Serverless Cloud Computing Professors and Supervisors

Harry HochheiserView profile

Assistant Professor

National Research Institute for Mathematics and Computer ScienceNetherlands

Harry Hochheiser is an Assistant Professor in the Department of Biomedical Informatics at the University of Pittsburgh School of Medicine, where he also serves as Associate Director of the Biomedical Informatics Training Program. His academic career spans multiple disciplines at the intersection of computing and healthcare, with a strong focus on human-computer interaction, bioinformatics, and medical informatics. Dr. Hochheiser's research interests include human-computer interaction, information visualization, bioinformatics, universal usability, security, privacy, and public policy implications of computing systems. His work particularly focuses on NIH-funded projects related to bioinformatics research portals, visualization for review of chart records, and tools for aiding the discovery of animal models of human diseases. His research demonstrates a commitment to developing technology that addresses real clinical needs while considering user experience and ethical implications. His publication record shows consistent scholarly output across multiple domains, with recent work emphasizing biomedical informatics, machine learning applications in healthcare, epidemiological modeling, and academic publishing practices. His research demonstrates a strong interdisciplinary approach that bridges computer science with clinical medicine and public health, with particular attention to human-centered design principles in healthcare technology. Editorial Board Member, PeerJ - the Journal of Life & Environmental Sciences Editorial Board Member, PeerJ Computer Science Over 2,900 points on PeerJ representing 2,800 editorial contributions and 105 reviews Dr. Hochheiser has made significant contributions across numerous subject areas including Science and Medical Education, Science Policy, Statistics, Human-Computer Interaction, Computational Science, Bioinformatics, and many others. His work has practical implications for healthcare technology development, particularly in creating more effective, user-friendly systems that address real clinical needs while considering privacy and security concerns.

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Gul AghaView profile

Professor

Menlo CollegeUnited States

Gul Agha is a distinguished Professor of Computer Science at the University of Illinois at Urbana-Champaign and Director of the Open Systems Laboratory. His career spans over three decades of pioneering research in concurrent and distributed computing systems. Professor Agha's research focuses on the actor model of computation, formal methods, and statistical model checking. His work bridges theoretical foundations with practical applications in distributed systems, programming languages, and verification techniques. He has made seminal contributions to understanding concurrent computation through his development of the actor model framework. His publication record shows consistent contributions from the 1980s through the present, with recent work focusing on verification of safety-critical systems, serverless computing optimization, and advanced techniques for distributed actor systems. The trend in his research demonstrates a progression from theoretical foundations to practical applications in modern computing environments including cloud infrastructure and IoT systems. His scientific achievements have been recognized with numerous prestigious awards: Fellow of the IEEE (2002) IEEE Computer Society Meritorious Service Award Golden Core Member of the IEEE Computer Society International Lecturer for the ACM (1992-1997) ACM Fellow (2018) for research in concurrent programming and formal methods Professor Agha has supervised numerous graduate students and postdoctoral researchers through the Open Systems Laboratory. His laboratory has secured substantial research funding for projects in distributed systems, formal verification, and wireless sensor networks. His work on the actor model has influenced both academic research and industry practices in concurrent and distributed computing. As Director of the Open Systems Laboratory, Professor Agha leads a research group focused on advancing the state of the art in distributed and concurrent systems. The laboratory serves as an intellectual hub for theoretical and practical research in open distributed systems, with projects spanning from foundational theory to real-world implementations in areas like structural health monitoring and cloud computing.

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Muhammad Mustafa RafiqueView profile

Associate Professor

Rochester Institute of Technology (RIT)United States

Muhammad Mustafa Rafique is an Associate Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. His research specializes in optimizing large-scale computing systems, with focus areas including: High-performance computing (HPC) resource management Distributed deep learning acceleration Fault-tolerant cloud architectures GPU-accelerated checkpointing systems Serverless computing frameworks Dr. Rafique's work demonstrates consistent innovation in improving computational efficiency for containerized HPC workflows, multi-GPU scheduling, memory optimization, and distributed training pipelines. His publications frequently appear in premier IEEE/ACM conferences, reflecting contributions to systems performance engineering. While no awards or student advisees are mentioned in available materials, his research collaborations include co-authors from institutions worldwide, indicating active engagement in the high-performance computing research community. Current work explores emerging memory technologies like CXL and advanced containerization techniques for next-generation datacenters.

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Jie LiuView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Jie Liu is a Researcher at the Institute of Software, Chinese Academy of Sciences and a Professor and Doctoral Supervisor at University of Chinese Academy of Sciences. He is also a Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and an Executive Committee Member of the System Software Committee of the CCF Computer Society. His research is conducted within the Software Engineering Technology R&D Center. Dr. Liu received his Ph.D. from the University of Science and Technology of China in 2011 and his B.A. from the same institution in 2004. He has progressed through the ranks at the Institute of Software, CAS, starting as an Assistant Research Fellow (2011-2014), then Associate Research Fellow (2014-2024), and currently as a Researcher (since 2024). His research spans Big Data Intelligent Analysis Models and Systems at the intersection of AI, Software Engineering, and System Software. Specifically, his work covers three main areas: Big Data and Machine Learning Systems (statistics and AI algorithm model libraries, data quantitative analysis tools, LLM reasoning optimization, Earth Big Data); Intelligent Software Engineering (code model constraint decoding, data science agents, system log analysis agents); and Knowledge-Enhanced Intelligent Model Construction (knowledge extraction, knowledge graphs, domain AI model design). His research has resulted in innovative approaches to handling complex data analysis challenges across multiple domains. Dr. Liu's research has produced significant outcomes including EarthDataMiner, which supports SDG indicator calculations and won the 2024 Beijing Municipal Science and Technology Progress First Prize. His work on RISC-V software migration technology has been integrated into the Ruiqian tool (https://rvpt.top/), demonstrating practical applications of his research in emerging computing architectures. Beijing Science and Technology Progress Award, First Prize, 2024 2023 Surveying and Mapping Science and Technology Award, Special Prize, 2023 DASFAA Best Paper Runner-up, Second Prize, 2013 Dr. Liu has successfully guided numerous graduate students who have secured positions at major technology companies including Alibaba, ByteDance, Southern Power Grid, and Agricultural Bank of China. He has secured funding through multiple National Natural Science Foundation projects, National Key R&D Program projects, and over ten other research initiatives. His research collaborations span industry leaders like Huawei, JD.com, and TravelSky, as well as academic institutions within the Chinese Academy of Sciences. He teaches graduate courses such as 'Machine Learning Systems' and 'Cloud Computing and Big Data Technology' at University of Chinese Academy of Sciences, and has established a research group focused on developing innovative solutions at the intersection of AI and software engineering with real-world applications in earth sciences, healthcare, and intelligent systems.

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Wei ChenView profile

Professor

Max Planck Institute for Security and PrivacyGermany

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.

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Luciano BaresiView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Luciano Baresi is a Full Professor at the Polytechnic University of Milan (Politecnico di Milano), Italy, affiliated with the Department of Electronics, Information and Bioengineering. He earned his laurea (MSc) and PhD in Computer Science from the same institution and has held visiting positions at the University of Oregon (USA), Tongji University (China), and the University of Paderborn (Germany). His research spans software engineering, with current focuses on self-adaptive systems, edge computing, and AI/ML-based software. His work integrates formal methods with practical applications, emphasizing autonomous systems, cloud-edge continuum, and federated learning. Recent publications highlight AI-driven advancements in software testing, resource optimization, and educational tools. Key research themes include: AI/ML for autonomous driving testing and data augmentation Serverless computing at the edge Federated learning system architectures Containerization and cloud resource management Awarded for impactful contributions: RE 2020 Most Influential Paper ICSOC 2020 Best Paper SEAMS 2022 Best Paper He advises 14+ PhD students and leads projects like Ketonet (health app), WHO's Essential Items Estimator, and dynaSpark. As Editor-in-Chief of Proceedings of the ACM on Software Engineering and senior editor for multiple journals, he shapes academic discourse in adaptive systems and software engineering.

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Mohammad Adnan HamdaqaView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Mohammad Adnan Hamdaqa is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), where he leads the Software and Emerging Technologies Lab. He holds a Ph.D. in Software Engineering from the University of Waterloo (2016), along with a Master's in Electrical and Computer Engineering from Concordia University, an MBA from New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of emerging technologies and software engineering, particularly how software engineering approaches can be adapted for new platforms like Cloud Computing and Blockchain. His work spans model-driven software engineering, cloud applications, and blockchain technologies. Analysis of his recent publications reveals a strong emphasis on blockchain technology, especially smart contracts and Ethereum, with significant work on security, evolution, and visualization of these systems. His research also demonstrates growing integration of large language models in software engineering tasks, particularly for model specification and code generation. There's also a notable thread of work on sustainability in infrastructure as code and security practices across cloud platforms. Hamdaqa actively contributes to the academic community as a member of IEEE Computer Society and ACM, and has served on program committees for numerous conferences in software engineering and services communities. He has successfully supervised multiple Master's students, with recent theses focusing on smart contract auditing, epidemiological modeling using model-driven approaches, and security practices in infrastructure as code. His lab maintains active research in both theoretical and applied aspects of software engineering for emerging technologies.

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Ji-Yong ShinView profile

Assistant Professor

Northeastern UniversityUnited States

Ji-Yong Shin is an Assistant Professor in the Khoury College of Computer Sciences at Northeastern University, where he has been faculty since 2020. Previously, he served as an Associate Research Scientist at Yale University after completing his Ph.D. at Cornell University. His research bridges systems design and formal verification to ensure correctness in complex distributed systems. His educational background includes: Ph.D. in Computer Science from Cornell University Professor Shin's research focuses on co-designing systems and formal verification methods to simplify correctness proofs without sacrificing performance. Key areas include distributed systems (consensus protocols like Raft/Paxos), serverless computing for stateful applications, cloud storage leveraging emerging hardware (persistent memory, RDMA), and system support for deep neural networks. His Atomic Distributed Objects (ADO) model abstracts network behaviors to enable compositional reasoning of distributed systems. His publication trend (2020-2025) shows consistent contributions to top-tier venues (PLDI, OOPSLA, NSDI, VLDB), with recent work emphasizing blockchain verification (LiDO-DAG), reconfiguration protocols (ReCraft), and storage systems (FusionFlow). This reflects a cohesive research trajectory where formal methods solve practical systems challenges in distributed computing. His scientific recognition includes: NSF CAREER Award (2025) He currently advises PhD student Bryant Curto and actively recruits new students, focusing on systems and formal methods. His funded research includes an NSF FMitF grant (2020) with Zhong Shao and Robert Soule for formal methods in cloud infrastructure. He also serves in leadership roles including HotStorage 2025 Co-General Chair and PC member for OOPSLA 2026, NSDI 2026, and USENIX ATC 2025. Professor Shin jointly runs the systems research group at Northeastern, collaborating on projects spanning distributed systems verification, serverless computing enhancements, and storage system optimizations using next-generation hardware.

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