Find Academic Supervisors

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.

Hong ZhangView profile

Assistant Professor

• Large-scale data analytics
• Distributed ML training and serving systems
• Application and network scheduling
• +5 more

Hong Zhang is an Assistant Professor at the University of Waterloo, specializing in large-scale data analytics, distributed machine learning systems, and cloud computing. His research focuses on advancing robust and efficient methods for modern AI systems, including topics like adversarial robustness, zero-knowledge proofs for deep learning, and scalable inference techniques for large language models. He holds a Ph.D. in Computer Science from the Hong Kong University of Science and Technology and dual bachelor's and master's degrees in Electronics and Communications Engineering from Huazhong University of Science and Technology. Education: Ph.D., Computer Science and Engineering, Hong Kong University of Science and Technology (2019) B.Sc. and M.Sc., Electronics and Communications Engineering, Huazhong University of Science and Technology, China (2013) Research Interests: Hong's work bridges theoretical foundations and practical applications in distributed ML systems, data center networking, and secure AI. Key areas include optimizing large-scale training/serve pipelines, mitigating adversarial vulnerabilities, and developing privacy-preserving techniques like zero-knowledge proofs for deep learning. His contributions span both algorithmic innovations and real-world system implementations. Publications Trends: Recent work emphasizes scalable inference acceleration (e.g., Eagle series), trustworthy AI (e.g., generative model guidelines), and cryptographic safeguards for ML (e.g., zkdl/zkllm frameworks). He frequently explores intersections between security, efficiency, and scalability in modern AI systems. Awards/Grants: No specific awards or grants mentioned in available texts. Advising & Labs: While student names aren't listed, his research group likely focuses on distributed systems and secure ML. Active collaborations likely involve cloud computing and adversarial machine learning domains.

Boris SedlakView profile

Researcher

• Distributed Systems
• Edge Computing
• Service-Oriented Computing
• +5 more

Boris Sedlak is a PostDoc Researcher and Ph.D. student in the Distributed Systems Group (DSG) at TU Wien, Austria. His research focuses on ensuring runtime requirements in large-scale computing systems through causal inference and active inference concepts, with applications in edge computing, vehicular networks, and distributed systems governance. Education: Ph.D. in Computer Science (Ongoing) at TU Wien, funded by the TEADAL EU Horizon project. M.Sc. in Software Engineering & Internet Computing (Distinction) at TU Wien (2018–2022). B.Sc. in Media Informatics at FH St. Pölten, Austria (2015–2018). Research Interests: Boris specializes in distributed computing continuum systems, active inference for system equilibrium, causal inference in distributed environments, edge computing elasticity, and privacy-preserving data stream processing. He explores applying neuroscience-inspired concepts to computing systems for adaptive and self-organizing solutions. Key Projects: TEADAL (2022–2025): Focuses on federated and trustworthy data lakes in distributed systems. INTEND (2024–2026): Investigates intelligent service adaptations through active inference. AloTwin (2023–2025) and FogProtect (2020–2022): Address edge computing security and data governance. Recent Contributions: Boris has published extensively on adaptive stream processing, SLO-aware task offloading in vehicular platoons, and equilibrium models using active inference. His work bridges causal reasoning and system design, emphasizing scalable solutions for heterogeneous edge infrastructures. Advisory & Collaboration: Supervises bachelor/master theses and actively collaborates on topics involving service-level objectives, causal models, and edge intelligence. He has presented at ICSOC, IEEE Edge Computing, and AIoTwin Summer School.

• Computing Education Research
• Educational Technology
• Large Language Models in Education
• +3 more

Arto Hellas is a Senior Lecturer at the Department of Computer Science, University of Helsinki, where he leads the Lecturer Hellas Arto group. His work focuses on computing education research (CER) and educational technology, particularly leveraging large language models (LLMs) to enhance programming education and automated assessment tools. He also explores web development optimization through edge computing and serverless architectures. Research Interests: Hellas's research spans the integration of AI into education, programming pedagogy, and educational technology. He investigates how LLMs can generate feedback, analogies, and exercises for students, as well as their impact on MOOCs and classroom dynamics. His work addresses challenges in student performance analysis, synthetic data generation for educational purposes, and the ethical implications of AI in learning environments. His studies on web development emphasize distributed systems and edge computing applications to improve web service delivery. Scientific Awards: ICER 2022 Best Paper Award for work on LLM-generated programming exercises SIGCSE TS 2022 Best Paper Award in Computing Education Research UKICER 2023 Best Paper Award Advising & Grants: Hellas currently leads the CoCoAI: Human-Centered AI for Computer Science Education project (2025–2027), focusing on personalized learning through LLMs. He has supervised 2 theses but no student names were explicitly provided. His grants and projects highlight contributions to educational technology, including datasets like the IDE Action Log Dataset and Morning or Evening? circadian rhythm study. Labs & Teams: Active within the Lecturer Hellas Arto group, his collaborations span computing education, AI ethics, and web development. His team's work has been featured in media, such as a 2023 article discussing AI's role in developing a chess website in days.

• Software Engineering
• Requirements Engineering
• Human-Computer Interaction
• +7 more

Dr. Maria Spichkova is a Senior Lecturer at RMIT University's School of Computing Technologies. She specializes in Software Engineering, Requirements Engineering, and Computer Science Education. Her research explores human factors in software development, AI applications, and sustainability. She has over 140 publications, including a monograph, and has secured over AUD$385k in research funding since 2015. Dr. Spichkova holds a PhD from TU Munich (2007) and has worked with industry partners like Microsoft and BMW. Awards include the 2023 EAI Fellowship and 2020 AAUT Citation for Teaching Excellence. Education: PhD in Computer Science, TU Munich (2007) Research roles at TU Munich (2003–2013) Research Interests: Human aspects of software engineering, requirements engineering, AI-driven solutions, sustainable eLearning systems, formal methods, and cultural influences on software development. She emphasizes industry collaboration and has led projects like Chirality-2 (mobile gaming for chemistry education) and EndOfTrip (student project). Awards: 2023: Fellow of European Alliance for Innovation (EAI) 2022: LearnSci Teaching Innovation Award (Honourable Mention) 2020: AAUT Citation for Outstanding Contributions to Student Learning 2018: Merit iAward for Chirality-2 Project Advising & Grants: Supervised 7 PhD and 9 Honours students. Notable projects include Tawfeeq Alsanoosy's PhD (14 co-authored papers) and Christopher Bond's Honours thesis (RMIT STEM Award). Secured AUD$330k in external research grants. Labs & Teams: Involved in multidisciplinary teams, e.g., Chirality-2 with Prof. Michelle Spencer (Chemistry) and Prof. Oliver Jones. Collaborates with industry partners like DENSO and AVL. Active in organizing workshops at ICSE, RE, and MODELS conferences.

Marios KogiasView profile

Assistant Professor

• Operating Systems
• Networking
• Distributed Systems
• +4 more

Marios Kogias is an Assistant Professor in the Department of Computing at Imperial College London, conducting research at the intersection of operating systems, networking, and distributed systems with a focus on tail-tolerance, fault-tolerance, and confidentiality using emerging datacenter hardware. He holds a PhD in Computer Science from EPFL (2020) supervised by Ed Bugnion, where his thesis won the Dennis M. Ritchie Award and received an Honourable Mention for the Eurosys Roger Needham PhD Award. His undergraduate degree in Electrical and Computer Engineering is from NTUA. His research spans operating systems, networking, distributed systems, cloud computing, and confidential computing, with significant contributions to microsecond-scale computing, serverless architectures, and eBPF applications. Current work emphasizes tail-latency optimization in datacenter environments and confidential computing security. Recent publications reveal strong trends in microsecond-scale systems, confidential computing, and serverless workflows, demonstrating expertise in leveraging hardware innovations for performance and security guarantees across distributed environments. His scientific awards include: Dennis M. Ritchie Award (2021) Honourable Mention for the Eurosys Roger Needham PhD Award (2021) IBM Fellowship Microsoft Swiss JRC Fellowship Distinguished Artifact Award (ASPLOS 2021) Best Student Paper Award (Eurosys 2020) Dr. Kogias actively mentors PhD students including Konstantinos Prasopoulos (co-advised with Ed Bugnion), Scofield Liu, Farzad Mohammadi, and Adel Sefiane. He teaches Networked Systems, Computer Networks and Distributed Systems, and Object-Oriented Design at Imperial, supported by fellowships from IBM and Microsoft during his doctoral research. His collaborative work spans EPFL, Microsoft Research Cambridge, and Imperial College London, focusing on systems architecture for next-generation datacenter applications.

Muhammed Oğuzhan MeteView profile

Assistant Professor

• Land Management
• Geographic Information Systems
• Cadastre and Property
• +5 more

Muhammed Oğuzhan Mete is an Assistant Professor at the Department of Geomatics Engineering, Faculty of Civil Engineering, Istanbul Technical University. His work bridges Geographic Information Systems (GIS) with advanced computational methods in land valuation and smart city development. Fields of Study : Land Management, GIS, Cadastre and Property Education : PhD in Geomatics Engineering from Istanbul Technical University Research interests focus on integrating GeoAI and Machine Learning for mass real estate valuation , smart city sustainability , and disaster management GIS applications . Recent projects include 3D modeling of historical monuments and cloud-based GIS platforms for earthquake response. Publications demonstrate expertise in hybrid valuation models , spatial big data analytics , and BIM-GIS integration . Research spans Turkey, Great Britain, and international collaborations. Notable work includes a 2025 GeoAI valuation model for Great Britain and 2024 cloud GIS solutions for post-earthquake waste management.

Le GruenwaldView profile

Professor

• Database Management
• Information Privacy and Security
• Mobile and Distributed Databases
• +9 more

Dr. Le Gruenwald is the David W. Franke Professor and Samuel Roberts Noble Foundation Presidential Professor at the School of Computer Science, University of Oklahoma. She also served as Program Director for Data Management Systems at the National Science Foundation (NSF) and held roles including Director of the University of Oklahoma's School of Computer Science. Her academic journey includes a PhD from Southern Methodist University (1990), an M.S. from the University of Houston, and a B.S. in Physics from the University of Saigon, Vietnam. Research Interests: Her work focuses on Database Management Information Privacy & Security Mobile/Distributed Databases Data Mining Quantum Computing Applications in Databases Outlier Detection in Data Streams Key Projects: Includes NSF-funded research on GPU-accelerated spatial data processing, cloud query optimization, and big data hubs. Notable projects: "Spatial Data Management on GPUs" (2013), "Big Data Innovation Hub for the South" (2015), and quantum data science initiatives (2023). Awards: 2012 NSF Directorate Recognition 2007 Distinguished Alumnus Award (SMU) 2009 ACM Recognition Award 2016-2017 Semantic Big Data Workshop Leadership Advising & Grants: Oversees NSF grants totaling millions, focusing on cyberinfrastructure, ecological forecasting, and medical data analytics. No formal student advisees listed but collaborates extensively with researchers globally. Labs & Teams: Leads initiatives in quantum database optimization, mobile-cloud systems, and GPU-accelerated spatial analytics within OU's School of Computer Science.

Jose Manuel Claver IborraView profile

Professor

• Parallel and Distributed Computing
• Cloud Computing
• Video Coding
• +7 more

Dr. José Manuel Claver Iborra is a Full Professor at the Department of Computer Science, School of Engineering (ETSE-UV), University of Valencia. He holds a PhD in Computer Science (Parallel and Distributed Computing program) from the Technical University of Valencia and an MSc in Physics (specialized in Electronics and Computer Science) from the University of Valencia. As an IEEE Senior Member, he focuses on cloud computing, video coding, parallel/distributed systems, reconfigurable computing, and network protocols for real-time applications. Current Research: Cloud-based video encoding, GPU acceleration for DNA analysis, FPGA-based network protocols, and indoor localization systems Academic Leadership: Coordinator of the UV-Tirant node in the Spanish Supercomputing Network (RES) His recent publications analyze GPU-based motion estimation, heterogeneous computing for video standards (H.264/AV1), and QoS scheduling algorithms. He supervises PhD and Master's theses on sensor networks, FPGA programming platforms, and parallel applications. Scientific Awards IEEE Senior Member He has directed funded projects on cloud infrastructure, distributed video processing, and reconfigurable systems since the 1990s.

Tianyin XuView profile

Assistant Professor

• Programming Languages
• Formal Methods
• Software Engineering
• +3 more

Tianyin Xu is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), with a courtesy appointment in the Department of Electrical and Computer Engineering (ECE). His research focuses on ensuring reliability and security in large-scale cloud and datacenter systems, with particular emphasis on configuration management, system verification, and distributed system resilience. He has held positions including a year at Facebook's Core Systems and completed his PhD at the University of California San Diego. Dr. Xu teaches courses such as CS 598(XU) on Cloud-Scale System Reliability, CS 523 (Advanced Operating Systems), and CS 423 (Operating Systems Design). He actively contributes to academic communities through roles like co-editing the SIGOPS Blog, serving on program committees for conferences like NSDI, OSDI, and EuroSys, and organizing the UIUC Systems Research Seminar. His research has been recognized with awards including the 2025 Best Paper Award at ASPLOS, 2024 Jay Lepreau Best Paper Award, and NSF CAREER Award. His work has led to impactful contributions like the Sieve framework for testing configuration changes and the Rex tool for kernel extension safety. Dr. Xu advises a vibrant group of students and collaborates with industry partners including VMware, IBM, and Intel. His lab focuses on advancing system reliability through innovative tools and methodologies.

• Computer Science
• Artificial Intelligence
• Cybersecurity
• +7 more

Matteo Trentin is a PhD student at the Department of Mathematics and Computer Science (University of Southern Denmark), focusing on Artificial Intelligence , Cybersecurity , and Programming Languages . His research intersects Serverless Computing , Resource Allocation , and Static Program Analysis , with a strong emphasis on Scheduling Policy and Domain-Specific Languages . Current affiliation: Department of Mathematics and Computer Science, University of Southern Denmark Research themes: Cloud systems, runtime environments, cost-aware scheduling, and formal methods Collaborations: International work with researchers in software architecture and formal verification His publications address topology-aware allocation , affinity-aware function scheduling , and formal specification of FaaS policies , often leveraging domain-specific languages and static analysis to optimize serverless platforms . Key trends include cloud resource management , operational semantics , and service platform engineering .

• Computer Science
• Intelligent Transportation Systems
• Cloud Computing
• +3 more

Fatemeh Banaie Heravan is a Research Fellow in the Department of Computer Science at the University of Huddersfield's School of Computing and Engineering. She is also a member of the Centre for Autonomous and Intelligent Systems, contributing to interdisciplinary research in computational methodologies and decision-making systems. University: University of Huddersfield School: School of Computing and Engineering Department: Department of Computer Science Rank: Research Fellow Email: F.Banaieheravan@hud.ac.uk Her research intersects with UN Sustainable Development Goals , focusing on technological solutions for global challenges. Key areas include: Serverless computing and energy-efficient cloud architectures Intelligent transportation systems and game theory for autonomous decision-making Participatory budgeting interfaces and collective decision-making platforms Recent publications highlight trends in cloud computing (2023-2024), deception modeling in transportation (2025), and democratic decision-making technologies (2024). Labs & Collaborations: Active in the Centre for Autonomous and Intelligent Systems, collaborating with experts like Dr. Parkinson and Prof. Pournaras on modular experimentation platforms.

Rich WolskiView profile

Professor

• Distributed Systems
• Cloud Computing
• Operating Systems
• +3 more

Rich Wolski is a Professor of Computer Science at the University of California, Santa Barbara (UCSB), holding the Duval Family Presidential Chair in Energy Efficiency. He previously held positions at UC San Diego, UC Knoxville, and research roles at Lawrence Livermore and Berkeley National Laboratories. His research focuses on distributed systems, cloud computing, and energy efficiency, including pioneering the Eucalyptus open-source cloud project and leading the RiPiT carbon emissions initiative. Education: Ph.D./M.S. in Computer Science from UC Davis (1994/1989), B.S. from Cal Poly San Luis Obispo (1986). Research Interests: Distributed systems, cloud computing architectures, resource-aware systems, and energy-efficient computational frameworks. Current projects include CSPOT (serverless IoT platform), RiPiT (carbon emissions measurement), SmartFarm, and the Aristotle Federated Cloud. He co-leads UCSB's RACELab with Chandra Krintz and collaborates with the Institute for Energy Efficiency. Awards: Includes Top-10 Cloud Pioneers (2012), multiple teaching awards, and industry recognitions for cloud innovation. Teaching: Leading CS170 (Operating Systems) in Winter 2025. Notable past courses include systems programming and distributed computing lectures.

György DánView profile

Professor

• Applied Game Theory
• Critical Infrastructure Security
• Edge Computing
• +5 more

György Dán is a Professor in Teletraffic Systems at KTH Royal Institute of Technology, Stockholm, Sweden. He holds a Ph.D. in Telecommunications from KTH (2006) and has extensive academic leadership roles, including Director of Third Cycle Education. His research focuses on networked systems design, with expertise in critical infrastructure security, edge computing, and cyber-physical systems. Dán has supervised over 20 PhD students and led major projects like VR DICE6G and REACT. He has authored/co-authored over 150 publications, receiving awards such as the Ericsson Research Foundation Award (2010-2014) and the 2020 KTH PhD Supervisor of the Year. Education Ph.D. in Telecommunications, KTH Royal Institute of Technology (2006) M.Sc. in Business Administration, Corvinus University of Budapest (2003) M.Sc. in Computer Engineering, Budapest University of Technology and Economics (1999) Research Interests His work spans applied game theory, smart grid security, mobile edge computing, and adversarial machine learning. Current projects include resilient edge computing systems and secure AI for cyber-physical infrastructures. Awards & Recognition Best Paper Awards at SNCNW 2025, IEEE SmartGridComm 2014, and IEEE Infocom 2008 Fulbright Visiting Scholar (University of Illinois, 2012-2013) Invited Professor at EPFL (2014-2015) Labs & Collaborations He leads the Network and Systems Engineering Division at KTH, collaborating with industries like Ericsson and ABB. His group focuses on experimental platforms like the GreenEyes testbed and stateful serverless edge computing.

Rohan Basu RoyView profile

Assistant Professor

• Parallel Computing
• Distributed Systems
• Cloud Computing
• +3 more

Rohan Basu Roy is an Assistant Professor (tenure-track) at the University of Utah, affiliated with the Kahlert School of Computing and the SCI Institute. His research focuses on optimizing parallel and distributed computing systems, including cloud, serverless, and HPC environments, with an emphasis on sustainability and cost-effectiveness. He holds a Ph.D. in Computer Engineering from Northeastern University, advised by Prof. Devesh Tiwari. Affiliations: University of Utah (Kahlert School of Computing), SCI Institute. His research interests include scheduling algorithms, energy efficiency, and environmental sustainability in computing systems. He has pioneered open-source tools like GreenMix and ECOLIFE , widely adopted in the systems research community. Awards: ACM-IEEE CS George Michael Memorial HPC Fellowship (2023), MLCommons ML and Systems Rising Star (2023), Northeastern University Excellence in Research Award (2023). Rohan has served as a program committee member for top-tier conferences (ASPLOS, HPCA, SC) and co-chaired tracks such as AI/ML for Systems at HiPC 2025. He has also delivered invited talks at Google Brain and ParslFest 2023.