Find Academic Supervisors

• Geostatistics
• Big Data Processing
• Computer Systems
• +6 more

Dr. John Zigman is an academic affiliated with the Faculty of Engineering at The University of Sydney. His research spans interdisciplinary fields including geostatistics, big data processing, and computer systems optimization. He has contributed to advancements in geological boundary modeling, memory management frameworks for hybrid systems, and Java performance analysis. Key research interests include: Geological modeling using Bayesian approaches and dynamic time warping Development of holistic memory management systems (e.g., Panthera framework) Optimization of parallel computing architectures and distributed garbage collection Integration of geophysical data with autonomous spatial modeling algorithms Recent work focuses on photonic integrated circuits (2025), Java performance re-engineering (2025), and large-scale geological boundary rectification (2023). His publications demonstrate expertise in both theoretical computer science and applied geosciences. Notable collaborations include work with Prof. Arman Melkumyan on geostatistical applications and Prof. Stephen Blackburn on persistent Java systems. His research bridges computational methods with earth sciences, addressing challenges in resource exploration and data-intensive systems.

Antony HoskingView profile

Professor

• Programming Languages
• Software Systems
• Software Assurance
• +7 more

Antony Hosking is a Professor and School Director of the School of Computing at the Australian National University (ANU). He holds a BSc in Mathematical Sciences from the University of Adelaide (1985), MSc with First Class Honours in Computer Science from the University of Waikato (1987), and a PhD in Computer Science from the University of Massachusetts Amherst (1995). Prior to ANU, he served for over 20 years at Purdue University as Assistant Professor and later tenured Associate Professor of Computer Science. He is also an Honorary Professor at the University of Massachusetts Amherst. His research focuses on programming languages, software systems, and software assurance, with particular expertise in garbage collection, memory management, compiler optimizations, and architectural support for programming languages. He co-authored the seminal reference text *The Garbage Collection Handbook*, now in its second edition (2023), and has contributed extensively to conferences like ACM SIGPLAN. He has held leadership roles in professional organizations, including the Executive Committee of ACM SIGPLAN and the International Symposium on Memory Management. Hosking’s accolades include being a Distinguished Scientist of the Association for Computing Machinery (ACM), an elected member of Association Internationale pour les Technologies Objets (AITO), and a Professional Member of IEEE. His consulting work involves intellectual property litigation in US courts and the US Patent and Trademark Office. He has advised on high-performance garbage collectors, concurrency, and real-time systems, with a focus on energy-aware and persistent storage solutions. His recent work addresses foundational assurance in systems software, aiming to build trustworthy systems. He collaborates on projects like the Single-Chip Cloud Computer and explores portable performance for parallel managed languages across multi-core architectures.

Nisansala YatapanageView profile

Senior Lecturer

• Formal Methods
• Concurrency Verification
• Safety-Critical Systems
• +7 more

Nisansala Yatapanage is a Senior Lecturer at the Australian National University (ANU) since January 2025, and served as a Lecturer from 2022 to 2024. She holds the position of Interim Associate Director of Engagement and Impact in the School of Computing within the ANU College of Systems & Society. Prior to ANU, she was a Senior Lecturer/Lecturer at De Montfort University, Leicester, U.K. (2017-2019), and worked with Prof. Cliff Jones at Newcastle University, U.K. (2013-2017) on the "Taming Concurrency" project. Her educational background includes a PhD from Griffith University (2012), supervised by Dr. Kirsten Winter. Before her PhD, she was a researcher in the ARC Centre for Complex Systems and Griffith University (2004-2007), working on specification and verification for safety-critical systems using Behavior Tree language and model checking. Nisansala's research focuses on the application of formal methods for various applications, particularly in concurrency, safety-critical systems, and security. She is currently investigating concurrency verification using rely/guarantee, separation logics, and temporal logic. Her work also explores the verification of security protocols and the foundations of concurrency, with recent research examining the links between rely/guarantee reasoning and linearisability for non-blocking algorithms. She has developed techniques for reducing Behavior Tree models prior to model checking and created a novel form of branching bisimulation called "Next-preserving Branching Bisimulation." Her publications demonstrate a consistent focus on formal verification methods, with particular emphasis on concurrency and safety-critical systems. Over the years, her work has evolved from Behavior Tree specifications and model checking to more advanced techniques involving rely/guarantee reasoning and separation logic. Recent publications show increasing focus on security protocols and the theoretical foundations of concurrent systems. Fellow of AdvanceHE Commended in Australian Photographer of the Year Competition 2020 (Travel category) Nisansala has extensive teaching experience across multiple institutions. At ANU, she has served as Course Convenor for multiple courses including COMP4011/8011 Special Topics in Formal Methods and Programming Languages, COMP1600 Foundations of Computing, and COMP1100/1130 Programming as Problem Solving. Previously at De Montfort University, she was Deputy Programme Leader of the BSc Computer Science & BSc Software Engineering degrees and Course Convenor for Data Structures & Algorithms and Concurrent & Parallel Algorithms. She has also taught at the ANU Logic Summer School. She has been involved in several significant research projects including "Taming Concurrency" at Newcastle University (2013-2017), a Model-Based Safety Analysis of Air Traffic Control Operational Procedures at UQ (2011-2012), and her PhD project on Slicing Behavior Trees for Verification of Large Systems at Griffith University (2007-2011).

Sudhakaran SnehaView profile

Assistant Professor

• Cyber Security
• Android Security
• Application Security
• +5 more

Sudhakaran Sneha is an Assistant Professor at Florida Institute of Technology (FIT), based in the College of Engineering and Science's Department of Electrical Engineering and Computer Science. She holds a Ph.D. from Louisiana State University (2017-2022) and has extensive research experience in cyber security, including roles as a Research Assistant at LSU's Applied CyberSecurity Lab and Cyber Physical Systems Lab. Her work focuses on Android Security, Cyber Forensics, Application Security, and Machine Learning applications in cyber defense. She is certified as a CEH (Certified Ethical Hacker) and CHFI (Computer Hacking Forensic Investigator). Dr. Sneha's research emphasizes memory forensics, mobile security, and threat analysis, with notable contributions to tools like AmpleDroid and DroidScraper for Android memory analysis. She has authored 8 technical papers and presented at leading conferences including IEEE S&P and RAID. Her work has been recognized with awards from WiCyS and Louisiana State University. Education background includes a B.Tech and M.Tech from Indian institutions (AWH Engineering College and Amrita Vishwa Vidyapeetham). Professional experience spans academia and industry, including teaching at MG University (India) and a cyber security internship at GJ Forensics. Current teaching focuses on Cyber Operations, and she actively reviews for journals like COSE and conferences such as WiSec, where she served as poster chair in 2024. Her professional network includes affiliations with ResearchGate, Google Scholar, and LinkedIn. Funding opportunities are currently unavailable, but students may contact her directly for potential research collaborations.

• Graph Transformation
• Graph-Based Programming Models
• Rewriting Systems
• +1 more

Detlef Plump is a Senior Lecturer in the Department of Computer Science at the University of York, UK, where he has worked since 2001. His academic journey includes roles as Assistant Professor at the University of Bremen (1993-2000), Lecturer at the University of York (2000-2001), and Research Associate at the University of Bremen (1987-1993). He holds a Dipl.-Inform degree, Dr.-Ing, and Habilitation from the University of Bremen. His research focuses on graph transformation, graph-based programming models, and rewriting systems, with contributions to theoretical computer science. He has held visiting researcher positions at Heriot-Watt University (Edinburgh), the University of Nijmegen, and the Free University of Amsterdam, accumulating over two years of collaborative research in the Netherlands. At York, he serves as ECA Officer and Programme Leader for the CS/Maths Undergraduate Programmes. His contact details include office CSE/035 and phone +44 (0)1904 325670. His work integrates formal methods with practical applications in graph computation models and algorithm design. Detlef’s contributions span graph program compilers, verification techniques, and theoretical foundations, as evidenced by his extensive publication record in venues like the Journal of Logical and Algebraic Methods in Programming. He emphasizes efficiency and correctness in graph-based systems, addressing challenges in both academia and industry.

• Computer Architecture
• High-Performance Computing (HPC)
• Cloud Computing
• +4 more

Prof. Weikuan Yu is a Professor in the Department of Computer Science at Florida State University. His research focuses on computer architecture, high-performance computing (HPC), cloud computing, parallel file systems, and deep learning applications. He holds the role of Chair and can be contacted via yuw@cs.fsu.edu or (850) 644-5442. His expertise includes optimizing storage systems and I/O behaviors in scientific workflows, developing scalable distributed systems, and applying machine learning to improve computational efficiency. Notable projects include work on burst buffer systems (e.g., BurstFS, TRIO), persistent memory management (PHAST), and distributed deep learning frameworks (e.g., compression techniques for time-evolutionary data). Recent research trends emphasize enhancing HPC storage efficiency through novel file systems and I/O emulation, as well as leveraging machine learning for fault tolerance and configuration tuning. His work bridges hardware-software co-design to address challenges in exascale computing and big data analytics. Prof. Yu has contributed to multiple open-source projects and frameworks, including OpenSHMEM-based key-value stores and MapReduce optimizations. His publications highlight advancements in parallel processing, distributed algorithms, and energy-efficient memory architectures.

Abigail KoayView profile

Research Fellow

• Cyber Security
• Machine Learning
• Industrial Control System (ICS) Security
• +3 more

Dr. Abigail Koay is an Honorary Research Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. Her research focuses on cybersecurity, machine learning applications in industrial systems, and healthcare technology. She has contributed to projects such as real-time cyber-attack detection using weakly supervised learning, supported by UQ Cyber Seed Funding (2021–2022). Her work spans multiple disciplines including: Cybersecurity for Industrial Control Systems (ICS) IoT network anomaly detection using fog-assisted frameworks Machine learning for medical imaging (e.g., glaucoma detection) AI-driven cybersecurity strategies for smart grids Recent publications highlight advancements in: Irregular time series analysis using GNNs Positive-unlabeled learning with random forests Domain generalization in retinal image analysis Dr. Koay has authored/co-authored 15+ peer-reviewed articles across journals like Frontiers of Computer Science , IEEE Access , and conferences including NeurIPS and ISGT Asia. She collaborates with industry partners on projects like Plan2Defend for smart grid security and SDGen for synthetic cybersecurity dataset generation. Her research integrates theoretical machine learning with practical cybersecurity challenges, emphasizing real-world applicability in critical infrastructure and healthcare systems.

Paul KrogmeierView profile

Research Fellow

• Programming Languages
• Logic
• Program Synthesis
• +7 more

Paul Krogmeier is a postdoctoral fellow at Harvard University's School of Engineering and Applied Sciences (SEAS), advised by Nada Amin and Walter Fontana. His research bridges programming languages, logic, and program synthesis with applications in interpretable machine learning and computational universality. Starting Fall 2026, he will join the University of Colorado Boulder as an assistant professor in computer science. His educational background includes a PhD from the University of Illinois under Madhusudan Parthasarathy. Dr. Krogmeier investigates computational universality under errors, formal expressivity of neural networks, and symbolic language emergence. His work connects evolutionary processes with learning mechanisms and rigorously characterizes creativity through computational models. Ongoing projects focus on DSL synthesis for few-shot learning and developing frameworks where symbolic language emerges from computational processes. His publication record shows consistent contributions to programming languages theory (OOPSLA, POPL) with increasing integration of machine learning techniques. Key themes include program synthesis, logic-based learning, and formal analysis of neural architectures, demonstrating interdisciplinary rigor across theoretical computer science and AI. His scientific achievements include: Distinguished Paper Award at OOPSLA 2023 Distinguished Paper Award at POPL 2022 While currently not advising students as a postdoc, he will establish an advising program at CU Boulder. His research is supported by institutional resources at Harvard SEAS with potential future funding from NSF and computing industry partnerships. At Harvard, he collaborates within Nada Amin and Walter Fontana's research group, which explores foundational programming language concepts applied to machine learning systems and biological computation models.

• Programming Languages
• Functional Programming
• Type Systems
• +4 more

Ningning Xie is an Assistant Professor in the Department of Computer Science at the University of Toronto, with a part-time role as a Research Scientist at Google DeepMind and a Faculty Affiliate at the Schwartz Reisman Institute. Her research focuses on programming languages, particularly functional programming, type systems, and logics, with applications in broader domains. Ph.D. from the University of Hong Kong B.S. from Zhejiang University Her work explores foundational and applied aspects of programming languages, including: Multi-stage programming and staging techniques Type systems and type inference Algebraic effect handlers and concurrency Compiler design and optimization Recent publications highlight advancements in type inference, effect handlers, and parallel computing. She actively contributes to academic service as a program chair and committee member for conferences like PEPM, Haskell, and POPL. ACM SIGPLAN Distinguished Paper Award (ICFP'25, PLDI'25, PLDI'21) Cambridge Hall of Fame Awards: Publication of the Year As a mentor, she seeks motivated students for her research group. Her affiliations with Google DeepMind and Schwartz Reisman Institute facilitate interdisciplinary collaboration.

Danko BaschView profile

Professor

• Computer Engineering
• Microprocessor Architecture
• Simulation and Modeling
• +3 more

Prof. Dr. Danko Basch is a Full Professor at the Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing (FER), University of Zagreb. His work focuses on microprocessor architecture , memory management algorithms , and simulation tool development . In research, Basch has contributed to: Computer Architecture Simulation : ATLAS toolset development Garbage Collection Algorithms : Copying, generational, and marking algorithms Simulation Languages : GPSS++ and Java extensions Memory Management Systems : Allocation strategies and performance optimization His work also extends to educational tools (FRISC/ARM processor guides) and software development (AGCS simulator, Moodle extensions).

• Static analysis
• Dynamic Analysis
• Abstract interpretation
• +5 more

Quentin Stiévenart is a post-doctoral researcher at the Software Languages Lab of the Vrije Universiteit Brussel (VUB) in Belgium, specializing in programming languages and program analysis. His research spans multiple areas within static and dynamic analysis, with a particular focus on WebAssembly security and analysis techniques. His primary research interests include: Static and dynamic program analysis Abstract interpretation Type systems and effect systems Concurrent and higher-order programming languages WebAssembly security and analysis Interpreter and framework design Stiévenart's recent publications demonstrate a strong focus on compositional and modular analysis techniques, particularly applied to WebAssembly. His work addresses critical security concerns in WebAssembly, including information flow analysis, binary analysis, and vulnerability detection. He has also contributed to frameworks for static analysis of higher-order languages and techniques for improving analysis performance through parallelism and incremental computation. His academic service includes extensive peer review activities and program committee membership for major conferences including SAS, SCAM, ICFP, ECOOP, and OOPSLA, with a particular emphasis on artifact evaluation committees. Stiévenart has developed several research tools including Wassail (a static analysis tool for WebAssembly security), MAF (a framework for modular static analyses), and Scala-AM (a framework for developing static analyses in Scala).

Paulo FerreiraView profile

Professor

• distributed systems
• programming of mobile devices
• concurrency / parallelism / replication
• +4 more

Paulo Ferreira is a Professor in the Department of Informatics at the University of Oslo's Faculty of Mathematics and Natural Sciences. He specializes in programming technology with a focus on distributed systems, mobile computing, and fog/cloud computing. His research interests include: Distributed systems and programming of mobile devices Concurrency, parallelism, and replication Fog and cloud computing architectures Software security and adaptability Algorithms for garbage collection Professor Ferreira teaches "Programming Ubiquitous Things" (IN5600) in Spring and "Fog and Cloud Computing" (IN5700) in Autumn. His recent publications show a strong focus on transport mode detection using edge and fog computing, garbage collection optimization, and mobile application development. His work demonstrates trends toward more efficient resource utilization in distributed environments, particularly in mobile and edge contexts. He has received numerous awards including: Best Prize for Master Thesis supervision (Norsk Regnesentrals pris, Dec. 2023) Two Best Paper Awards at the ACM/IFIP/Usenix Middleware Conference Recognition of Service Award from ACM "Excellent teaching" awards at the University of Lisbon (2010/2011 and 2013/14) Professor Ferreira currently supervises PhD students Mahdieh Kamalian (transport mode detection) and Lyla Naghipour Vijouyeh (fog emulator development). He has led more than 15 research projects, served as an expert for the European Union for assessment of projects proposals under the 7th Framework Program, and serves on various program committees (e.g. Middleware, ICDCS, DAIS, etc.). He is a senior member of ACM and IEEE, serves on the editorial board of the Springer Journal of Internet Services and Applications, and is a member of the Steering Committee of EuroSys (ACM European Chapter of the Special Interest Group on Operating Systems).

Luís Antunes VeigaView profile

Associate Professor

• Distributed systems
• Cloud computing
• Grid computing
• +5 more

Luís Antunes Veiga is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), Universidade de Lisboa, and a Senior Researcher at INESC-ID Lisboa, where he is Vice-Coordinator of the Computing Systems and Communication Networks Laboratory and of the Distributed Systems Group. He has held roles such as Scientific Coordinator of the Distributed, Parallel and Secure Systems research area, Vice-Head of Department for Academic Matters, and Coordinator of the MSc programme in Information Systems and Computer Engineering (MEIC). Education: Details of degrees not explicitly listed, but career progression from Teaching Assistant (2001) to Associate Professor (2015) indicates completion of PhD and other qualifications. Research Interests: His work lies at the intersection of distributed systems and cloud computing, with a focus on: Virtualization & Cloud Infrastructure: Virtual machines, container technologies, and serverless (FaaS) platforms. Data Management & Consistency: Replication strategies, consistency models, and garbage collection for large-scale systems. Edge & P2P Computing: Extending cloud abstractions to edge devices and community networks, peer-to-peer middleware, and mobile computing. Recent Publication Trends: Over the last three years, his research output has concentrated on serverless computing at the edge , analyzing performance, cost, and scheduling strategies. Key contributions include novel utility-driven placement algorithms and lightweight orchestration frameworks that reduce cold-start latency while respecting edge resource constraints. Scientific Awards: Nominated for Best Researcher Award 2019, INESC-ID Lisboa. Advising & Grants: He has successfully supervised more than nine PhD students as primary advisor (including joint programmes with UCLouvain, UPC, and University of Maryland) and numerous MSc students. Funding has been secured through: EU Programmes: CloudStars (MCSA), MoTiV (H2020), CloudForEurope (FP7), TIMBUS (FP7). National FCT Projects: novaVM, ContexTWA, PROSOPON, Synergy, RepComp, GINGER. Labs & Teams: He leads activities within the Distributed Systems Group , coordinates the INESC-ID Computing Systems and Communication Networks Laboratory , and is a member of the IST Scientific Council (2023–).

Rodrigo BrunoView profile

Assistant Professor

• Systems
• Programming Languages
• Cloud Computing
• +4 more

Rodrigo Bruno is an Assistant Professor at Instituto Superior Técnico (University of Lisbon) and Senior Researcher at INESC-ID Lisbon. His research bridges Systems and Programming Languages with a focus on optimizing language runtimes for cloud environments (Microservices, Serverless). He previously worked at Oracle Labs Zurich and ETH Zurich. Research Areas Systems Programming Languages Cloud Computing Serverless Computing Operating Systems Key projects include Shell (FCT-funded serverless platform), Graalvisor (polyglot runtime virtualization), and Naos (RDMA networking in Java). His work appears in top venues like NSDI, EuroSys, ATC, and SoCC. Scientific awards include the EdgeEmu Best Paper Award , Best Young Researcher 2022 (INESC-ID), and multiple teaching excellence recognitions. He has served on program committees for EuroSys, NSDI, ATC, and more. Rodrigo Bruno leads a dynamic team including PhD candidates Vasyl Lanko, Bernardo Ribeiro (co-advised), and MSc students like André Páscoa. His research integrates with production systems such as the V8 JS Engine and OpenJDK HotSpot JVM. Current teaching includes Cloud Computing and Virtualization , Computer Systems Engineering , and IT Infrastructure Management . His service spans organizing committees for SESAME, MoreVMs, and artifact evaluation for SOSP.

Stefan K. MullerView profile

Assistant Professor

• Type Systems
• Parallel Computing
• Resource Analysis
• +3 more

Stefan K. Muller is an Assistant Professor in the Computer Science Department at Illinois Institute of Technology. His research focuses on applying programming language techniques to improve correctness and efficiency in parallel computing, with applications spanning AI, computer science education, and systems design. He earned his PhD at Carnegie Mellon University (2018) under Umut A. Acar, following a postdoc there (2018–20), and holds an AB in Computer Science from Harvard University (2012). PhD, Carnegie Mellon University (2018) Postdoc, Carnegie Mellon University (2018–20) AB, Harvard University (2012) Stefan’s work integrates type systems, static resource analysis, and concurrency to address challenges in parallelism. His recent projects include Graph Types for language-agnostic parallel computation analysis, Responsive Parallelism models for interactive systems, and Resource-aware GPU Programming tools. He has contributed to conferences like POPL, PLDI, ICFP, and SPLASH, often focusing on deadlock detection, futures-based parallelism, and efficient compiler optimizations. His publications (2012–2024) emphasize formal methods for parallel systems. Key trends include type-driven concurrency, static analysis of GPU programs, and responsive scheduling for interactive applications. He mentors students in programming language theory and parallel computing, with former advisees now at institutions like Apple, Amazon, and UPenn. Stefan’s teaching includes courses on Types and Programming Languages (CS534), Science of Programming (CS536), and Compiler Construction (CS443). Outside academia, he is a homebrewer, runner, and singer, with a Bacon number of 2 and Erdős number of 4 .