Find Academic Supervisors

Tiziano De MatteisView profile

Assistant Professor

• Parallel and Distributed Computing
• High-Performance Computing
• Energy Efficiency in Computing
• +4 more

Tiziano De Matteis is an Assistant Professor in the @Large Research group at Vrije Universiteit Amsterdam's Faculty of Science, Department of Computer Systems. He also holds an affiliation with the Network Institute. His research focuses on overcoming post-Moore architecture challenges through parallel and distributed computing, high-performance systems, energy efficiency, and FPGA applications. Previously, he was a PostDoc at ETH Zurich's SPCL Group and earned his MSc/PhD from the University of Pisa. Education PhD in Computer Science, University of Pisa MSc in Computer Science, University of Pisa Research Interests Post-Moore architectures for distributed ecosystems Energy-aware parallel computing High-level abstractions for parallel software development FPGA-based hardware acceleration Data stream processing and distributed systems Recent Research Trends Recent work emphasizes: Data center risk analysis and sustainability Optimizing microservices and distributed scheduling LLM model offloading to NVMe storage Python-based data-centric programming productivity GPU interconnect performance in supercomputing Grants & Projects Participates in the EU-funded 'Extreme and Sustainable Graph Processing' project (2023-2025), exploring scalable graph algorithms and energy-efficient computing systems. Teaching Accelerator-Centric Computing Ecosystems Computer Organization Distributed Systems Systems Seminar

Victorita Dolean-MainiView profile

Professor

• Domain Decomposition Methods
• High Performance Computing
• Wave Propagation
• +2 more

Victorita Dolean-Maini is Professor at University of Strathclyde and Visiting Professor at University of Strathclyde (2023-2026). She specializes in domain decomposition methods for PDEs, high-performance computing, and scientific machine learning. Her work develops fast algorithms for wave propagation problems and complex systems. She co-authored the reference work 'Domain Decomposition Methods' (SIAM 2015) and received the Bull-Joseph Fourier Prize for stroke simulation using HPC. Current research explores physics-informed neural networks with domain decomposition architectures and their application to medical digital twins. She serves on the editorial board of SIAM Journal on Scientific Computing and collaborates with industrial partners on scientific machine learning projects. Recent publications focus on neural network architectures combining domain decomposition with physics-informed learning, multilevel methods, and efficient coarse spaces for partial differential equations.

Moez LouatiView profile

Adjunct Associate Professor

• Fluid Mechanics of Waves
• Pipeline Hydraulics
• Water Loss Management
• +5 more

Moez Louati is an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at The Hong Kong University of Science and Technology (HKUST). His expertise spans fluid mechanics of waves, pipeline hydraulics, and smart water infrastructure. He holds a PhD from HKUST, supported by scholarships and the SENG PhD Fellowship Award. His research focuses on pipeline defect detection, hydraulic transients, and smart urban water systems, with notable contributions including the discovery of Bragg resonance connections in pressurized pipes. He has led projects funded by RGC, ITF, and international collaborations, and co-founded Hyele Limited, a startup developing pipeline condition assessment technologies. Education: B.Eng. (Electro-Mechanical Engineering) and MPhil (Renewable Energy) from Tunisia’s National School of Engineering of Sfax (ENIS). Professional credentials include HKIE chartered engineer status and roles as Chair of IAHR’s Africa Division and Assistant Editor of the Journal of Hydraulic Research. Research Interests: Fluid mechanics of waves, computational fluid dynamics (CFD), machine learning for infrastructure optimization, and sustainable water management. Key projects include Smart Urban Water Supply Systems and high-frequency wave-based defect detection methods. Awards: Geneva Innovations Expo 2023/24 awards, Straub Award nomination, and HKUST’s Tech-Ship startup funding. Active in international organizations and advisory roles for Hong Kong’s WSD and DSD. Labs & Facilities: Designed three water lab facilities at HKUST and collaborated globally on projects like the FREJLEV Facility’s air-water stratified flow studies. Holds five patents in pipeline diagnostics and HPC applications.

• Distributed Systems
• Cloud Computing
• Edge Computing
• +7 more

Nishant Saurabh is a tenured Assistant Professor at the Department of Information and Computing Sciences , Utrecht University , Netherlands. His research focuses on resource and data management , application scheduling , performance modeling , and optimization in large-scale hybrid distributed systems including Cloud, Edge, and Quantum computing. Recently, he has expanded into ML workload scheduling and causal performance attribution across the Cloud-Edge continuum. Research Expertise : Distributed Systems and Cloud Computing Quantum-HPC Middleware Systems Performance Modeling and Optimization ML/AI Workload Scheduling Cloud-Edge Continuum Architectures Observability Frameworks Scientific Leadership : Associate Editor, Springer's Journal of Cloud Computing Editorial Board, Frontiers of AI book series IBM HPC-Quantum Working Committee member Workshop Chair, IEEE IPDPS 2025 Supervision : He has supervised 16+ Master/Bachelor students on projects including container migration, reinforcement learning for serverless computing, and quantum middleware evaluation. Current PhD students include Diogo Landau (Performance Observability), Nathan Keyaerts (LLM Methods), and Negar Alizadeh (Energy Efficiency).

Kartik JainView profile

Assistant Professor

• Biofluid Dynamics
• Computational Physiology
• Transitional Turbulence
• +5 more

Kartik Jain is an Assistant Professor of Biofluid Dynamics at the University of Twente's Engineering Fluid Dynamics (EFD) group within the Faculty of Engineering Technology. He leads the Computational Physiology (Co∅) research group, focusing on computational modeling of physiological flows and biofluid dynamics. Education: Bachelor's in Control Engineering (Kurukshetra University) Masters in Mechanical Engineering with Simulation Sciences specialisation (RWTH Aachen University) PhD in Engineering (Dr.-Ing., University of Siegen, summa cum laude) Research Interests: Biofluid dynamics, transitional turbulence in physiological systems, computational modeling of renal hemodynamics, cerebrospinal fluid flow, and vascular stenosis. His work emphasizes high-performance computing (HPC) with contributions to the APES simulation framework and the Musubi Lattice Boltzmann solver. Recent Research Projects: Computational models for Type II Endoleaks and SIRT therapy optimization Optical Coherence Tomography (OCT) integration with flow simulations for stent planning Biofilm dynamics in confined geometries Advising & Grants: Supervises multiple PhD and MSc students on topics like particle transport in liver therapy and stent hemodynamics. Collaborates with institutions like the University of Zurich (NCCR Kidney.CH), University of Stuttgart (SFB1313), and industrial partners like Abbott Vascular. Labs & Teams: Co-directs the Co∅ team and actively contributes to the APES framework development at DLR Dresden. Engages in teaching fluid mechanics and Lattice Boltzmann methods at both bachelor and doctoral levels.

• Computer Architecture
• High-Performance Computing (HPC)
• Memory Systems
• +3 more

Prof. D.H. Pleiter is a Professor in the Department of Computer Architecture at the Bernoulli Institute, part of the Faculty of Science and Engineering at the University of Groningen. His research focuses on computer architecture, high-performance computing, and memory systems optimization. He is actively involved in evaluating hardware and software co-design strategies for modern HPC systems, particularly using Arm-based processors. His recent work includes analyzing memory prefetching mechanisms in scientific applications, emphasizing performance evaluation and memory access patterns. He collaborates on topics such as HBM2, DDR5, and locality properties in high-bandwidth memory systems, using frameworks like Gem5 for simulation. No awards or grants are explicitly listed, but his research network includes international collaborations in HPC and memory technologies. He is affiliated with the Bernoulli Institute, contributing to its research in computer architecture and innovative systems design.

• Distributed Systems
• Cloud Computing
• High-Performance Computing
• +3 more

Thilo Kielmann is an Associate Professor at the Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department) and the Network Institute. His research focuses on distributed systems, cloud computing, and high-performance computing, with emphasis on resource management, data locality, and scalable infrastructure. He has authored 95+ research outputs and supervised 8 PhD theses. Education details are not explicitly listed, but his academic role implies advanced qualifications in computer science. His work contributes to UN Sustainable Development Goals through innovative computing solutions. Research interests include distributed file systems (e.g., MemEFS), resource disaggregation, energy-efficient scheduling (e-BaTS), and scalable VM management. His publications span conferences like HPDC and journals like Future Generation Computer Systems. No scientific awards are explicitly mentioned. He teaches four courses, including Computer Programming and Large Research Project in Computer Science. Labs/teams involvement is not detailed, but his research collaborations and conference roles (e.g., HPDC15 Chair) suggest active participation in academic networks.

Simon Portegies ZwartView profile

Professor

• Computational Astrophysics
• Gravitational Dynamics
• Stellar Evolution
• +4 more

Simon Portegies Zwart is a Professor of Computational Astrophysics at Leiden University's Leiden Observatory (Sterrewacht Leiden). His research focuses on computational gravitational dynamics, stellar evolution, and supercomputing applications in astrophysics. He leads the AMUSE software framework project, enabling multi-domain astrophysical simulations. He holds editorial roles at the Journal of Computational Astrophysics and is a member of the Royal Netherlands Academy of Arts and Sciences (KHMW). Education: PhD in Astrophysics (Utrecht University) Research Interests: His work spans numerical stellar dynamics, galaxy evolution, and high-performance computing. Notable contributions include simulating star cluster dynamics, supermassive black hole interactions, and planetary system formation. He emphasizes sustainable computational practices and interdisciplinary software development. Key Contributions: Developed the Starlab, AMUSE, and OMUSE software packages Recipient of the HPC Innovation Excellence (2020) and SURF Innovation Challenge (2015) awards Advising & Grants: Supervises multiple PhD candidates and postdocs, focusing on computational astrophysics and oceanography. Collaborates with institutions like RIKEN (Japan) and the Massachusetts Institute of Technology (MIT). Labs & Teams: Leads the Computational Astrophysics group at Leiden, specializing in gravitational dynamics and multi-physics simulations.

• Neuroscience
• Computer Science
• Neurobiology
• +2 more

Jan-Harm Betting is a Researcher at Erasmus MC, where he conducts interdisciplinary research spanning neuroscience and computer science. His primary affiliations center on computational approaches to neural systems and high-performance computing applications. His research integrates Neuroscience and Computer Science, focusing on: Neuroscience: Purkinje cell dynamics, neural oscillations, sensorimotor integration, and rodent behavioral analysis. Computer Science: Deep-learning algorithms, high-performance computing optimization, and computer-vision techniques for biomedical data. Publications from 2020–2023 reveal a consistent focus on developing computational tools for neuroscience, including whisker-tracking algorithms for rodent behavior studies and resource-management systems for cloud HPC. His work frequently combines empirical neural data with advanced computational modeling. He collaborates internationally, as evidenced by multi-institutional research networks and co-authored publications with peers across neuroscience and engineering disciplines.

• Supercomputing
• Data Processing Systems
• Scientific Software
• +3 more

Bob Dröge is a researcher specializing in computational infrastructure and astronomical data systems. His work focuses on optimizing scientific software stacks for high-performance computing (HPC) environments, particularly through collaborations like the Euclid Mission and the EESSI project . He has contributed to distributed data processing systems, GPU-accelerated simulations, and mission-critical archival infrastructures. Research Interests Supercomputing and HPC architecture Scientific software deployment and optimization Astronomical data distribution networks Dark matter cosmological surveys Key Collaborations include the Euclid Mission (European Space Agency) and EESSI (European Environment for Scientific Software Installations). His publications span conferences like ADASS (Astronomical Data Analysis Software and Systems) and journals such as Software - Practice and Experience .

Elham KhaniView profile

Researcher

• Optical Communication
• Data Science
• Machine Learning
• +2 more

Elham Khani is a researcher at the Electrical Engineering Department of Technische Universiteit Eindhoven. Her work focuses on optical communication systems, data center networking, and AI applications in semiconductor manufacturing. She is actively involved in the SmartTWO project (2019-2025), contributing to next-generation telecom technologies. Research Interests : Optical network design for metro-access systems AI-driven defect detection in microchips Scalable data center architectures with optical switching Energy-efficient network solutions supporting UN SDGs Collaborations : Her work intersects computer science (100% data center focus) and electrical engineering, with significant contributions to network architecture optimization (72%) and real-application traffic management (100%).

Christos StrydisView profile

Associate Professor

• High-Performance Computing (HPC)
• Hardware Acceleration
• Reconfigurable Computing
• +6 more

Dr. Ir. Christos Strydis is an Associate Professor jointly affiliated with the Erasmus Medical Center (Neuroscience department) and Delft University of Technology (Quantum & Computer Engineering department). He is also the founder and head of the Neurocomputing Laboratory and a senior member of the IEEE . His roles span academic research, engineering leadership at Neurasmus BV , and teaching at both institutions. BSc, MSc, and PhD in Computer Engineering from the Technical University of Crete and Delft University of Technology 2011–present: Post-Doctoral Researcher, Chief Engineer, and faculty member at Erasmus Medical Center 2016–present: Assistant and Associate Professor at Erasmus Medical Center Dr. Strydis’s research lies at the intersection of neuroscience and computer engineering , focusing on high-performance computing (HPC) , low-power embedded systems , and functional ultrasound (fUS) imaging . His work bridges hardware acceleration, reconfigurable computing, and brain simulations to advance neural implants and neuroimaging technologies. His recent publications highlight innovations in exascale FPGA architectures for brain simulations, AI chip performance analysis , real-time spike detection algorithms , and secure health data integration via cloud HPC. Themes span from hardware security to cerebellar signal processing, emphasizing scalability and energy efficiency. At Erasmus and Delft, he supervises PhD, MSc, and BSc students , teaches bachelor- and master-level courses , and leads grants funded by the ICT Delft Research Centre , Google Inc. , and national/EU projects. His lab, the Neurocomputing Laboratory , focuses on translating computational neuroscience into clinical applications.

Georgi GaydadjievView profile

Professor

• Reconfigurable Computing
• Advanced Computer Architectures
• Parallel Memory Systems
• +7 more

Georgi Gaydadjiev is a Professor in Innovative Computer Architecture at the University of Groningen's Faculty of Science and Engineering. Previously, he held roles including Chair Professor at TU Delft and Chalmers University of Technology, and served as VP of Dataflow Software Engineering at Maxeler Technologies. He holds a PhD from TU Delft and has over 35 years of industry and academic experience, focusing on reconfigurable computing, high-performance systems, and energy-efficient architectures. His research spans embedded systems, fault tolerance, and scalable architectures. Education: MSc Electrical Engineering (TU Delft), PhD (TU Delft), studies at Voenmeh (Baltic State Technical University). Research interests include reconfigurable computing, advanced architectures, parallel systems, and HPC. He leads projects funded by EU, Google, and Swedish Research Councils, addressing exascale computing and customized hardware. His work has been recognized with awards like the CES Design Showcase (1999) and best paper awards at ICS'10 and WiSTP'07. He advises PhD students and oversees labs like Maxeler IoT-Labs BV, focusing on deploying dataflow technology beyond data centers.

• Computer Science
• Big Data
• Distributed Computing
• +6 more

Eliya Buyukkaya is a researcher active in the fields of Computer Science , Big Data , and Distributed Computing . Their work focuses on scalable systems, environmental informatics, and data compression techniques. 2025: Crop growth simulations using big data 2021: Bit Plane Slicing for clustering 2018: Video streaming optimization for games 2017: Clustering anomaly detection 2015: Cloud resource selection for HPC Research spans Big Data Analytics , Collaborative Algorithms , and Latency Optimization , emphasizing scalability and efficiency. Their work impacts Environmental Informatics , Game Networking , and High-Performance Computing . Collaborations include experts in Earth Observation and Computer Science , with publications in top-tier venues like Computers and Electronics in Agriculture and PLoS ONE .

Alexander NolteView profile

Assistant Professor

• Software Engineering
• Human-Computer Interaction
• Open Source Software
• +7 more

Alexander Nolte is an Assistant Professor at the Mathematics and Computer Science school of Eindhoven University of Technology and an Adjunct Associate Professor at Carnegie Mellon University since 2020. His work bridges software engineering , human-computer interaction , and collaborative innovation , with a focus on hackathons , open source , and business process management . Key research themes include: Hackathon Impact : Analyzing collaboration patterns, creativity, and project sustainability in software startups and open source. Process Analytics : Developing tools for prescriptive monitoring and explainable AI systems. Acoustic Software : Building open-source platforms for room acoustics research. Diversity Initiatives : Creating inclusive environments in technical teams. His 15 most recent publications highlight trends in large language models , collaborative event design , and software diversity . Awards include multiple best paper and demo awards from 2021 to 2024. Nolte actively contributes to scientific datasets and collaborates on interdisciplinary projects, particularly in open-source room acoustics software with TU/e and Zenodo. He teaches Human-Computer Interaction and Software Development for Engineers , emphasizing practical, event-driven learning.