Find Academic Supervisors

• Computer Architecture
• Machine Learning
• Edge Computing
• +7 more

Kostas Siozios is a researcher affiliated with Aristotle University of Thessaloniki (AUTH) in Greece. His work spans computer architecture, embedded systems, and machine learning, with a focus on hardware-aware optimization, energy efficiency, and edge computing. Key research areas: Computer Architecture Machine Learning Edge Computing Approximate Computing Printed Electronics Cyber-Physical Systems Recent publications highlight advancements in federated learning, DNN acceleration, and energy-efficient design for emerging hardware. His work often integrates evolutionary algorithms, genetic optimization, and variability-aware strategies. Collaborations include researchers from institutions like RWTH Aachen, TU Delft, and ETH Zurich. Topics frequently address hardware-software co-design, low-power systems, and reconfigurable architectures.

• Quantum Networks
• Federated Learning
• Edge Computing
• +7 more

Andrea Passarella is a Researcher at the National Research Council, Italy , with a focus on Quantum Networks , Federated Learning , and Social Network Analysis . He collaborates extensively with academics like Marco Conti and Chiara Boldrini on topics ranging from Human-AI Hybrid Systems to Edge Computing . Key Research Areas : Quantum Networking, Decentralized AI, Social Media Analysis Recent Collaborations : Publications with ACM, IEEE, and Springer on cutting-edge networked systems His 2025 work includes Quantum Internet protocols and Human-AI Coevolution frameworks. In 2024, he explored Signed Ego Networks on Twitter and Energy-Efficient Edge Systems .

Deepak GargView profile

Professor

• Programming Languages
• Software Security
• Computer Science
• +3 more

Deepak Garg is a tenured faculty member at the Max Planck Institute for Software Systems and an Honorary Professor of Computer Science at Saarland University. His research focuses on programming languages, software security, formal verification, and information flow control. Research Interests: Programming Languages and Type Theory Software Security and Secure Compilation Information Flow Control and Access Control Formal Verification of Low-Level Programs Probabilistic Programming and Security Compiler Correctness and Runtime Systems Scientific Contributions: He has authored over 40 publications with notable awards including the Dr.-Eduard-Martin-Prize for thesis supervision, Distinguished Paper and Distinguished Artifact awards at PLDI 2021, and the Internet Defense Prize for ERIM 2019. His work spans foundational research (e.g., logics for authorization) and practical systems (e.g., Groundhog, RefinedC, ERIM). Advising: Supervised 12 PhD students to completion and currently advising 7 PhD candidates across institutions like Saarland University, MPI-SWS, and Penn State University. His group includes co-advised students with researchers such as Derek Dreyer and Peter Druschel. Service: Active in program committees for top conferences including CSF , LICS , and OOPSLA , with leadership roles in workshops like PLMW and Dagstuhl Seminars on Secure Compilation.

Paarijaat AdityaView profile

Professor

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +4 more

Paarijaat Aditya is a faculty member at the Max Planck Institute for Software Systems (MPI-SWS) , focusing on interdisciplinary research at the intersection of theoretical computer science and applied systems. Their work spans algorithms, programming languages, security, and distributed systems , with a particular emphasis on serverless computing, federated learning, and privacy-preserving urban sensing. Research Areas : Machine Learning Security (e.g., model hijacking, federated learning) Serverless Computing (e.g., GPU sharing, high-performance frameworks) Privacy Engineering (e.g., urban sensing, image capture, mobile compliance) Distributed Systems (e.g., NFV, peer-assisted content delivery) Their publications reflect a trajectory of advancing scalable AI training, secure collaborative systems, and privacy-compliant infrastructures. Recent works address challenges in public cloud adaptability, while earlier contributions explore mobile privacy risks and secure resource management.

André van HoornView profile

Professor

• Software Performance Engineering
• Distributed Systems
• Software Architecture
• +4 more

Prof. Dr.-Ing. André van Hoorn was a distinguished academic at the University of Hamburg , leading the Software Development and Construction Methods group in the Department of Computer Science since 2023. His research focused on quantitative analysis of performance and quality attributes in complex distributed systems, contributing significantly to software engineering and architecture communities. He held leadership roles in SPEC Research and organized ICPE and ECSA conferences. Education and Career: He previously worked at Oldenburg, Kiel, and Stuttgart universities. His academic rank was Professor, reflecting his expertise and leadership in software systems research. Research Interests: His work emphasized resilience engineering, microservices, cloud computing, and performance optimization. He developed tools like Kieker for performance monitoring and frameworks like Radon for serverless computing analysis. Teaching and Outreach: He actively mentored students and pioneered the SeaSchool project to introduce students to non-programming aspects of computer science. His pedagogical innovations included tablet-based e-exams in large courses. Legacy: His contributions span academic leadership, impactful research, and community engagement. Condolence books are available at the University of Hamburg’s Department of Computer Science, and a fundraising campaign supports his family.

• Data Management
• Database Systems
• Data Discovery
• +6 more

Raul Castro Fernandez is a prominent researcher in data management and database systems, with a focus on data discovery, integration, and marketplaces. He has collaborated extensively with leading institutions and researchers, contributing to projects like Data Station and Nexus for secure data sharing. His work bridges theoretical innovation with practical implementations in cloud optimization, differential privacy, and LLM-driven data tools. Key Contributions : Data market frameworks, LLM applications in databases, differential privacy platforms Collaborators : Yue Gong, Samuel Madden, Michael Stonebraker, Eugene Wu, Kyle Chard Research Themes Fernandez explores automated metadata management for data catalogs, spatiotemporal data sharing with privacy guarantees, and LLM-based data discovery . His work on stateful stream processing (e.g., SABER system) and cost optimization in cloud analytics shows technical depth. Recent Trends 2023-2025 publications highlight his pivot toward LLM applications in data management, including tabular data representation and hypothesis assessment tools. He also investigates sustainability in HPC through carbon credit systems.

• Computer Architecture
• High-Performance Computing (HPC)
• Internet of Things (IoT)
• +7 more

Vincent Bode is a researcher and teaching assistant at the Chair of Computer Architecture and Parallel Systems at the Technical University of Munich (TUM) . His work focuses on benchmarking and optimizing Data Distribution Service (DDS) middleware for Industrial IoT applications, particularly through the DDS-Perf project in collaboration with Siemens .

Wei ChenView profile

Professor

• Software Engineering
• Intelligent Software Engineering
• Network Distributed Computing
• +6 more

Wei Chen is a Research Fellow at the Institute of Software, Chinese Academy of Sciences, where he serves as a PhD and Master's supervisor. He leads the Software Engineering Technology R&D Center and maintains affiliations with the University of Chinese Academy of Sciences and its Nanjing College. Dr. Chen has established himself as a leading figure in intelligent software engineering research within China's academic community. His primary research focuses on four interconnected areas: intelligent code maintenance and quality assurance (particularly Python ecosystem compatibility based on domain knowledge), reliability assurance of complex IoT systems in human-machine-object convergence scenarios, cloud-native system development with emphasis on Function-as-a-Service optimization, and quality assurance of deep learning frameworks in resource-constrained environments. Dr. Chen's work consistently bridges theoretical advances with practical applications, maintaining strong industry collaborations with major Chinese technology companies. Analysis of Dr. Chen's recent publications reveals a strategic integration of AI techniques with traditional software engineering challenges. His research shows increasing emphasis on leveraging large language models for IoT component synthesis, sophisticated dependency management solutions for Python ecosystems, and innovative approaches to testing autonomous systems. The work demonstrates both theoretical depth and practical utility, with many publications leading to implemented tools and systems. Second Prize of Science and Technology Progress Award of China Institute of Electronics (2022) First Prize of Science and Technology Progress Award of China Institute of Electronics (2021) ACM SIGSOFT Distinguished Paper Award (2023) Special Prize of the 4th China Software Open Source Innovation Competition (2021) First Prize in the 4th China Software Open Source Innovation Competition (2021) OW2 Programming Contest First Prize (2016) Dr. Chen has mentored over ten graduate students who have achieved notable success in academic competitions and industry placements. His laboratory (TCSE, http://tcse.cn/) currently manages multiple significant research projects including 'Complex IoT System Reliability Assurance Key Technology Research' (2025-2028), 'Intelligent Development, Testing, and Maintenance of Cloud-native Software Ecosystems' (2024-2027), and 'Traffic Infrastructure Digital Industrial Software Architecture and Core Technology Standard System' (2021-2024). The lab maintains active collaborations with Huawei, Alibaba, Tencent, and other leading technology enterprises.