Supervisors

Browse the supervisors related to our CDT in Machine Learning Systems here. Click their names to navigate to their personal websites.

The supervisors are grouped into six research areas:

The below list is not exhaustive. Supervisors can also be nominated in other University of Edinburgh schools such as Engineering and Mathematics as long as the research topic fits within the CDT remit. In that case, a co-supervisor in Informatics will need identified at offer stage.

Computer Systems and Hardware for ML

Name	Title	Research
Ajitha Rajan	Professor and Personal Chair of Software Testing and Verification	automated software testing techniques, biomedical artificial intelligence
Amir Shaikhha	Reader (Associate Professor)	design and implementation of data-analytics systems
Antonio Barbalace	Senior Lecturer (Associate Professor) in Operating Systems	system software, specifically, operating systems, virtualisation environments, run-times/compilers/linkers for parallel, heterogeneous and distributed computer architectures from embedded to data-center scale
Bjoern Franke	Professor and Personal Chair of Software Transformation	software transformation, dynamic program analysis and transformation, just-in-Time Compilation, code generation and optimisation, instruction set simulation, hardware/software design space exploration
Boris Grot	Professor and Personal Chair of Computer Systems and Architecture	Cross-stack innovation for tomorrow’s datacenters: from microarchitecture to software/hardware co-design to massively parallel cloud-based services
Jackson Woodruff	Lecturer (Assistant Professor) in Compiling Techniques	compilers for hardware accelerators
Jianyi Cheng	Lecturer (Assistant Professor) in Computer Architecture	high-level synthesis, formal methods, deep learning systems, hardware security
Luo Mai	Lecturer (Assistant Professor) in Data Centric Systems	intersection of computer systems, machine learning, and data management
Mahesh Marina	Professor and Personal Chair of Networked Systems	networked systems (wireless networks, mobile/edge systems), loud service assurance, edge computing, sustainable computing and networking, machine learning systems and quantum systems
Michael O’Boyle	Professor and Personal Chair in Computer Science	heterogeneous code discovery and Optimisation, neural machine translation and neural synthesis, deep neural network system stack, software defined hardware, auto-parallelising compilers, GPGPU multi-core platforms, machine learning based optimisation, compiler/architecure co-design space exploration, very high level programming languages
Michio Honda	Reader (Associate Professor)	identifying TCP extensibility against middlebox interference and building the first TCP/IP network stack for persistent memory, (currently) network stack designs
Murray Cole	Professor and Personal Chair of Patterned Parallel Computing	parallel programming models, emphasising approaches which exploit skeletons to package and optimize well known patterns of computation and interaction as parallel programming abstractions
Nigel Topham	Professor and Chair of Computer Systems	computer architecture, development of next-generation microarchitectures for high-performance embedded systems, (currently) automated synthesis of processors, interactions between the synthesis of architecture, microarchitecture, and physical design.
Paul Patras	Professor and Personal Chair of Mobile Intelligence	mobile intelligence, network traffic analytics, performance optimisation, security and privacy, explainability, bridging fundamental mathematical models and real-world applications of networked systems

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ML Methods, Architectures and Deployment

Name	title	research
Amir Vaxman	Reader in Graphics, Simulation and Visual Computing	geometry processing, discrete differential geometry, focusing on directional-field design, unconventional meshes, constrained shape spaces, architectural geometry, and medical applications
Amos Storkey	Professor and Personal Chair of Machine Learning & Artificial Intelligence	machine learning methods, generative models and generative AI, machine learning and deep learning methodology, model understanding and efficiency
Antonio Attili	Lecturer in Computational Reactive Flows	Turbulence and combustion, soot formation in flames, aerosols, combustion instabilities, rocket propulsion, numerical methods, and massively parallel computing. Big-data analysis and applying machine learning and generative AI to fluid mechanics
Antonio Vergari	Reader (Associate Professor)	efficient inference with guarantees, complex probabilistic queries, automating probabilistic Machine Learning
Changjian Li	Lecturer (Assistant Professor) in Graphics, Simulation and Visual Computing	3D Shape Creation and Analysis, applications in sketch-based modeling, shape reconstruction and analysis from point clouds, and medical image processing and modeling
Elliot Crowley	Senior Lecturer (Associate Professor) in Electronics and Electrical Engineering	simplifying machine learning, AutoML (neural architecture search), efficient network training, low-resource deep learning, engineering applications of machine learning
Fengxiang He	Lecturer in AI Driven Business Informatics and Financial Com	trustworthy AI, deep learning theory and explainability, theory of decentralised learning, privacy in machine learning, symmetry in machine learning, learning theory in game-theoretical problems, and their applications in economics
Hakan Bilen	Reader (Associate Professor)	computer vision
He Sun	Reader	algorithmic spectral graph theory, unsupervised learning, computational geometry, and randomised algorithms
Henry Gouk	Lecturer (Assistant Professor) in Machine Learning	artificial intelligence engineering
Laura Sevilla	Reader (Associate Professor)	visual world in motion
Michael Gutmann	Senior Lecturer (Associate Professor) in Machine Learning	methods for (Bayesian) inference and design
Nikolay Malkin	Chancellor's Fellow in AI and Data Science	deep-learning-based reasoning (Machine learning for generative models, NLP and reasoning in language, computer vision)
Oisin Mac Aodha	Reader (Associate Professor) in Machine Learning	(currently) computer vision and machine learning, with an specific emphasis on 3D understanding, human-in-the-loop methods, and AI for conservation and biodiversity monitoring
Steven McDonagh	Senior Lecturer in AI and Computer Vision for Health	computer vision, machine learning and medical image analysis. multi-modal, multi-task learning and medical imaging applications
Timothy Hospedales	Professor in Artificial Intelligence	efficient and robust AI, meta-learning, lifelong transfer-learning in both probabilistic and deep learning contexts
Viacheslav Boroditsky	Incoming Lecturer (Tenured Assistant Professor) in Machine Learning	geometric learning, uncertainty quantification, harmonic analysis
Victor Elvira	Professor and Personal Chair in Statistics and Data Science	computational statistics, statistical signal processing, probabilistic machine learning, Monte Carlo methods, importance sampling methodology - including sequential Monte Carlo (particle filtering), Bayesian inference in static and dynamical models, statistical modelling and inference in population ecology, signal processing for biomedical applications and wireless communications, (currently on) forecasting climate tipping points probabilistically
Wenda Li	Lecturer in Hybrid AI	neuro-symbolic reasoning, AI for math, machine learning for theorem proving, mechanised mathematics

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Programming Languages and Database for ML

Name	Title	Research
Elizabeth Polgreen	Lecturer (Assistant Professor) in Programming Languages for Trustworthy Systems	formal program synthesis techniques and the use of synthesis to increase the scalability of verification
Gordon Plotkin	Professor (Laboratory for Foundations of Computer Science)	structural operational semantics (SOS), denotational semantics, theoretical computer science
James Cheney	Professor and Personal Chair of Programming Languages and Systems	databases and data provenance, programming languages and compilers, generic programming, logic and automated theorem proving,compression and information theory,XML and related technologies
Jane Hillston	Professor and Personal Chair in Quantitative Modelling	quantitative modelling, stochastic process algebras
Leonid Libkin	Professor and Chair of Foundations of Data Management	databases, logic in computer science, logic in finite model theory, logic in automata theory
Milos Nikolic	Lecturer in Database Systems	databases, large-scale data management systems, in-database learning, stream processing, incremental computation, query compilation
Ohad Kammar	Royal Society University Senior Research Fellow	applied mathematics, programming language theory, computational effects, domain theory, probabilistic programming, concurrency, access control, staging and metaprogramming, conceptual biology
Rob Van Glabbeek	Royal Society Wolfson Fellow and Personal Chair in Computer Science	comparative concurrency semantics. Mathematical models and formal languages for the representation of distributed systems and the verification of statements about them
Wenfei Fan	Professor and Personal Chair in Web Data Management	database theory and systems
Yang Cao	Lecturer (Assistant Professor) in Database Systems	In-database model explanation, transactional caching, transaction scheduling, graph transactionsquery optimisation under constraints, bounded evaluation, approximate query processing, graph computing frameworks, graph pattern matching,data quality

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Trustworthiness, Ethics, Safety, Security and Privacy

Name	Title	Research
Adriana Sejfia	Lecturer (Assistant Professor) in Software Engineering	software engineering, programme analysis and machine learning for security
Aggelos Kiayias	Professor and Chair in Cyber Security and Privacy	computer security, information security, applied cryptography, foundations of cryptography, blockchain technologies, distributed systems, e-voting, secure multiparty protocols, privacy and identity management
Chris Heunen	Professor and Chair of Quantum Programming	quantum theory, quantum machine learning, quantum programming and semantics
Craig Innes	Chancellor's Fellow	safety, trustworthiness, and risk for cyber-physical systems
Daniel Woods	Lecturer in Cyber Security	cyber security, cyber insurance, digital risk management, cyber risk quantification, incident response, how the legal system impacts cybersecurity, privacy preference signals, 0-Day exploit brokers and prices
David Aspinall	Professor and Personal Chair in Software Safety and Security	software security, user authentication, theorem proving, programming and specification languages
Jacques Fleuriot	Professor and Personal Chair of Artificial Intelligence	AI Modelling, interactive theorem proving, formal verification, process modelling, and AI/machine learning applied to health/care, medicine and other complex domains
Jingjie Li	Lecturer (Assistant Professor) in Systems Security	user-centric security and privacy control, measuring human behavior and digital risks, efficient human-machine interface
Marc Juarez Miro	Lecturer in Cyber Security and Privacy	cyber security and privacy, ML-based traffic analysis, security and privacy of ML, algorithmic bias
Markulf Kohlweiss	Senior Lecturer (Associate Professor) in Security and Privacy	formal verification, foundations of cryptography and applied cryptography, privacy-enhancing protocols, blockchains, crypto-currencies, formal verification of protocol implementations
Michele Ciampi	Chancellor's Fellow	theory of cryptography, zero-Knowledge proofs, multi-party computation protocols and Blockchain
Nadin Kokciyan	Lecturer in Artificial Intelligence	Multiagent Systems, Agreement Technologies (Argumentation and Negotiation), Privacy in Social Software, AI Ethics, Explainable AI, Responsible AI
Ram Ramamoorthy	Professor and Personal Chair of Robot Learning and Autonomy	robotics and machine learning. learning, adaptation and control mechanisms to enable autonomous robots to cope with the uncertain and the unknown, and for them to be effective in human-AI teams
Rik Sarkar	Reader	ML and optimisation algorithms.Privacy, fairness, and Explainability.GenAI and artificial data. topological data analysis, topology in ML, Network Analysis and graph machine learning, AI for Biomedical Engineering (diagnostics, interpretability, molecule design)
Susan Lechelt	Lecturer in Design Informatics	human-computer interaction, interaction design. Themes of data literacy, creativity, playfulness, sustainability, and responsible innovation
Tariq Elahi	Lecturer (Assistant Professor) in Security and the Internet of Things	Privacy Enhancing Technologies (PETs), anonymous communication networks, data-driven privacy systems engineering
Tiejun Ma	Professor and Personal Chair of Financial Computing (Risk Modelling)	financial computing, risk modelling

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Natural Language Processing and Speech Systems

Name	Title	Research
Edoardo M. Ponti	Lecturer (Assistant Professor) in Natural Language Processing	modular deep learning, efficient architectures of language models, computational typology of language
Frank Keller	Professor and Personal Chair in Computational Cognitive Science	NLP and cognitive science. language and vision tasks, such as image description, visual grounding, video summarization, visual story telling, computational narrative
Hao Tang	Lecturer in Speech Technology	speech representations in NLP, data structures that speech systems use to solve tasks,
Ivan Titov	Professor and Personal Chair of Natural Language Processing	natural language understanding (question answering, information extraction, and semantic parsing), improving generalization across tasks and data distributions, interpretability and controllability of deep learning models
Korin Richmond	Reader in Speech Technology	human language and machine learning. articulatory modelling, speech synthesis and recognition, pronunciation modelling, machine learning in tracking shapes in ultrasound videos
Mark Steedman	Professor in Cognitive Science	computational cognitive and social science, natural language and speech processing, Artificial Intelligence
Mirella Lapata	Professor and Personal Chair in Natural Language Processing	probabilistic learning techniques for natural language understanding and generation, extracting semantic information from large volumes of text
Pasquale Minervini	Lecturer in Natural Language Processing	NLP and ML. relational learning and learning from graph-structured data, solving knowledge-intensive tasks, hybrid neuro-symbolic models, compositional generalisation, designing data-efficient and robust deep learning models
Peter Bell	Professor and Personal Chair of Speech Technology	automatic speech recognition and understanding (cross-domain and cross-lingual adaptation, efficient alignment, search and decoding on audio data, training methods for ASR, end-to-end and raw-waveform methods, ASR systems for minority or under-resourced languages, speech representation learning, audio-visual speech recognition and enhancement)
Simon King	Professor and Personal Chair of Speech Processing	basic building blocks of speech: speech recognition (new acoustic models, multilingual systems), speech synthesis (unit selection methods, HMM-based speech synthesis, multilingual systems)

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Autonomous and Multi-Agent ML Systems

Name	Title	Research
Barbara Webb	Professor and Personal Chair in Biorobotics	perceptual systems for the control of behaviour, through building computational and physical (robot) models of the hypothesised mechanisms. insect behaviours.
Kobi Gal	Reader in Artificial Intelligence and Human-Machine Intelligence	Human-in-the-loop Machine Learning, Human-Computer Decision-Making, Artificial Intelligence in Education and in Participatory Democracy, Ethical implications of the Human-in-the-Loop.
Michael Rovatsos	Professor and Personal Chair of Artificial Intelligence	ethical AI: In a multiagent systems context, this mostly means creating mechanisms to elicit users' and stakeholders' views and translate them into concrete constraints and optimisation criteria for algorithms and design principles for algorithms.
Sethu Vijayakumar	Professor and Personal Chair in Robotics	basic research in the fields of robotics, statistical machine learning, motor control, planning and optimization in autonomous systems and computational neuroscience, Valkyrie humanoid robot, science public outreach.

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This article was published on 2024-12-04