Find Academic Supervisors

• Software Engineering
• Distributed Systems
• Cloud Computing
• +4 more

UnivProf. Dr. Jens Grabowski is a full professor at the Institute of Computer Science at Georg-August-Universität Göttingen, leading the Software Engineering for Distributed Systems group. His primary roles include teaching advanced courses on software engineering, software testing, and parallel computing, as well as supervising practical internships in these domains. His research focuses on software engineering methodologies, cloud computing architectures, static analysis tools, and model-driven approaches to system design. Education details are not explicitly listed, but his academic position implies a PhD in Computer Science. His work spans both theoretical contributions (e.g., defect prediction models, developer behavior studies) and applied systems (e.g., cloud resource management frameworks, testing tool development). He is actively involved in open-source software research, particularly analyzing Apache projects and Python ecosystems. Key research themes include: Model-driven cloud orchestration using standards like TOSCA and OCCI Static analysis tool evaluation and warning management Empirical studies on software evolution and developer practices Simulation-based approaches for system validation His recent publications (2021-2025) demonstrate sustained contributions to cloud computing infrastructure, static analysis tool efficacy, and software testing methodologies. Notable frameworks developed include MoDMaCAO for cloud application management and the SmartShark ecosystem for mining software repositories. Grants and advising activities are not explicitly detailed in the provided texts, but his leadership in multiple research groups implies significant involvement in academic funding and PhD supervision. He maintains collaborations in distributed systems, cloud computing, and software engineering education.

Diyar AltinsesView profile

Researcher

• Machine Learning
• Fault-Tolerant Systems
• Predictive Maintenance
• +4 more

Diyar Altinses is a researcher at the Department of Electrical Power Engineering, South Westphalia University of Applied Sciences (Soest, Germany). Holding an M.Sc. in Systems Engineering and Engineering Management (double degree from University of Bolton and FH-SWF, 2019-2021), he completed his Dr. rer. nat. in 2021 with a focus on multimodal fault-tolerance through machine learning. Research interests span Fault-tolerant machine learning for industrial sensor data reconstruction Drone logistics optimization with 5G and multimodal networks Synthetic dataset generation for industrial process modeling Self-optimizing systems in metal forming and packaging Recent publications highlight applications of neural fusion techniques in drone landing precision, imputation methods for time series decomposition, and benchmarking data-driven industrial approaches. His work connects computational techniques with real-world process optimization challenges.

• Geological Fracture Modeling
• Thermo-Hydro-Mechanical-Chemical Simulation
• Carbon Capture and Storage
• +3 more

Dr. Saeed Mahmoodpour is a researcher at the Technical University of Munich's Department of Geothermal Technologies within the School of Engineering and Design. He works under the Assistant Professorship of Geothermal Technologies led by Prof. Dr. Michael Drews, focusing on subsurface energy systems and contributing to projects like the Geothermal Alliance Bavaria (GAB) and GoEffective. His educational background includes: Bachelor of Science in Petroleum Engineering from Sharif University of Technology (2008-2012) Master of Science in Reservoir Engineering from Sharif University of Technology (2012-2014) Professional experience at University of Tehran and Technical University of Darmstadt prior to his current position Dr. Mahmoodpour's research centers on subsurface energy systems , with particular expertise in fracture network modeling , THMC simulations , carbon capture and storage , and underground hydrogen storage . His work integrates computational approaches with geological analysis to address challenges in sustainable energy development. He has developed sophisticated models for predicting behavior of geological formations under various energy storage and extraction scenarios. Analysis of his recent publications (2022-2025) reveals a strong focus on hydrogen storage in geological formations and enhanced geothermal systems . His research demonstrates increasing sophistication in modeling coupled physical processes, with recent work incorporating molecular dynamics simulations alongside traditional reservoir modeling approaches. A notable trend is his expanding investigation of CO2-hydrogen mixtures and their behavior in subsurface environments. Dr. Mahmoodpour actively collaborates with researchers across multiple institutions, contributing to the Geothermal Congress and EGU General Assembly presentations. His work supports the Bavarian Pressure Map initiative and other regional geothermal development efforts in the North Alpine Foreland Basin.

Ulf SchlichtmannView profile

Professor

• Electronic Design Automation
• Integrated Circuit Design
• Microfluidics
• +2 more

Professor Ulf Schlichtmann holds the Chair of Design Automation at Technische Universität München's School of Computation, Information and Technology. His research specializes in electronic design automation (EDA) methodologies for complex integrated circuits, with recent focus on optical networks-on-chip, microfluidic biochips, and neuromorphic computing architectures. Research interests span hardware design automation, photonic network optimization, fault-tolerant systems, and AI-assisted hardware generation. Recent innovations include wavelength-routed optical NoCs, 3D-printed microfluidics, and LLM-enhanced HDL design tools that advance hardware efficiency and reliability. Publications demonstrate consistent breakthroughs in cross-domain optimization, with applications spanning from high-performance computing to biomedical microdevices. Laboratory leadership includes coordination of international degree programs and industry collaborations.

Alireza HakamianView profile

Researcher

• Software Engineering
• Resilience Engineering
• Cloud Computing
• +3 more

Dr. Alireza Hakamian is a Researcher at the Department of Informatics, University of Hamburg, affiliated with the SWK Team within the Research groups. His work focuses on resilience engineering, microservices architecture, and systems simulation. Notable contributions include the development of MiSim, a simulator for resilience assessment of microservice-based systems, and TQPropRefiner, a tool for specifying and refining transient software quality properties. His research explores chaos engineering practices, transient behavior analysis, and container orchestration techniques (e.g., Kubernetes). He emphasizes integrating real-world container environments into simulation frameworks for more authentic resilience testing. Expert interviews and industry insights underpin his work on transient behavior management in distributed systems. Key tools and methodologies developed include the DiSpel Cockpit for resilience scenario verification and the TransVis visualization system. His work bridges theoretical software design principles with practical implementation challenges in cloud-native systems.

• Dependability
• Fault Tolerance
• Distributed Systems
• +7 more

Lukas Pirl is a researcher at the Hasso Plattner Institute (HPI), University of Potsdam, working within the Department of Operating Systems and Middleware. His research focuses on dependability, fault tolerance, and experimental assessments of distributed systems with particular applications in railway technology and IoT systems. His research interests span multiple domains including: Dependability and fault tolerance architectures & protocols Experimental assessments using software fault injection Environmentally aware computing and information management Symmetric peer-to-peer systems and storage operating systems Railway digitalization and safety-critical systems Lukas's recent publications demonstrate a strong focus on applying distributed systems research to railway technology. His work spans from digital train control systems (FlexiDug project) to railway crossing safety (Digital St. Andrew's Cross), and from blockchain applications in railway systems (RailChain, ZugChain) to IoT testing methodologies. A significant portion of his research involves using SUMO for railway simulations and developing test automation frameworks for railway components, showing an evolution from general distributed systems research toward specialized applications in critical infrastructure. He has co-supervised numerous Master's theses at HPI, working with students on topics ranging from railway simulation architectures to blockchain implementations for railway systems. His teaching activities include serving as a teaching assistant for courses on distributed systems, embedded operating systems, and trends in operating systems across multiple semesters. Lukas is actively involved in several major research projects: FlexiDug : Investigating reuse of rail infrastructures in former brown coal mining areas, focusing on software architectures for dependable digital train control and signaling systems RailChain : Exploring distributed ledger technologies for the railway sector with focus on timing predictability and resource constraints DiAK : Digitalization of railway crossings for increased safety through bridging V2X and C-V2X technologies Rail2X : Investigating vehicle-to-everything technologies for the railway sector with focus on wireless technology assessments

• Seismology
• Geophysics
• Earthquake Mechanics
• +4 more

Dr. Mohammad Moein is a researcher at the Department of Earth Sciences, Free University of Berlin, specializing in geophysics and seismology. His academic journey includes a BSc in Petroleum Engineering (2010), MSc in Reservoir Geoscience (2012), and a PhD in Earth Sciences (2018) from ETH Zurich. He has held postdoctoral positions at Technical University of Darmstadt (2018-2019) and University of Halle (2019-2021), and since 2021, he leads a DFG-funded project on induced earthquakes in fractured rocks. His work bridges theoretical and applied geophysics, focusing on geo-energy applications. PhD: Earth Sciences, ETH Zurich (2018) MSc: Reservoir Geoscience and Engineering, IFP School (2012) BSc: Petroleum Engineering, Amirkabir University of Technology (2010) Moein's research explores the physical mechanisms of induced seismicity, stress heterogeneity in megathrust faults, and fracture network dynamics in crystalline rocks. He employs borehole imaging, hydraulic simulations, and statistical analysis to study depth-dependent fracture patterns and their implications for geothermal and carbon capture projects. His work has significant applications in assessing seismic risks associated with subsurface energy operations. His publications demonstrate interdisciplinary expertise across seismology, fracture mechanics, reservoir engineering, and geothermal systems. Key themes include pressure diffusion controls on earthquake magnitudes, fractal fracture analysis, and stress-based tomography. Current projects focus on DFG-funded research into induced seismicity mitigation. Dr. Moein's laboratory affiliations include the Seismology working group (AG Seismik) at the Institute of Geological Sciences, Free University Berlin. His career trajectory reflects a commitment to advancing geophysical understanding through field observations, experimental validation, and computational modeling.

• Power Electronics
• Drive Systems
• Electric Machines
• +5 more

Prof. Axel Mertens holds a professorship at Leibniz University Hannover's Faculty of Electrical Engineering and Computer Science, leading the Institute of Drive Systems and Power Electronics. He also serves on the Executive Board of the Leibniz Research Centre Energy 2050 and participates in the Faculty Council as a Deputy Representative for Professors. His expertise spans power electronics, electric drives, renewable energy systems, and aircraft propulsion. He has authored numerous articles on topics like inverter topology optimization, self-sensing motor control, and grid stability in inverter-dominated grids. Research focuses include: High-efficiency power conversion systems Electric machine design and control EMI mitigation strategies Reliability analysis for power electronic systems Integration of renewable energy sources His work contributes to advancing energy-efficient traction systems, airborne wind energy, and fault-tolerant aircraft propulsion. Current projects involve the SkyPower100 airborne wind energy initiative and DampedWEA vibration-reduction research. He actively participates in interdisciplinary collaborations through Leibniz Research Initiatives. Notable achievements include pioneering work on quasi-three-level modular converters and innovative self-sensing control techniques. His research addresses both fundamental and applied challenges in power electronics, with applications ranging from automotive electrification to sustainable energy generation.

Sonja PhilippView profile

Professor

• Structural Geology
• Geothermal Reservoirs
• Fracture Mechanics
• +3 more

Sonja Philipp is Professor of Structural Geology and Geodynamics at the University of Göttingen, researching brittle deformation processes and geothermal reservoir characterization. Her work combines field studies with numerical modeling to analyze fracture propagation and fluid transport in sedimentary rocks. Projects include AuGE (geothermal exploration analogues) and fracture analyses in limestone-marl alternations. Research highlights permeability structures in fault zones and mechanical heterogeneity effects on reservoir performance. Philipp teaches Fractured Reservoirs and leads rock mechanics investigations for safe geothermal drilling.

Christian DietrichView profile

Professor

• Operating Systems
• Real-Time Systems
• Embedded Systems
• +3 more

Christian Dietrich is a Professor at the Technische Universität Hamburg (TUHH) in the Operating System Group (OSG) . His research focuses on Operating Systems , Real-Time Systems , and Embedded Systems , with specific interests in Software Fault Tolerance , Memory Management , and Software Variability . Projects: ParPerOS (Parallel Persistency OS), ATLAS (Adaptable Thread-Level Address Spaces), CLASSY-FI (Cross-Layer Fault Injection), AHA (Automated Hardware Abstraction), CADOS (Configurability-Aware OS) Supervised Theses: 10+ completed theses on topics like io_uring Integration , Heterogeneous Multi-Core , Virtual Memory Primitives , and Fault Injection His recent publications (2022-2024) address Heterogeneous Computing , Virtual Memory Interfaces , and Crash-Consistent Systems . He received awards including USENIX ATC 2017 Best Paper , RTAS 2015 Best Paper , and ISORC 2022 Outstanding Paper .

• Seismology
• Applied Geophysics
• Marine Geophysics
• +4 more

Laura Gaßner is a Researcher at the Geophysical Institute (GPI) of the Karlsruhe Institute of Technology (KIT) , specializing in Applied Geophysics . Her work bridges seismic inversion techniques, wind turbine-induced ground motion analysis, and marine geophysics. Education : Master's and PhD (2019) from KIT, with a dissertation on full-waveform inversion for gas-hydrate imaging. Research Interests : Modeling and inversion of seismic wave fields for subsurface exploration Seismic and acoustic emissions from wind turbines in low mountain ranges Marine seismics for gas-hydrate and deep-sea fan characterization Ground motion analysis and its societal impacts Integration of multidisciplinary data for environmental impact studies Computational geophysics with finite-difference and inversion methodologies Scientific Trends : Her publications focus on wind turbine seismo-acoustic emissions, gas-hydrate imaging via full-waveform inversion, and fluid-induced microseismicity. Key keywords include Seismology , Environmental Geophysics , Marine Geophysics , and Computational Modeling , with sub-fields like Wind Turbine Seismology , Gas Hydrate Systems , and Fault Reactivation Analysis .

Volker SkwarekView profile

Professor

• Cybersecurity
• Distributed Systems Security
• IoT and Sensor Networks
• +3 more

Prof. Volker Skwarek is a Professor for Technical Informatics at the Department of Industrial Engineering and Management, Hamburg University of Applied Sciences. He leads the research group DLT³-Hamburg and heads the research and transfer center for digital business processes. His work focuses on cybersecurity in distributed systems, IoT security, and blockchain applications in industrial environments. He has held leadership roles including Deputy Head of the Department HWI and coordinates the graduate focus area 'Information Science'. Research interests include ultra-low-power IoT systems, self-sovereign identity frameworks, and secure blockchain-sensor integrations. Prof. Skwarek has authored over 30 peer-reviewed articles, 2 books, and multiple patents. He actively contributes to international standardization of blockchain technologies and serves on editorial boards for distributed ledger journals. His projects span smart grid security, decentralized energy trading systems, and forensic blockchain analysis. Notable projects include WaterGridSense 4.0 (smart grid resilience), LegalBlock (legal frameworks for smart contracts), and TrustedCamApp (secure video streaming in sensor networks). He emphasizes practical applications alongside theoretical advancements, collaborating closely with industry partners to address real-world challenges in digital security and automation. Prof. Skwarek holds national/international awards for research and education innovation. His teaching includes courses on technical informatics, programming in C, and cybersecurity fundamentals. He advocates for continuous professional development through academic-industry partnerships and standardization initiatives.

• High-Performance Computing (HPC)
• Parallel and Distributed Systems
• Load Balancing
• +4 more

Florina M. Ciorba is a Professor in the field of High-Performance Computing (HPC), affiliated with the University of Basel. Her research focuses on parallel algorithms, fault-tolerant systems, dynamic load balancing, and energy-efficient computing. She has contributed extensively to HPC workflows, scheduling techniques, and resilient numerical methods for extreme-scale simulations. Key research areas include: Parallel and distributed systems Load balancing and scheduling algorithms Fault tolerance mechanisms GPU and heterogeneous computing Energy-aware HPC applications Recent work emphasizes scalable particle simulations, application classification using ML, and optimizing astrophysics workflows. She collaborates with international teams on standards like SPEChpc 2021 benchmarks and HPC operational autonomy loops. Publications span top venues including IEEE Transactions on Parallel and Distributed Systems, Euro-Par, and Cluster conferences. Her work addresses both algorithmic innovations and software implementations for next-generation HPC platforms.

• High Performance Computing
• Fault Tolerant Systems
• Quantum Computing Integration
• +7 more

Thomas J. Naughton is a researcher affiliated with the University of Reading and Oak Ridge National Laboratory. He specializes in High Performance Computing (HPC), focusing on fault tolerance, quantum computing integration, and distributed systems. Research Interests: His work bridges HPC and quantum computing, develops fault-tolerant systems, and explores computational models through optical computing. Recent Publications: His 2026-2024 papers address quantum-HPC convergence software stacks, virtualization performance, and fault injection frameworks. Educational Contributions: He co-developed Bebras-inspired computational thinking resources for K-12 education, emphasizing task-based learning.

• Cybersecurity
• Machine Learning
• Internet of Things (IoT)
• +5 more

Qusay H. Mahmoud is affiliated with the University of Ontario Institute of Technology, Canada, and previously held roles at the University of Guelph (2002–2013) and completed his PhD at Middlesex University, London (2002). His research focuses on cybersecurity, machine learning, IoT systems, blockchain, and smart policing. He has authored over 200 peer-reviewed publications in journals like IEEE Access, Sensors, and Future Internet, and conferences such as Canadian AI, IEEE CCWC, and SMC. His work spans anomaly detection in IoT networks, adversarial machine learning, cryptocurrency fraud analysis, and reinforcement learning applications. Research Interests: Dr. Mahmoud’s expertise includes developing AI-driven solutions for cybersecurity challenges, IoT security frameworks, blockchain applications in healthcare and finance, and enhancing smart policing through machine learning. He also explores adversarial training for robust deep learning models and reinforcement learning for bridging virtual-physical environment gaps. His contributions emphasize real-world applications, such as phishing detection, fault-injection attack mitigation, and cryptocurrency market analysis. Articles Trends: Recent work highlights the use of large language models (LLMs) in crime prediction, adversarial robustness in GANs, and reinforcement learning for robotics. His publications often intersect machine learning with cybersecurity, IoT, and blockchain, addressing practical challenges like anomaly detection, fraud prevention, and system reliability. Grants & Advising: While specific grants are not detailed, his extensive publication record suggests sustained research activity. No formal student advisees are listed, though collaborations with co-authors like Akramul Azim and Michael Lescisin indicate active teamwork. Labs/Teams: Engaged in interdisciplinary projects at the University of Ontario Institute of Technology, focusing on AI, cybersecurity, and IoT systems. Collaborations extend to institutions globally, addressing emerging tech challenges like blockchain in healthcare and edge computing security.