Research staff

A list of all the research staff within ANC.


Antreas Antoniou
Antreas Antoniou Antreas' broader research topic is the design and/or learning of learning priors for deep neural networks, such that systems that are robust to transfer across data domains, tasks and modalities is possible.
  Andrew Bates  
  Anirban Chakraborty

Anirban's research areas are Information Retrieval, Contextual Recommendation, Machine Learning. You can find more information about his research activities at Anirban Chakraborty ( 

  Robbie Court  
Yizhou Fan
 Yizhou Fan Yizhou considers himself a learning analyst using computational methods to advance the understanding of online learning strategies and self-regulated learning. His research interests are MOOC, self-regulated learning, learning design, learning tactics and strategies, and multimodal learning analytics.
Hannah Jones
Hannah Jones Hannah explores how collaborative research theory and methodologies work within an academic context. Her background is in industrial design, graduating with an Intel Scholarship, with a focus on design methodologies that address unmet user needs.
Nina Kudryashova
Nina Kudryashova Nina's research interests are: latent dynamics in neural populations; information theory; computation through dynamics.
  Iris Kyranou  
Christian Lange
Christian Lange

Christian is broadly interested in the application of machine learning methods to science. He is currently working on an ecological application (species distribution modelling using implicit neural representations), and previous to that he was focused on chemical reaction prediction / retrosynthetic route planning. 

  Yanran Li Yanran's research interest is how to make animation more automatic. Relevant topic includes graph neural networks, video prediction, human motion understanding, human interaction understanding and spatial-temporal understanding.
Eric Ma
Chenfei Ma

Chenfei's primary research interest is the deep learning and machine learning method applied in human-machine interfaces. Recently, he is working on neural network nonlinear feature reduction and visualization, which might aid in understanding deep learning methods and decoding human movements.

Martin Pullinger
Martin Pullinger

Martin's research interests: Low carbon and low energy practices, and the policies and technologies that help enable them; Quantitative and experimental research methodologies, combining sensor and survey data with data science methods.

Sohan Seth
Sohan Seth

Sohan runs the Data Science Unit (DSU) at the School of Informatics. His research focusses on building interpretable models for analysing real-world data with a focus on science, health, people and environment (SHaPE). Interested in Bayesian methods, causal models, computer vision, explainable models, exploratory data analysis, machine learning, model criticism, predictive modelling, time series modelling, unsupervised learning in the areas of art, climate, data science, disease characterisation, health informatics, medical diagnosis, patient stratification, remote sensing, risk prediction, social sciences, sustainable development, time-resolved spectroscopy, etc.

Oksana Sorokina
Oksana Sorokina

Oksana's research interests are: systems biology analysis of molecular signalling; network analysis of synaptic proteome; development of new informatics tools and databases to support neuroscience research.

Lynda Webb
Lynda Webb Lynda's areas of interest are: Digital health, care and rehabilitation; Living lab, co-creation and co-design research methods. Energy demand.
Hancong Wu
Hancong Wu Hancong's research interests include prosthetic control, the Internet of Things and tiny machine learning. His works also involve the development of circuits and systems for translational research.