Find Academic Supervisors

Tiark RompfView profile

Associate Professor

• Programming Languages
• Compilers
• Software Engineering
• +13 more

Tiark Rompf is an Associate Professor in the Department of Computer Science at Purdue University, where he has been a faculty member since Fall 2014. He is the founder and director of the Purdue Center for Programming Principles and Software Systems (PurPL), a research group focused on next-generation software systems that integrate data-driven algorithms, also known as "Software 2.0". His academic background includes a PhD from École Polytechnique Fédérale de Lausanne (EPFL), an MS from Universität zu Lübeck, and a BS from Universität Bremen, all in computer science. His research spans programming languages, compilers, systems, databases, machine learning, and AI. He is a leading figure in meta-programming, domain-specific languages (DSLs), and compiler design, particularly through his work on Lightweight Modular Staging (LMS). His interdisciplinary work bridges theory and practice, aiming to make high-level programming languages performant and scalable. The most recent publications highlight his focus on advanced type systems (e.g., reachability types), query languages (e.g., Flan, Rhyme), compiler IRs, and the integration of machine learning and data management systems. These works appear in top venues like POPL, OOPSLA, ICFP, SIGMOD, and ECOOP, indicating sustained influence and innovation in programming language research. Among his scientific contributions, he has no explicitly listed awards in the provided text, but his leadership in founding PurPL and his extensive publication record in premier conferences are significant recognitions of his impact. He advises a group of active researchers and students, many of whom are co-authors on his recent papers. His lab, PurPL, fosters collaborative research in programming principles and software systems, often involving meta-programming, differentiable programming, and system-level optimizations. He has led or co-led multiple collaborative projects, including work on Flare (a native compiler for Apache Spark), HACCLE (secure multi-party computation), and AutoGraph (imperative-style differentiable programming).

• Software Engineering
• Context-Aware Systems
• Public Health Informatics
• +4 more

Ufuk Çelikkan is an Assistant Professor in the Department of Software Engineering at Izmir University of Economics since September 2008. He holds a Ph.D. and M.S. in Computer Science from North Carolina State University (1995, 1993) and a B.S. in Computer Science from Middle East Technical University (1988). Education : Ph.D., M.S. (NCSU), B.S. (METU) Experience : Researcher at Gemalto Inc. (2007-2008), Software Engineer at IBM (1995-2007), Research Assistant at NCSU and Bilkent University His research focuses on context-aware systems , service-oriented architecture , and IoT applications , often bridging software engineering with health informatics and retail technology . Recent work explores design pattern recommendations , encryption mechanisms , and academic-industry alignment in IT education. Key trends in his publications include context-aware system design , public health informatics , and authentication technologies . He has contributed to interdisciplinary projects involving medical education , laundry business automation , and supermarket behavior analysis .

Imre GáborView profile

Academic

• Computer Science
• Software Engineering
• Web Application Performance
• +4 more

Imre Gábor is an Assistant Lecturer at the Department of Automation and Applied Informatics within the Faculty of Electrical Engineering and Informatics at Budapest University of Technology and Economics (BME). He is affiliated with the Applied Computer Science Group , focusing on software engineering and system performance. Office: Q.B224, Magyar tudósok krt. 2., Budapest 1117, Hungary Email: Imre.Gabor@aut.bme.hu Phone: +36 (1) 463-2713 Fax: +36 (1) 463-2871 His research spans Java-based systems , XML serialization , web application performance , and cloud computing . Recent work analyses WebSocket benchmarking , EC2 scalability , and application server tuning . Publications in Computer Science and Software Engineering highlight his expertise in distributed systems , XML technology , and enterprise application performance . He contributes to the BME Publication Registry and collaborates via platforms like Google Scholar and ResearcherGate . He is associated with the Applied Computer Science Group , which investigates theoretical and applied challenges in modern software development and system optimization.

Stefan GeislerView profile

Professor

• Human-Machine Interaction
• Natural User Interfaces
• Usability Engineering
• +6 more

Stefan Geisler is a Professor at Ruhr West University of Applied Sciences since 2010. He holds the professorship for Applied Computer Science / Human-Machine Interaction and serves as Program Director for the Human-Technology Interaction program. Since 2016, he has led the Positive Computing Research Institute , contributes to the Intelligent Mobility research program , and directs the Media and Interaction Department in the North Rhine-Westphalian doctoral program. Research Focus: Human-Machine Interaction (HMI), Natural User Interfaces (NUI), Usability Engineering, Automotive HMI, and Intelligent Mobility. Projects: Golden Rules in Automotive HMI, PARCURA (smart glasses in hospitals), UsAHome (home HMI systems), BMBF-funded AHA project (safety-critical interfaces), and intercultural/intergenerational innovation development. Collaborations: FH Struktur, IQPC Conference, CAMO network, and North Rhine-Westphalian doctoral program. Teaching: Covers the entire usability engineering lifecycle, emphasizing user testing integration and intuitive interface design. Publication Trends: Focus on automotive HMI optimization, gesture-based interaction, user experience in mobility systems, and human-centered design for safety-critical applications. Subfields include driver assistance systems, natural user interfaces in automated vehicles, and usability testing methodologies. Leadership: Directs the Positive Computing Research Institute and the Media and Interaction Department. Supervises doctoral research in intercultural innovation and automotive NUI development.

Ruben MayerView profile

Professor

• Distributed Systems
• Decentralized Information Systems
• Data Management
• +6 more

Prof. Dr. Ruben Mayer is a computer science professor and current head of the Chair of Data Systems at the University of Bayreuth (since March 2023). He also serves as a guest professor at the Technical University of Munich (TUM) . Prior roles include interim professorships at TUM Campus Heilbronn and TUM's Chair of Application and Middleware Systems, following postdoctoral research at TUM and University of Stuttgart. His research focuses on large-scale distributed data analytics systems , including complex event processing , graph processing , deep learning systems , and decentralized systems like blockchains and edge computing. Recent work emphasizes federated learning and graph neural networks , with interdisciplinary exploration of machine learning and law . ACM DEBS Grand Challenge Audience Award (2016, 2017) ACM DEBS Grand Challenge Performance Award (2016) He has served as reviewer for top conferences like NeurIPS and ICDE, and as Associate Editor for PVLDB Volume 19 (VLDB 2026). His teaching spans cloud databases , distributed systems , and blockchain technologies across multiple semesters at TUM.

Val TannenView profile

Professor

• Database Systems
• Logic in Computer Science
• Computational Theory
• +3 more

Val Tannen is a Professor at the University of Pennsylvania in the Department of Computer and Information Science . His research focuses on Databases , Logic , and Computation , with notable contributions to provenance analysis, semiring semantics, and stream processing systems like DBSP. 2023 : Best Paper at VLDB 2023 : Member of Academia Europaea 2013 : Fellow of the ACM His recent work includes incremental computation frameworks for databases, hierarchical query algorithms, and semantic-web integration middleware. He has co-advised PhD students Jesse Comer and Lawrence Dunn . Research groups: Databases and Logic and Computation .

Stefan KuhlinsView profile

Professor

• Business Informatics
• Information Technology
• E-commerce
• +6 more

Prof. Dr. Stefan Kuhlins is a Professor of Business Informatics at Heilbronn University's Faculty of Economics. He specializes in Business Engineering Logistics and previously worked at the universities of Mannheim and Regensburg. His research focuses on E-commerce, XML technologies, and enterprise software integration. He also operates as a freelance business information technology specialist. Current: Professor at Heilbronn University (Faculty of Economics) Previous: University of Mannheim, University of Regensburg Specialization: Business Engineering Logistics (formerly Technical Logistics Management) Freelance: E-commerce and software projects Education : Graduate in Business Information Technology Research Interests : His work spans business informatics, information technology, and programming with particular emphasis on database systems, XML standards, and Robotic Process Automation (RPA). He has developed frameworks for enterprise application integration and explored wireless usability metrics through Java software agents. His publications reflect a strong focus on E-commerce systems, XML schema design, and software development methodologies. Publications Trends : His scholarly output from 1993-2018 covers XML technologies, Java applications in enterprise systems, simulation modeling for logistics, and web service integration. The articles demonstrate consistent engagement with software engineering challenges in E-commerce and enterprise contexts. Technical Leadership : Since 2014, he has served as Head of the Internship Office for Business Engineering Logistics (BEL) and Technical Logistics Management (TLM) programs at Heilbronn University. This administrative role complements his technical expertise in systems design. Programming Expertise : With deep knowledge of C++ standard libraries and Java technologies, he has contributed to areas like garbage collection, CORBA optimization, and multithreaded frameworks. His technical work spans from core programming challenges to enterprise-scale integration solutions.

• Internet of Things
• Smart Grid
• Virtual Learning Environments
• +5 more

David Vernet Bellet is a Professor with a PhD at the Higher Technical School of Engineering, Department of Engineering, Universitat Ramon Llull in Barcelona, Spain. He leads and participates in multiple research projects focused on smart technologies, including the 'Estudi plataforma Airtool' project as Principal Researcher and the 'LHCb-RTA-URL' project investigating new physics and data science challenges at CERN's LHCb experiment. Research Group on Smart Society (2022-2025) GRITS: Internet Technologies & Storage Research Group (2017-2021) LHCb-RTA-URL: CERN Data Challenges (2023-2026) His research spans across cutting-edge domains at the intersection of computer science, energy systems, and educational technology. With a primary focus on Internet of Things applications, smart grid technologies, and virtual learning environments, his work has established him as a leading researcher in these fields. His fingerprint analysis shows strong expertise in IoT (100%), Virtual Learning Environments (90%), Smart Grid (89%), and Intelligent Tutoring Systems (62%). Analysis of his recent publications reveals a consistent research trajectory focused on developing innovative middleware solutions for IoT architectures, creating social internet of energy paradigms, and designing intelligent tutoring systems for cross-disciplinary training. His work demonstrates a unique ability to bridge theoretical computer science with practical applications in energy management and educational technology. 172 total citations across his work 9 h-index according to Scopus Multiple publications in high-impact journals like IEEE Internet of Things Journal, Sensors, and Journal of Supercomputing As an active researcher, he supervises projects and collaborates with numerous researchers across the Research Group on Smart Society, contributing significantly to both academic knowledge and practical implementations in smart technologies. His work on ontology-defined middleware, social internet of energy, and intelligent tutoring systems represents significant contributions to their respective fields. He maintains active collaborations through the Research Group on Smart Society, which includes approximately 40 researchers working on interconnected projects related to smart technologies, internet of things, and data science applications across multiple domains.

• Database Systems
• Information Integration
• Service-Oriented Computing
• +3 more

Michael Carey is a Professor specializing in database systems and distributed computing. His research focuses on database systems, information integration, service-oriented computing, middleware, and performance evaluation. He has contributed to projects like Apache AsterixDB, a scalable open-source database management system. Education: Ph.D. in Computer Science from UC Berkeley (1983), M.S. in Electrical Engineering (Computer Engineering) from Carnegie-Mellon University (1981), and B.S. in Electrical Engineering and Mathematics from Carnegie-Mellon University (1979). Research interests include next-generation databases, data mining, big data management, and declarative data processing. His recent work emphasizes optimizing big active data systems, memory management in join queries, and scalable NoSQL benchmarks. Notable projects include SQL++ language enhancements and the CH3 benchmark for NoSQL systems. He has received the 2016 IEEE TCDE Impact Award for contributions to data engineering. His grants include NSF-funded projects on big data systems and collaborative research in scalable analytics. Key contributions include Apache AsterixDB, a community-driven platform for big data research, and frameworks for large-scale machine learning integration with databases. His work bridges theory and practice, addressing challenges in distributed systems and real-time data processing.

Francisco MouraView profile

Associate Professor

• Systems Software
• Distributed Systems
• Operating Systems
• +5 more

Francisco Moura is an Associate Professor at the University of Minho, affiliated with HASLab/INESC TEC. His research focuses on Systems Software, including compiler design, operating systems, middleware, and performance optimization. He co-founded Eurotux SA, specializing in open-source software and cloud-based systems. His work emphasizes the interplay between performance metrics (efficiency, availability) and software system architecture. Research interests span distributed systems, database replication protocols, and mobile agent architectures. Notable contributions include studies on partial replication in databases, fault-tolerant group communication systems, and optimizing transaction processing in wide-area networks. Publications highlight practical applications of theoretical models, validated via network simulators and real-world benchmarks. Publications (2001–2006) address challenges in distributed computing, from mobile agent frameworks for virtual enterprises to latency-reduction techniques in WANs. No scientific awards listed, but active in industry-academia collaborations through Eurotux SA. Advising activities are unspecified in available texts. His work is anchored in HASLab/INESC TEC, a leading center for high-assurance software research.

Ricardo Gonçalves MacedoView profile

Assistant Professor

• Storage Systems
• Operating Systems
• High-Performance Computing (HPC)
• +3 more

Ricardo Gonçalves Macedo is an Invited Assistant Professor at the University of Minho and a Researcher at INESC TEC's Distributed Storage Research (DSR) team since 2016. He holds a PhD in Computer Science (2023) from the MAP-i program at Universities of Minho, Aveiro, and Porto, focusing on user-level software-defined storage data planes. His research emphasizes storage systems and operating systems, addressing performance, reliability, and energy efficiency in large-scale I/O infrastructures. Key areas include kernel-bypass storage stacks, disaggregated resources, and HPC storage challenges. Recent work includes tools like LAZYFS for fault injection and PADLL for metadata QoS control. He leads projects like DisaggregatedHPC (energy-efficient resource disaggregation) and CDMS (healthcare data management). Ricardo has supervised over 10 theses at the University of Minho and contributes to open-source projects in storage optimization. His work is published in top venues like VLDB, IEEE Cluster, and FAST.

• Computer Science
• Distributed Systems
• Blockchain Technology
• +4 more

Pezhman Nasirifard is a researcher at the Technical University of Munich, specializing in distributed systems and blockchain technology. He earned his PhD from the same institution in 2023, focusing on reducing coordination in permissioned blockchains using Conflict-free Replicated Data Types (CRDTs). His work bridges computer science and energy systems, addressing challenges in blockchain scalability, distributed ledgers, and grid inference through crowdsourced data. Key contributions include the OrderlessChain framework, which eliminates global transaction ordering in blockchains, and the FabricCRDT approach for permissioned blockchain systems. He has also explored energy grid modeling using drone imagery and crowdsourcing, as well as serverless computing architectures. His publications span venues like Middleware, e-Energy, and IEEE Transactions, highlighting interdisciplinary research in distributed systems, blockchain applications, and energy infrastructure. Collaborations with co-authors like Hans-Arno Jacobsen and Ruben Mayer emphasize his engagement with cutting-edge technologies and distributed computing paradigms.

Bilgin AVENOĞLUView profile

Associate Professor

• Artificial Intelligence
• Software Engineering
• Cloud Computing
• +4 more

Dr. Bilgin AVENOĞLU is an Associate Professor at Ankara Üniversitesi's Faculty of Engineering, Department of Software Engineering (since 2022). Previously, he held full-time positions at TED Üniversitesi in similar roles. He holds a Ph.D. in Computer Systems from Orta Doğu Teknik Üniversitesi (2014), an MSc in Computer and Instructional Technology Education (2005), and a BSc in Computer Education (2001). Research Interests: Artificial Intelligence applications in pervasive computing Middleware systems and cloud-based frameworks Optimization algorithms for multi-dimensional problems Context-aware and workflow-based systems Recent Research Trends: Focuses on integrating physiological data with human-machine interfaces, developing robust optimization methods, and middleware solutions for multi-modal interactions. His work bridges software engineering with ambient intelligence and cloud computing. Awards: No awards explicitly listed, but active in TÜBİTAK-funded projects. Grants & Projects: Led a 2018-2022 TÜBİTAK/TÜBA project on physiological data infrastructure for human-machine applications. Collaborates with institutions like Orta Doğu Teknik Üniversitesi and İnönü Üniversitesi. Labs/Teams: No dedicated lab mentioned, but active in cross-institutional research collaborations.

Borja SotomayorView profile

Professor

• Computer Science Education
• Distributed Systems
• Resource Allocation
• +3 more

Borja Sotomayor is a Senior Instructional Professor in the Department of Computer Science at the University of Chicago. He specializes in teaching introductory computer science, software development, and computer networks. His research focuses on resource allocation in distributed systems using virtualization and, more recently, on computer science education. He has published widely in these areas and contributed to projects like the chidb database system and the Haizea resource management framework. He is actively involved in campus activities, including advising student organizations and designing educational tools. Sotomayor holds a PhD from the University of Chicago (2010) and has authored books on the Globus Toolkit. He is also known for designing t-shirts and promoting STEM education through initiatives like the CRA Education Committee.

Maciej BestaView profile

Researcher

• Sparse Graph Computations
• Large Language Models
• Graph Neural Networks
• +7 more

Maciej Besta is a leading researcher at ETH Zurich's Institute for Computing Platforms, where he heads research initiatives at the Scalable Parallel Computing Lab (SPCL) and contributes to the ETH Future Computing Laboratory (EFCL). Working under the mentorship of Professor Torsten Hoefler, he has established himself as a prominent figure in high-performance computing, graph processing, and large language models. Position: Researcher at Institute for Computing Platforms, ETH Zurich Research Leadership: Head of Sparse Graph Computations and Large Language Models Research at SPCL Collaboration: Leads project management for SPCL's contributions to ETH Future Computing Laboratory Besta's research spans multiple abstraction levels, from hardware and network topologies to middleware, algorithms, and programming models. His primary focus areas include graph-enhanced language models, graph neural networks, graph databases, and sparse models, with applications across various computational settings. He approaches these problems through rigorous performance modeling and formal reasoning, emphasizing both scalability and practical implementation. His recent publications reveal a clear trend toward integrating graph structures with language models and AI systems. Besta has pioneered work on graph databases, knowledge graphs of thoughts, and higher-order graph neural networks, while maintaining his strong foundation in high-performance computing and network topology design. His research bridges traditional HPC with cutting-edge AI, creating novel approaches for efficient large-scale computation. IEEE TCSC Award for Excellence in Scalable Computing (Early Career, 2023) Multiple Best Paper Awards at Supercomputing conferences (2022, 2023) ACM SIGHPC Doctoral Dissertation Award (2022) ETH Medal for outstanding doctoral thesis (2021) Fellow of The Explorers Club (2022) Besta actively mentors ETH Zurich students through semester projects, Bachelor's, and Master's theses, focusing on graph processing and related computer science challenges. His mentorship extends beyond technical guidance, incorporating lessons from his extensive polar and mountaineering expeditions that emphasize mental resilience, efficient risk management, and leadership. He has supervised numerous student projects that have resulted in high-impact publications at top-tier conferences. As a core member of the Scalable Parallel Computing Lab, Besta collaborates with researchers across ETH Zurich and international institutions. His unique approach integrates insights from extreme environment expeditions into research methodology, creating a distinctive framework for tackling complex computational problems. The lab's work under his leadership spans theoretical modeling, practical implementation, and real-world deployment of high-performance systems.