benagil Inria team. He leads research in high-performance systems, runtime systems, and performance analysis for HPC and distributed systems. He holds an HDR from Institut Polytechnique de Paris and a PhD from University of Bordeaux (2009). His work includes the EZTrace framework for performance analysis and contributions to storage systems optimization. Education: 2021: Habilitation à Diriger des Recherches (HDR), Institut Polytechnique de Paris 2010: PostDoc at Riken, University of Tokyo 2009: PhD in Computer Science, University of Bordeaux 2006: MS in Computer Science, University of Bordeaux Research focuses on runtime system design, HPC trace analysis, and storage efficiency. Recent projects include PALLAS trace format (IPDPS 2025) and GPU performance prediction (Euro-Par 2024). He advises 4 current PhD students and has supervised 2 former students now in industry. Key contributions include: Co-developer of EZTrace performance analysis framework Co-author of 60+ peer-reviewed papers in top venues (IPDPS, IEEE Cluster, ICPP) Technical leadership in Inria's Benagil team and Samovar Lab

Atakan AralView profile

Academic

• Edge Computing
• Edge AI
• Internet of Things (IoT)
• +3 more

Atakan Aral is a Visiting Lecturer at the Department of Computing Science, Umeå University. His research focuses on Edge Computing, Edge AI, and the Internet of Things (IoT), with a particular emphasis on resource management and sustainable environmental monitoring. He is affiliated with the Autonomous Distributed Systems Lab and Green Distributed Computing Group, both part of the Wallenberg AI, Autonomous Systems and Software Program (WASP) initiative. His work spans theoretical frameworks and practical implementations in edge intelligence and distributed systems. Research Interests: Edge Computing architectures and workflows Neuromorphic and energy-efficient AI systems Federated learning and multi-cluster collaboration Sensor networks for environmental monitoring Optimization of resource allocation in distributed systems Key Publications Trends: Recent work emphasizes neuromorphic edge AI applications, hierarchical federated learning, and energy-efficient IoT deployments. His articles often intersect computing continuum concepts with real-world challenges like rural environmental monitoring and latency-critical systems. Scientific Awards: No awards explicitly listed in the provided text. Advising & Grants: No formal student advisees or grant details provided. However, he contributes to the De facto Center of Excellence in Autonomous Distributed Systems (2023–2029), indicating involvement in large-scale collaborative research. Labs & Teams: Member of the Autonomous Distributed Systems Lab (lead in distributed systems research) and Green Distributed Computing Group (focused on sustainability in computing).

Mian M. HamayunView profile

Associate Professor

• Computer Science
• Transaction Level Modeling (TLM)
• MPSoC Simulation
• +15 more

Mian M. Hamayun is an Associate Professor of Computer Science and Head of Subject Group at the University of Birmingham Dubai campus, part of the College of Engineering and Physical Sciences. He holds a PhD in System Modelling, Simulation & Virtualization from the University of Grenoble Alpes, France, and has academic qualifications from Joseph Fourier University and COMSATS Institute of Information Technology, Pakistan. PhD in System Modelling, Simulation & Virtualization, University of Grenoble Alpes, 2013 MS in Informatics (Parallel & Distributed Systems), Joseph Fourier University, 2009 MSE in Software Engineering (Gold Medalist), COMSATS, 2005 PGCHE, University of Birmingham, 2021 FHEA and SFHEA, University of Birmingham (2021, 2024) His research spans Transaction Level Modeling (TLM) , MPSoC simulation , cloud computing , virtualization , Internet of Things/Vehicles , edge AI , and TinyML . He focuses on performance estimation, binary translation, and system-level simulation for embedded and distributed systems. The recent publications reflect a strong trend in IoT and vehicular networks , secure telemedicine , cloud orchestration , and embedded system simulation . His work integrates virtualization with security, real-time constraints, and machine learning on edge devices. Senior Fellow of the Higher Education Academy (SFHEA), 2024 Fellow of the Higher Education Academy (FHEA), 2021 Dr. Hamayun has supervised multiple research students and contributed to projects involving fatigue detection, person re-identification, retinal image analysis, and secure surgery frameworks. He has taught core computer science courses including Operating Systems, Networks, Data Structures, Algorithms, and Functional Programming at both undergraduate and postgraduate levels. His prior roles include Assistant Professor at NUST SEECS, R&D Engineer in France, and Lecturer at IUT1. He leads research in virtual prototyping and edge intelligence at the Dubai campus, contributing to smart city and cognitive systems initiatives. His lab work involves hybrid simulation environments, secure automotive platforms, and distributed IoT systems.