We live in a time where information about most of our movements and actions is collected and stored in real-time thanks to technological advancements. A large number of increasingly small sensors are used everywhere (from mobile phone to IoT devices) while advances in data storage, indexing, and processing platforms allow us to store and process data cheaply and efficiently: “It is now cheaper to keep data rather than to delete it”. Data science strives to develop the methods and tools to unlock the value in massive amounts of data safely and ethically.
Interdisciplinary in nature, it employs theories and techniques from computer science, statistics, machine learning, and mathematics to understand, analyze and potentially affect human, physical, and societal phenomena. Big data from credit card transactions, browsing history, social networking, genetic tests or many other sources have the potential to radically transform science and industry with Harvard Business Review calling Data Scientist “the sexiest job of the 21st century”.
The Department of Computing at Imperial, along with Imperial’s Data Science Institute, creates a unique environment for Data Science by bringing together world-leading computer scientists along with researchers in medicine, biology and the social sciences. Our work aims to revolutionize applications in medicine, cyber-security, development economics, bioinformatics, behaviour analytics and many more.
Related videos
Introducing the Data Science Institute
Data science is the driving force of the new economy.
The Data Science Institute is a cross-faculty body set up to coordinate data science research at Imperial. This video introduces the diverse scientific disciplines at the core of the Institute and its potential impact on the modern world.
Are you dining on data?
Data Science Insights - Are you dining on data? (highlights)
At this event Derek Scuffell, Syngenta R&D Data Strategist, and Judith Batchelar, Director of Brand at UK supermarket chain Sainsbury's, each shared insights in how their supply chains are driven by data and how the world will be able to feed itself in the future because of data.
Building Brains: Learning from data
Data Science Insights - Building Brains: Learning from data (highlights)
At this event Professor Steve Furber CBE from the University of Manchester, talked about how his new hardware architecture, SpiNNaker, is pioneering neural network research and then shared insights into how progress in his field will develop computer-based intelligence. Axel Threlfall, editor-at-large at Reuters, chaired this event.
Research groups and centres
Academics
Academics
-
Dr Marc Deisenroth
Research interests
Statistical Machine Learning, Robotics, Control, Time-Series Analysis, Signal Processing.
-
Dr Yves-Alexandre de Montjoye
Location
Data Science Institute, William Penney Laboratory
Research interests
Data privacy, machine learning, biometric and behavioural identification, safe and anonymous use of data, data science for good.
-
Prof Aldo Faisal
Location
407A, Huxley Building
4.08, Royal School of MinesResearch interests
Neurotechnology, biomedical engineering, machine learning, algorithmic prediction of human behaviour.
-
Dr Thomas Heinis
Location
423, Huxley Building
Research interests
Scientific data management, distributed data processing, spatial databases, indexing.
-
Prof. William Knottenbelt
Personal details
Prof. William Knottenbelt Professor of Applied Quantitative AnalysisSend email+44 (0)20 7594 8331
Location
363, ACE Extension
Research interests
Mathematical modelling and optimisation, parallel queueing systems, resource allocation, Markov models, decentralised finance, blockchain, and cryptocurrencies.
-
Dr Peter McBrien
Location
428, Huxley Building
Research interests
Data integration, information systems, modelling, distributed databases.
-
Dr Pedro Mediano
Location
572, Huxley building
Research interests
Computation in neural systems, computational cognitive neuroscience, information theory, machine learning, neurodynamics, mental health, and consciousness.
-
Prof. Peter Pietzuch
Personal details
Prof. Peter Pietzuch Professor of Distributed Systems and Director of ResearchSend email+44 (0)20 7594 8314
Location
442, Huxley Building
Research interests
Distributed systems, operating systems, data management, stream processing, data-intensive applications, networking, systems for machine learning, security, confidential computing, trusted hardware, and decentralised ledgers.
-
Dr Holger Pirk
Location
431, Huxley Building
Research interests
Data management, database systems, analytical query processing, and processing models for modern hardware.
-
Islem Rekik
Location
5th floor, Imperial-X (I-HUB) White City Campus
Research interests
Machine learning, deep learning, predictive intelligence in medicine, network neuroscience, holistic artificial intelligence.