Find Academic Supervisors

George DanezisView profile

Professor

• Systems Security
• Privacy
• Anonymous Communications
• +8 more

George Danezis is a Professor of Security and Privacy Engineering at University College London (UCL), affiliated with the Information Security Group. He is also a faculty fellow at the Turing Institute and has held part-time roles since 2018 to focus on commercialization. His research spans systems security, privacy, anonymous communications, and blockchain technologies. Danezis co-founded Chainspace (acquired by Facebook in 2019) and Mysten Labs, where he serves as Chief Scientist. He holds a PhD from the University of Cambridge (2004) and has held positions at Microsoft Research, K.U.Leuven, and the University of Cambridge. Education: PhD (Computer Laboratory, University of Cambridge, 2004), B.A. (Hons) in Computer Science (Queens' College, Cambridge, 2000). Research interests include blockchain consensus, decentralized systems, privacy-preserving technologies, and machine learning applications in security. He has advised numerous doctoral students and led projects funded by EU Horizon 2020, EPSRC, and industry partnerships. His work emphasizes practical solutions for privacy, such as Loopix (anonymity system), Narwhal/Tusk (blockchain consensus), and Coconut (privacy credentials). Danezis has received awards for best papers (PET 2002/2018), is a Fellow of the British Computing Society, and advises organizations like Privacy International and DeepMind. Publications focus on blockchain, anonymity, and privacy, with over 100 peer-reviewed papers. Grants include leadership in projects like DECODE (EU), PANORAMIX, and Glass Houses. Teaching includes courses on computer security and privacy technologies at UCL.

Martin MüllerView profile

Professor

• Artificial Intelligence
• Game Theory
• Monte Carlo Tree Search
• +7 more

Martin Müller is a Professor in the Department of Computing Science at the University of Alberta, where he conducts research in artificial intelligence, game theory, and heuristic search. He holds the Canada CIFAR AI Chair at Amii and is an Amii Fellow, underscoring his leadership in AI. His research group focuses on Monte Carlo tree search, reinforcement learning, combinatorial game theory, and automated planning, with applications in games such as Go, Hex, and NoGo. His research interests span Monte Carlo and exact methods in game-tree search , exploration in heuristic search and machine learning , and algorithms in combinatorial game theory . He has developed open-source software like MCGS (Minimax-based Combinatorial Game Solver) and contributes to game-playing systems such as Fuego for Go. His work bridges theoretical foundations with practical implementations in AI-driven game solvers. Recent publications show a strong trend in reinforcement learning , particularly in deep Q-learning, policy gradient methods, and anomaly detection in deep RL. His team also explores combinatorial game solving , sparse reward environments , and imperfect information games . The research integrates machine learning with classical AI techniques, emphasizing empirical validation and algorithmic innovation. Canada CIFAR AI Chair Amii Fellow Best student paper award at IEEE Conference on Games 2024 Best paper award at IEEE COG 2021 Outstanding paper award at AAAI-18 Faculty of Science Dissertation Award (2016) Dissertation Award from the Canadian Artificial Intelligence Association (2013) Müller has supervised numerous PhD and MSc students, including Hongming Zhang, Henry Du, and Timo Bertram, many of whose theses focus on game AI, reinforcement learning, and combinatorial optimization. He is funded by NSERC, Mitacs, and Compute Canada. His group collaborates on projects involving neural networks for game playing, SAT solving, and planning algorithms. He is currently on sabbatical but remains academically active, teaching a graduate course on combinatorial games in 2025 and hosting visiting researchers. His lab is involved in the development of MCGS, a solver for sum games, and contributes to open-source AI software. The team publishes regularly in top venues such as NeurIPS, ICML, AAAI, and IEEE Transactions on Games. Future work includes advancing combinatorial game solvers, improving deep RL robustness, and exploring generalization in game representations.

Stefan MarrView profile

Researcher

• Concurrent Programming
• Language Implementation
• Virtual Machines
• +6 more

Stefan Marr is a faculty member at the University of Kent, United Kingdom, focusing on Concurrent Programming , Language Implementation , and Virtual Machines . His research spans projects like optimizing interpreters, improving concurrency models, and enhancing profiling tools for dynamic languages. Projects : Royal Society Industry Fellowship (FastStart), EPSRC-funded CaMELot, Oracle Labs-funded Automatic Superinstructions. Collaborations : With students and researchers across institutions, including Shopify, Vrije Universiteit Brussel, and Johannes Kepler University Linz. His recent work emphasizes profiling reliability for Java, interpreter performance , and tooling for complex concurrent systems . Projects like SOM (Simple Object Machine) and its variants (SOM++, TruffleSOM, PySOM) highlight his commitment to language implementation research and education. Scientific Awards include fellowships and grants from the Royal Society, EPSRC, and Oracle Labs. His contributions to conferences as program committee member , steering committee , and workshop organizer further underscore his academic leadership.

• Analysis and transformation of programs
• Software Security
• Parallel and distributed computing technologies

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

Xuehai QianView profile

Professor

• Computer Architecture
• Computer Systems
• Hardware Security
• +3 more

Xuehai Qian is a Tenured Full Professor in the Department of Computer Science at Tsinghua University since July 2024. Prior to this, he served as an Associate Professor at Purdue University (2022-2024), Assistant Professor at the University of Southern California (2015-2022), and Postdoctoral Researcher at the University of California Berkeley (2013-2015). Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, USA (2013) ME in Computer Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, China (2007) BE in Computer Science and Technology, Beihang University, China (2004) His research focuses on parallel computer architecture , hardware/software co-designed domain-specific architectures for graph analytics and machine learning , hardware security , and quantum computer architecture . He has pioneered scalable cache coherence protocols for atomic block execution, hardware sequential consistency violation detection, and distributed frameworks for graph processing leveraging emerging memory technologies. Xuehai Qian’s publications span computer architecture , graph analytics , machine learning systems , and quantum computing , with a strong emphasis on distributed systems , accelerators , and memory optimization . His work includes novel architectures for graph processing, decentralized training protocols, and ReRAM-based accelerators for deep learning. NSF CAREER Award (2018) ACSIC (American Chinese Scholar In Computing) Rising Star Award (2019) IEEE Senior Member (2019) Hall of Fame inductions: ASPLOS (2018), HPCA (2019), ISCA (2021), MICRO (2021) W.J. Poppelbaum Memorial Award (2013) He has advised students who have received Microsoft Research Lovelace Fellowships , Ph.D. Fellowships , and Facebook Fellowships . His research has been supported by grants such as the NSF SPX project on FPGA-based machine learning platforms and smaller NSF grants. Notably, he has served as an Associate Editor for Science China (Information Sciences) since 2023 and as a Guest Editor for IEEE Transactions on Parallel and Distributed Systems (2019).

Wen-Ben JoneView profile

Associate Professor

• VLSI system design
• low-power VLSI systems
• many-core micro-processor design
• +3 more

Wen-Ben Jone is an Associate Professor at the University of Cincinnati 's Department of Electrical Engineering & Computing Systems. He previously held positions as Assistant/Associate Professor at New Mexico Institute of Mining and Technology and Visiting Associate/Full Professor at National Chung-Cheng University, Taiwan. His research focuses on VLSI system design, low-power circuits, and fault-tolerant testing methodologies. He has advised over 70 graduate students and authored/co-authored numerous papers in top-tier journals and conferences. Education : PhD: Case Western Reserve University (Computer Engineering, 1987) MS: National Chao-Tung University (Computer Engineering, 1981) BS: National Chao-Tung University (Computer Science, 1979) Research Interests : Reliable VLSI design and testing Low-power and fault-tolerant circuits Many-core processor architectures Parallel computing and debugging tools Awards : 2003 IEEE Donald G. Fink Prize Paper Award 2008 Best Paper Award (International Symposium on Low-Power Electronics) 2012 Best Paper Award (VLSI Design, Automation & Test) Grants : $390k NSF Grant (CCF-0541103) for cache optimization techniques His work emphasizes practical solutions in VLSI testing and reliability, with a focus on low-power strategies and resilient system design.

Nima HonarmandView profile

Assistant Professor

• Computer Architecture
• Parallel Computing
• Operating Systems
• +3 more

Nima Honarmand is an Assistant Professor in the Department of Computer Science at Stony Brook University, where he co-directs the Computer Architecture Stony Brook (COMPAS) Lab . His research focuses on computer system design , particularly parallel computer architecture and operating systems . Education : Ph.D. in Computer Science from University of Illinois at Urbana-Champaign under Josep Torrellas. His work addresses challenges in deterministic replay of parallel programs to simplify debugging on multi-processor systems. Current research explores memory fencing, consistency models, and architectural extensions for reproducibility. Recent publications span conferences like ASPLOS, ISCA, PACT, and POPL, with emphasis on parallelism constraints , memory hierarchy optimization , and fault-tolerant systems . Awards include Best Paper at PACT 2011 and Best Paper Candidate at VTS 2007 . Teaching : Courses include Computer Architecture (CSE 502) and Operating Systems (CSE 306/CSE 506). Email : nhonarmand@cs.stonybrook.edu

Qian LiView profile

Researcher

• Database Systems
• Operating Systems
• Distributed Systems
• +3 more

Qian Li is a researcher working at the intersection of database systems and operating systems, with primary affiliation at DBOS Inc. and academic connections to Stanford University's School of Engineering, Department of Computer Science, and Peking University in Beijing, China. The research focuses on developing the Database Operating System (DBOS) concept, which reimagines operating systems with database technology at their core. Research interests center on database systems, operating systems integration, transaction processing, and serverless computing. The work explores how database principles like ACID transactions can improve system reliability, debugging, and application development, particularly in cloud environments. Key projects include DBOS, Epoxy for cross-data store transactions, and Apiary for transactional serverless computing. The publication record shows a strong trend toward integrating database transaction semantics with modern computing paradigms, particularly serverless architectures. Recent work demonstrates how transactional guarantees can simplify application development, improve debugging, and enable new approaches to cloud-native application design. The research bridges theoretical database concepts with practical systems implementation. As a core contributor to the DBOS project, Qian Li has collaborated extensively with leading researchers including Michael Stonebraker, Matei Zaharia, Christos Kozyrakis, and Peter Kraft. The work has been published consistently in top-tier venues including VLDB, USENIX ATC, and CIDR, reflecting significant impact in the systems research community.

• High-Performance Computing
• Parallel Computing
• Data Compression
• +4 more

Kento Sato is a researcher specializing in High-Performance Computing (HPC), with a focus on checkpointing systems, data compression, and parallel computing optimization. His work addresses challenges in fault tolerance, algorithmic efficiency, and resource management in large-scale computing environments. Collaborating with institutions like the Joint-Laboratory of Extreme Scale Computing, he explores trade-offs between compression efficiency and hardware costs, as well as automatic variable identification for checkpointing. His contributions span theoretical advancements and practical implementations, with notable publications in venues such as SC, IPDPS, and the International Journal of High Performance Computing Applications. Key Research Themes: Checkpointing protocols, lossy compression for scientific data, HPC workflow optimization. Long-term Collaboration: Regular co-authorship with experts like Satoshi Matsuoka and Martin Schulz. Publications consistently highlight innovations in fault tolerance mechanisms, adaptive hardware design, and scalable algorithms for machine learning and distributed systems.

Arunava NahaView profile

Assistant Professor

• Control Systems
• Cyber-Physical Systems Security
• Reinforcement Learning
• +6 more

Arunava Naha is an Assistant Professor in the Department of Electrical Engineering at Linköping University, Sweden, affiliated with the Information Coding (ICG) research group. His work bridges control theory, cybersecurity, and machine learning, focusing on secure and reliable operation of networked and cyber-physical systems. His research interests include: Optimal and risk-constrained control under uncertainty Reinforcement learning for control systems Detection of deception and replay attacks in cyber-physical systems Physical watermarking for active intrusion detection Sequential change detection and statistical monitoring The recent publications show a strong trend in applying machine learning and stochastic control techniques to enhance the security and resilience of networked control systems. His work often involves probabilistic constraints, model-free methods, and quickest detection frameworks, contributing to both theoretical advances and practical solutions in critical infrastructure protection. Scientific awards: No awards mentioned in the provided text. Advising and grants: No information available on students, advising, or funded grants. Labs, teams, and research groups: Arunava Naha is part of the Information Coding (ICG) group within the Department of Electrical Engineering at Linköping University, which conducts research in communication, signal processing, and control systems with applications in secure and reliable information transmission and system operation.

Dongyoon LeeView profile

Associate Professor

• Computer Systems
• Software Reliability
• Software Security
• +9 more

Dongyoon Lee is an Associate Professor in the Department of Computer Science at Stony Brook University. His research focuses on building reliable, secure, and efficient software systems, spanning compiler design, operating systems, security, and hardware architecture. He holds a Ph.D. (2013) from the University of Michigan, Ann Arbor, and has held positions at Virginia Tech (2014-2019) and internships at Microsoft Research, NEC, and IBM. Education: Ph.D. in Computer Science & Engineering, University of Michigan, Ann Arbor (2013) M.S. in Computer Science & Engineering, University of Michigan, Ann Arbor (2009) B.S. in Electrical and Computer Engineering, Seoul National University (2004) Research Interests: Lee's work addresses challenges in software reliability (e.g., concurrency bugs, transient faults), security (e.g., memory safety, kernel permissions), and runtime systems (e.g., stream processing, distributed storage). He leads the COSY Lab (Compilers, Operating Systems, and Security), emphasizing cross-stack solutions. Recent Article Trends: Recent publications focus on homomorphic encryption compilers (e.g., DaCapo , HECATE ), energy-efficient systems ( Write-Light Cache ), and security tools like DevFuzz for device driver testing. Themes include optimizing performance-security trade-offs and addressing vulnerabilities in edge computing and embedded systems. Awards: Distinguished Paper Awards (ESEC/FSE 2018, ASE 2019), ICTAS Junior Faculty Award (2017), Google Research Award (2015), and ProQuest Distinguished Dissertation Award (2013). Advising & Grants: Supervises students in Ph.D., MS, and undergraduate programs. Secured grants including NSF SaTC funding for homomorphic encryption compilers and projects with the South Korean Agency for Defense Development (ADD). Leads research on ARM TrustZone security and energy harvesting systems. Labs/Teams: COSY Lab (Compilers, Operating Systems, and Security) at Stony Brook, collaborating on cross-disciplinary projects with industry and government partners.

Amittai AviramView profile

Associate Professor

• Parallel Computing
• Deterministic Systems
• Operating Systems
• +4 more

Amittai Aviram is an Associate Professor of the Practice in the Department of Computer Science at Boston College's Morrissey College of Arts and Sciences. He holds dual PhDs in Computer Science (Yale University) and English (Yale University), with research spanning parallel computing, deterministic systems, compiler design, and literary theory. His research integrates: Operating system support for deterministic parallelism Cloud computing security and timing channels Economic simulations of democratically managed enterprises Formal approaches to lyric poetry and literary theory His publications demonstrate interdisciplinary expertise, with recent computer science work focusing on parallel programming models (OpenMP), cloud security, and deterministic systems, alongside literary scholarship on poetry, modernism, and dialogism. He maintains educational resources including implementations of B+ trees and Huffman coding algorithms.

• Computer Architecture
• Programming Education
• Hardware Security
• +3 more

Andrew Hilton is a Professor in the Electrical and Computer Engineering Department at Duke University's Pratt School of Engineering. His primary academic role focuses on teaching computer engineering courses specializing in programming, software engineering, architecture, and system software. His research spans multiple areas of computer architecture with particular emphasis on security, performance optimization, and energy efficiency. Hilton has developed innovative approaches in core micro-architecture, architectural support for security, simulation methodologies, and micro-architectural applications for emerging technologies. His work on programming education has led to the development of the "Seven Steps" methodology for translating problems to code, which forms the foundation of his educational materials. Hilton's recent publications demonstrate consistent contributions to the field, with research trends showing increasing focus on hardware security mechanisms alongside traditional architecture optimization. His 2018 paper "MAPS: Understanding Metadata Access Patterns in Secure Memory" received the Best Paper award at ISPASS 2018, highlighting his significant contributions to secure memory systems. Best paper award at ISPASS 2018 for 'MAPS: Understanding Metadata Access Patterns in Secure Memory' Hilton actively mentors students through Duke's academic programs and has developed extensive educational materials including the "All of Programming" textbook and multiple Coursera specializations. His teaching philosophy emphasizes mastery learning and flipped classroom approaches, particularly evident in ECE 551 where students must demonstrate proficiency before advancing. He maintains an active research laboratory focused on computer architecture innovation and collaborates with students on cutting-edge research in processor design and security.

• Computer Architecture
• Cybersecurity
• Energy Efficiency
• +2 more

Andrew Douglas Hilton is a Teaching Professor in the Department of Electrical and Computer Engineering at Duke University , where he also serves as the Director of Innovation in Computing Education . He focuses on teaching professional-level programming, software engineering, and architecture courses to graduate and advanced undergraduate students, with a particular emphasis on preparing them for software engineering careers. Education: Ph.D. in Computer Science from the University of Pennsylvania (2010) Hilton’s research interests center on computer architecture , particularly architectural support for security and energy-efficient performance . His recent publications explore themes like secure memory, thermal management, and speculative execution in processor design. He has co-authored a widely used course textbook, All of Programming , and developed two Coursera specializations in Java and C. His teaching spans courses such as ECE 651 (Software Engineering) and ECE 553 (Compiler Construction), with a focus on design principles, testing, and teamwork. Scientific Awards: Klein Family Distinguished Teaching Award (2015) Hilton collaborates with faculty at Duke (Genevieve Lipp, Ben Lee, Daniel Sorin) and institutions such as UT Austin and IBM Research. His former students, Tamara Lehman and Ziqiang Huang, hold academic and research positions at the University of Colorado Boulder and University of Waterloo, respectively.

Ashvin GoelView profile

Professor

• Systems Software
• Cloud Computing
• Storage Systems
• +5 more

Ashvin Goel is a Professor in the Department of Electrical and Computer Engineering and Department of Computer Science at the University of Toronto , where he leads research at the intersection of Operating Systems , Reliability Engineering , and Computer Security . His work focuses on ensuring software systems can withstand bugs and vulnerabilities, with publications in top venues like SOSP , OSDI , and FAST . He received his PhD in Computer Science and Engineering from Oregon Graduate Institute in 2003, with prior degrees from UCLA (MS) and IIT Kanpur (BS). Current research projects include runtime verification systems like Recon and intrusion recovery frameworks such as Taser , often in collaboration with Professor Angela Demke Brown. His team explores kernel instrumentation, file system consistency, and security recovery methods. NSERC Discovery Accelerator Award 2012 FAST Best Paper Award 2012 Google Faculty Research Award 2011 Netapp Faculty Award 2008 Ontario Early Researcher Award Professor Goel's recent publications address deterministic concurrency control, distributed graph mining, and storage system reliability. He teaches graduate courses in Dependable Software Systems and Distributed Systems , with prior course development in operating systems security and time-sensitive applications.