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

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.

Introducing the Data Science Institute

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?

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

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.

Academics

Academics

  • Dr Wenjia Bai

    Personal details

    Dr Wenjia Bai Senior Lecturer in Artificial Intelligence in Medicine

    Location

    Data Science Institute, William Penney Laboratory

    Research interests

    Medical image analysis and understanding, machine learning.

  • Dr Marc Deisenroth

    Personal details

    Dr Marc Deisenroth Visiting Professor

    +44 (0)20 7594 8234

    Research interests

    Statistical Machine Learning, Robotics, Control, Time-Series Analysis, Signal Processing.

  • Dr Yves-Alexandre de Montjoye

    Personal details

    Dr Yves-Alexandre de Montjoye Reader

    +44 (0)20 7594 0991

    Location

    Data Science Institute, William Penney Laboratory

    Research interests

    Privacy, Machine learning, AI Safety, Memorization, Automated attacks.

  • Prof Aldo Faisal

    Personal details

    Prof Aldo Faisal Professor of AI & Neuroscience

    +44 (0)20 7594 6373

    Location

    407A, Huxley Building
    4.08, Royal School of Mines

    Research interests

    Neurotechnology, biomedical engineering, machine learning, algorithmic prediction of human behaviour.

  • Dr Thomas Heinis

    Personal details

    Dr Thomas Heinis Reader

    +44 (0)20 7594 8276

    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 Analysis

    +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

    Personal details

    Dr Peter McBrien Senior Lecturer

    +44 (0)20 7594 8202

    Location

    428, Huxley Building

    Research interests

    Data integration, information systems, modelling, distributed databases.

  • Dr Pedro Mediano

    Personal details

    Dr Pedro Mediano Lecturer

    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 Research

    +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

    Personal details

    Dr Holger Pirk Senior Lecturer

    +44 (0)20 7594 3008

    Location

    431, Huxley Building

    Research interests

    Data management, database systems, analytical query processing, and processing models for modern hardware.

  • Islem Rekik

    Personal details

    Islem Rekik Senior Lecturer at I-X

    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.