Find Academic Supervisors

Mark SantolucitoView profile

Assistant Professor

• Program Synthesis
• Computer Music
• Live Coding
• +5 more

Mark Santolucito is an Assistant Professor of Computer Science at Barnard College, Columbia University. He holds a PhD from Yale University, where his work focused on Program Synthesis and Computer Music. His research explores new ways to enable programmers through advanced synthesis techniques, particularly in areas like live coding, infrastructure configuration analysis, and educational tools. Education: PhD in Computer Science, Yale University (201?) Focus: Program Synthesis and Computer Music Research Interests: Program synthesis, formal methods, live coding interfaces, infrastructure as code analysis, and educational outreach in computing. He develops tools to bridge the gap between theoretical computer science and practical applications, with a focus on accessibility and usability. Awards: Fulbright Scholar Fellowship (2024) Grants & Collaborations: Collaboration with FIT on creative computing workshops Development of the functional programming card game (cardComposer) Contributions to the Yale Open Music Initiative Labs/Teams: Leads the Barnard Computer Science Research Lab, focusing on synthesis techniques and educational technology. Active in the SEConfig workshop and infrastructure analysis projects.

Joseph EremondiView profile

Assistant Professor

• Dependent Types
• Programming Languages
• Formal Verification
• +2 more

Joseph Eremondi is an Assistant Professor in the Department of Computer Science at the University of Regina, specializing in programming language theory and design. His research develops tools to enhance usability of dependently typed programming languages, which enable mathematical specification and verification of code behavior. Current projects include gradual dependent types, semantics for pattern matching, termination proof techniques, and compiler error diagnosis. Eremondi's publications advance formal foundations for programming language design while addressing practical usability concerns. Recent work establishes theoretical foundations for gradual dependent typing and develops ordinal notations for termination verification. He teaches courses in programming language concepts and formal verification, including courses on Agda-based program verification.

Shih-Hsi LiuView profile

Professor

• Software Engineering
• Meta-heuristics
• Evolutionary Algorithms
• +5 more

Shih-Hsi (Alex) Liu is a Professor in the Department of Computer Science at Fresno State. He holds a Ph.D. from the University of Alabama at Birmingham (2007), an M.S. from the University of Houston (2002), and a B.S. from National Chiao-Tung University, Taiwan (2000). His research focuses on software engineering, meta-heuristics, evolutionary algorithms, and service-oriented architectures. Dr. Liu leads the Cloud Agility Lab and has published over 30 articles with 3,000+ citations. He serves on the editorial board of Applied Soft Computing (impact factor 7.2) and has mentored over 30 student projects. His work explores algorithmic optimization, QoS-driven systems, and domain-specific languages implementation through service-oriented technologies. Education: Ph.D., Computer Science, University of Alabama at Birmingham, 2007 M.S., Computer Science, University of Houston, 2002 B.S., Computer Science, National Chiao-Tung University, 2000 Research emphasizes balancing exploration/exploitation in evolutionary algorithms, improving compiler generation for DSLs, and addressing challenges in swarm intelligence. Recent work critiques algorithm stopping criteria and proposes memory-assisted optimization techniques. His articles address topics like MIoT applications, artificial bee colony parameter tuning, and QoS-aware service composition. Grant and advising activities remain centralized through student project supervision, with no specific grants mentioned in the text. The Cloud Agility Lab focuses on advancing cloud computing and software agility in distributed systems.

Bruce LesterView profile

Professor

• Parallel Computing
• Programming Languages
• Multi-Core Processors
• +3 more

Dr. Bruce Lester is a Professor of Computer Science at Maharishi University of Management (MUM), where he founded the Computer Science Department and served as its Chair for eight years. He holds PhD, MS, and BS degrees from the Massachusetts Institute of Technology (MIT). His research focuses on Parallel Computing and Programming Languages for Multi-Core Processors, with a strong emphasis on compiler optimization and concurrency control. Education: Bachelor of Science, Massachusetts Institute of Technology Master of Science, Massachusetts Institute of Technology Doctor of Philosophy (PhD), Massachusetts Institute of Technology Research Interests: Dr. Lester’s work spans Parallel Computing, Programming Languages, and Multi-Core Processor Optimization. He has developed techniques for lock-free parallel data structures, operator fusion in data-parallel libraries, and compile-time detection of control flow errors in parallel programs. His contributions to the field include foundational research on concurrency debugging and the design of educational tools like Multi-Pascal for teaching parallel programming. Publications Trends: His publications emphasize practical applications of parallel computing, including high-performance algorithms, compiler techniques, and concurrency error detection. Recent work focuses on lock-free systems and data-parallel library optimizations. Awards & Honors: Best Paper Award at the 2011 International Conference of Parallel and Distributed Computing (World Congress on Engineering) Advising & Grants: No formal advisee names are listed in the provided data. His professional experience includes 13 years of teaching and six years as a Senior Software Engineer at Primus Telecommunications, where he developed client/server systems and internet platforms. Labs & Teams: While specific lab affiliations are not detailed, his role as founder of MUM’s Computer Science Department suggests leadership in departmental research initiatives.

• High-performance computing
• Decimal arithmetic
• Parallel programming
• +4 more

Alvaro Vazquez Alvarez is an Assistant Professor at the Higher Technical School of Engineering, University of Santiago de Compostela. He holds a PhD in Computer Engineering (2009) from the same institution, focusing on High-performance decimal floating point units under the supervision of Dr. Elisardo Antelo Suárez. His research interests span high-performance computing, decimal arithmetic hardware design, parallel programming models, and LiDAR data processing. His work emphasizes FPGA implementation of arithmetic units, numerical algorithms optimization, and compiler/runtime systems for parallel environments. He leads the CograDe Research Group (Computer Graphics and Data Engineering), exploring advanced topics in parallel computing and data engineering applications. Key contributions include universal MPI binding frameworks for new languages and efficient LiDAR point cloud processing algorithms. Notable technical expertise includes: digit-by-digit algorithms, redundant number systems, CORDIC-based computations, and multi-operand decimal arithmetic implementations. His publications bridge theoretical numerical methods with practical hardware/software co-design solutions. Current research focuses on extending parallel programming interfaces, improving decimal arithmetic precision in modern architectures, and applying advanced geometric processing techniques to 3D data challenges.

Ross PatersonView profile

Lecturer

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

Dr. Ross Paterson is a Lecturer at City St George's, University of London, where he has been employed since 1998. He is a member of the Research Centre for Machine Learning and specializes in programming languages and functional programming. His research interests focus on functional programming techniques, embedded domain-specific languages, program transformations, and persistent data structures. His work bridges theoretical computer science with practical applications in programming language design and implementation. Dr. Paterson's publication record spans over three decades, with significant contributions to functional programming, type theory, and data structures. His most influential work includes the development of arrows as a general interface to computation, applicative functors, and finger trees as a general-purpose data structure. His research shows consistent focus on theoretical foundations with practical implementations in functional programming languages. Throughout his career, Dr. Paterson has maintained strong academic connections, having previously worked at the University of North London (1996-1998), Imperial College London (1990-1995), and the University of Queensland (1988-1989).

Oscar PastorView profile

Professor

• Conceptual modeling
• Model-driven engineering
• Requirements engineering
• +5 more

Full Professor and Director of the Valencian Research Institute of Artificial Intelligence (VRAIN) and the Research Center on Software Production Methods (PROS) at Polytechnic University of Valencia. Holds leadership positions including Director of Internationalization and Transference at VRAIN since 2022, Director of PROS since 2008, and former Director of the Department of Informatics Systems and Computation (2001-2002). PhD in 1992 after research at HP Labs, Bristol. Research spans conceptual modeling, model-driven engineering, and bioinformatics applications. Created the OASIS specification language and OO-METHOD production framework. Led development of IntegraNova, an MDA-based Conceptual Model Compiler commercialized through CARE Technologies (founded 1996). Current work focuses on Conceptual Modeling-based interpretation of Human Genome data. Recent publications demonstrate strong interdisciplinary convergence between software engineering and genomics, with significant output in model-driven development validation, ontology-based modeling, and genomic data management systems. Key themes include empirical validation of modeling techniques, precision medicine infrastructure, and evolutionary algorithms for requirement traceability. International Peter Chen Award on Conceptual Modeling (2016) ER Fellow Award (2010) Supervised 33 PhD and 51 Master's theses. Secured extensive funding including 7 international, 8 national, and 5 regional competitive projects plus 10 technology transfer projects. Edited 33 conference proceedings and organized 12 international conferences. Serves on steering committees for ER, CAiSE, ESEM, and other major conferences. Leads the PROS Research Center and multidisciplinary teams bridging information systems and bioinformatics. Current projects develop tools for genomic data interpretation using conceptual modeling frameworks, with applications in precision medicine and life engineering.

Hu ZhenjiangView profile

Professor

• Bidirectional Transformation
• Functional Programming
• Software Engineering
• +4 more

Zhenjiang Hu is a Chair Professor at Peking University, China, and previously held professorships at the National Institute of Informatics, University of Tokyo, and SOKENDAI. He specializes in bidirectional transformation, functional programming, and software engineering. His research focuses on foundational theories and applications in programming languages, including parallelization and formal methods. Education: BSc, Shanghai Jiao Tong University (1988) MSc, Shanghai Jiao Tong University (1991) PhD, University of Tokyo (1996) Research Interests: Development of bidirectional languages and frameworks Optimization of functional programs Automated parallelization techniques Formal verification of transformations Awards: Yangtze River Scholar (2015) ACM Distinguished Scientist (2016) Basic Research Achievement Award (2015) Multiple Best Paper Awards including Takahashi Awards (1997, 2008) Grants & Leadership: PI of 14 national grants totaling over 250 million Yen Founder and Chair of NII Shonan Meetings (2010-2018) Leadership roles in ICFP, MODELS, APLAS, and other top conferences Labs/Teams: Active in the NII Shonan Meetings, fostering collaborative research in informatics and software engineering.

• Programming Languages
• Program Verification
• Software Security
• +5 more

Gilles Barthe is a scientific director at the Max Planck Institute for Security and Privacy in Bochum, Germany, and a part-time research professor at the IMDEA Software Institute in Madrid, Spain. His research focuses on programming languages, program verification, cryptography, privacy, and mathematical logic, with an emphasis on applying relational verification to cryptographic systems. He leads the Foundations of Security and Privacy Group, developing techniques to ensure cryptographic software is secure against timing and side-channel attacks, and verifies implementations of post-quantum algorithms like Kyber. Barthe has pioneered tools such as EasyCrypt for formal proofs, and contributed to standards like AWS Key Management Service verification. His work bridges theory (e.g., quantum verification) and practice (e.g., compiler optimization for constant-time code). Education: Ph.D. in 1993 from University of Manchester, followed by roles at INRIA, IMDEA, and others. Research Interests: Secure compilation, cryptographic protocol verification, differential privacy, and quantum programming semantics. Recent articles explore secure compilation against Spectre variants, quantum relational logics, and formal verification of lattice-based cryptography. He has advised over 20 PhD/Master’s students, many contributing to cryptographic verification frameworks. Barthe’s teams collaborate on high-assurance implementations, masking techniques, and mitigating modern microarchitecture threats. His lab’s work includes PanCast for epidemic risk mitigation and certified cryptographic libraries.

Isaac SheffView profile

Research Fellow

• Distributed Systems
• Consensus Protocols
• Heterogeneous Trust
• +2 more

Isaac Sheff is a Senior Research Scientist at Heliax and former Postdoctoral Researcher at the Max Planck Institute for Software Systems. His research focuses on distributed systems, consensus protocols, and formal verification, with applications to blockchain technology. He leads development of Typhon, a next-generation heterogeneous consensus protocol enabling fast finality and multi-chain atomic transactions. His work combines theoretical foundations with practical implementations in Haskell and Coq. Publications demonstrate his contributions to program logics (Iris, Melocoton), consensus algorithms (Heterogeneous Paxos), and distributed data structures (Charlotte). His research consistently bridges formal methods, distributed systems, and security. He has collaborated on projects including ProLoc and CoVault that develop privacy-preserving location proofs and secure analytics platforms using distributed systems principles.

Santosh NagarakatteView profile

Professor

• Compilers
• Formal Verification
• Computer Architecture
• +4 more

Santosh Nagarakatte is a Professor and Undergraduate Program Director in the Department of Computer Science at Rutgers University. His research focuses on hardware-software interfaces, compilers, formal verification, and numerical methods. He has contributed to projects like the RLIBM math library and verified eBPF ecosystems, emphasizing robustness and security in software systems. Education: PhD in Computer Science from the University of Pennsylvania. His work has been recognized with awards including the ACM Distinguished Member (2023), NSF CAREER Award (2015), and multiple distinguished paper awards at top conferences like PLDI and POPL. Research interests include compiler optimizations, verified compilers, memory safety, and high-performance computing. He has advised numerous PhD students and leads projects funded by Intel, NSF, and the eBPF Foundation. His lab focuses on practical formal methods and math library correctness.

Monica S. LamView profile

Professor

• Virtual Assistants
• Natural Language Processing
• Machine Learning
• +6 more

Monica S. Lam is the Kleiner Perkins, Mayfield, Sequoia Capital Professor in the Computer Science Department at Stanford University's School of Engineering, where she has been a faculty member since 1988. She serves as Faculty Director of the Open Virtual Assistant Lab (OVAL) and holds a courtesy appointment in the Electrical Engineering Department. Lam received her B.Sc. from the University of British Columbia in 1980 and her Ph.D. in Computer Science from Carnegie Mellon University in 1987. Her research spans multiple domains with a focus on creating trustworthy virtual assistants based on Large Language Models. She is particularly renowned for her work on the Almond virtual assistant, which emphasizes privacy preservation and open-source development. Her research interests include virtual assistants, natural language programming, machine learning, distributed mobile computing, and compiler technologies. Lam's recent publications reveal a strong focus on addressing key challenges in virtual assistant technology, particularly around hallucination reduction in LLMs, multilingual dialogue systems, semantic parsing, and multimodal interactions. Her work consistently emphasizes privacy preservation, open-source development, and user control over data. Member of the National Academy of Engineering ACM Fellow NSF Young Investigator Award (1992) ACM Most Influential Programming Language Design and Implementation Paper Award (2001) Wikimedia Foundation's Research of the Year Award (2024) for eliminating LLM hallucinations Popular Science's Best of What's New Award in Security (2019) for Almond virtual assistant Lam has advised numerous PhD students who have gone on to prominent positions at institutions like MIT, Harvard, Google, and Amazon. Her research has been supported by significant funding including NSF grants and industry partnerships. She leads the Open Virtual Assistant Lab (OVAL), which focuses on developing open, privacy-preserving virtual assistant technologies that give users control over their data while maintaining functionality.

Juan Carlos Preciado RodríguezView profile

Associate Professor

• Web Engineering
• Data Intensive Systems
• Big Data
• +4 more

Juan Carlos Preciado Rodríguez is an Associate Professor of Computer Languages and Systems at the University of Extremadura (Spain), affiliated with the Quercus Software Engineering Group. He has held significant academic roles, including Deputy Rector for over 8 years. His research focuses on Web Engineering, Big Data, Machine Learning, and Smart Cities, with over 60 scientific publications. He founded Homeria Open Solutions SL and MetrikaMedia SL, two spin-offs from UEx. He has led multiple R&D projects, including 1 European, 1 national, and 1 regional initiative, and participated in 18 R&D contracts as Principal Investigator in 5 cases. He holds 2 national patents and actively contributes to academic and entrepreneurial ventures. His educational background includes a PhD, though specific details are not provided. Research interests span Model-Driven Engineering (MDE), Business Intelligence, and Data Visualization. Recent work includes applications in demand forecasting, smart cities, and educational data analysis. Notable projects involve leveraging data-driven approaches for university dropout prediction and optimizing vocational training programs using TOPSIS methodology. He has engaged in collaborative ventures such as SCPL (Social Cooperative Programming Language) and AutoCRUD for workflow automation. His work bridges software engineering with societal challenges, including unmanned aerial systems for smart city services and advanced visualization tools like LiveSankey. His contributions span both technical innovation and archaeological studies, reflecting interdisciplinary engagement.

• Parallel and Distributed Programming
• Functional Programming
• High-Level Programming Models
• +3 more

Professor Phil Trinder is a Professor of Computing Science at the University of Glasgow's School of Computing Science. He leads the Glasgow Parallelism Group (GPG) and is a member of the Glasgow Systems Section (GLASS). His research focuses on parallel and distributed programming models, functional programming, and scalable systems. Education: DPhil (Doctor of Philosophy) from the University of Oxford. Research Interests: Design and implementation of high-level distributed/parallel programming models, computational algebra applications, and collaboration with industry (Ericsson, Microsoft, etc.). Publications span over 78 works, emphasizing parallel algorithms, distributed systems, and functional programming frameworks like Erlang. Recent work explores tierless IoT architectures and reliability in distributed platforms. Grants/Projects: Principal Investigator on 12 major projects, including EU funding and EPSRC grants. Notable contributions to SD Erlang and SymGrid-Par frameworks. Labs/Teams: Glasgow Parallelism Group (GPG), GLASS section, and involvement in the Scottish Programming Languages Seminar (SPLS).

Yiren ZhaoView profile

Assistant Professor

• Large-scale GenAI Systems
• Hardware-Algorithm Co-design
• AI Security
• +4 more

Dr. Yiren Zhao is an Assistant Professor (Lecturer) in Computer Engineering at Imperial College London, part of the Faculty of Engineering. He leads the DeepWok Research Lab and holds affiliations with the UKRI Artificial Intelligence for Engineering Biology Consortium and the University of Cambridge as a Visiting Researcher. His work focuses on Large-scale GenAI Systems, emphasizing hardware-algorithm co-design, efficiency, and security. He has secured over £5M in funding since 2022 and reviews for top conferences like ICLR, ICML, and NeurIPS. Dr. Zhao earned a BEng in Electrical and Electronic Engineering from Imperial College London (2016), followed by an MPhil and PhD in Computer Science from the University of Cambridge (2017–2022). His research spans GenAI acceleration, unstructured data processing (e.g., graphs), and system-level AI safety. Recent projects include MASE (unified ML system exploration) and ImpNet (imperceptible backdoor attacks). Awards: Apple Scholar in AI/ML (2020), Microsoft Research Award (2023), and Junior Research Fellowship at St John’s College (2021). Labs/Teams: DeepWok Lab (20+ members), involved in Imperial-X and AI-4-EB initiatives. Grants: Industry/government-funded projects totaling over £5M since 2022. His work bridges computer systems and AI, with notable contributions to quantization, adversarial attacks, and hardware-aware optimization. Collaborations include the Center for Spatial Computational Learning and CaRAML group.