Strategy 2016-2021

Contents Foreword The Vision and Mission Strategic Objectives Research Education Technologies Translation Promotion

FOREWORD Professor Yi-ke Guo, Director, Data Science Institute Big Data is frequently described as heralding a revolution and the transformation of society. The scale of the data challenge is clear. How we manage, process and analyse this data to extract knowledge or insight is an important question for academics, businesses and policy makers, and one which needs to be addressed promptly. Data Science is an emerging discipline which seems to address this question by employing techniques and theories drawn from many fields within the broad areas of mathematics, computer science and statistics etc. Imperial College has specifically chosen leading the data revolution as one of its key research themes in its 2015-2020 strategy. The Data Science Institute has been created to act as a focal point across the College to address this research theme. Building upon the achievements that we have already accomplished in our inaugural year, and from engaging with the College community, we have devised a five year strategic plan to allow us to continue to contribute to the College research environment and add value to data science advancement across all disciplines within the College and beyond. In delivering our new strategy we wish to create a world class data science research base at Imperial and to seize the opportunity to create an environment that fosters collaboration and innovation in data driven research and education on a global scale.

VISION Our vision is to use data to create a better world. MISSION Our mission is to foster, advance and promote excellence in data science research, education and application across all domains for the benefit of society.

STRATEGIC OBJECTIVES 1 2 3 To act as a focal point for coordinating data-driven scientific research at Imperial through stimulating cross-disciplinary collaboration. To train and educate the new generation of data scientists. To develop data management and analysis technologies and services for supporting data driven research.

4 5 To enable the translation of data science innovation by close collaboration with partners including industry and the public sector, and supporting commercialisation. To promote data science and its applications to the general public and to influence policy makers.

RESEARCH

1 We will act as a focal point for coordinating data driven scientific research at Imperial through stimulating cross-disciplinary collaboration 1. We will conduct fundamental research in data science and its broad applications. 2. We will create a series of academic Labs bringing together inter-disciplinary data science expertise to ensure that our programme of research is developed in a focused, valuable and sustainable manner. 3. We will continue to support the development of cross-college strategic applications. 4. We will recruit and nurture world class data scientists through joint appointments with academic departments and other mechanisms. 5. We will continue to be a central co-ordinating hub for external engagement in data research with national and international Research Institutes. 6. We will facilitate access to funding for data driven research and develop a data science fund to encourage and support inter-disciplinary data science research across the College. 7. We will support our investigators through creating a culture of knowledge transfer. 8. We will collaborate and work closely with the College s cross-faculty Institutes. 9. We will create hubs of data science expertise which will work across College campuses by establishing a DSI Investigator network. 10. We will actively engage in the College s development plans for White City Campus. Case studies Social and Cultural Analytics Lab Under the leadership of Professor Armand Leroi (Professor of Evolutionary Developmental Biology ) the new Social and Cultural Analytics Lab within the DSI has been established to bring together researchers from across disciplines, from evolutionary biology and linguistics to machine learning and neuroscience, to form a network of academics interested in the acquisition, analysis and explanation of large amounts of social and cultural data. The Lab, launching in November 2015, will seek to nurture and support College activities which investigate the science of human behaviour and interaction, ranging from cultural evolution and artistic creativity to online collaboration and digital markets. EPSRC Maths in Healthcare In early 2015, EPSRC announced a commitment of 6m to support the creation of Multidisciplinary Research Centres, bringing together researchers working in the Mathematical Sciences with academics and stakeholders within the Healthcare Technologies space. The DSI, in collaboration with Principle Investigator Professor Barahona from Department of Mathematics and a number of academics from the Faculties of Engineering and Medicine including Lord Ara Dazi and Professor Paul Matthews, facilitated an application for an EPSRC Centre for the Mathematics of Precision Healthcare. The Programme was awarded and research is due to begin in 2016. The Centre will address the need for the development of novel mathematical and algorithmic techniques for the analysis and interpretation of data-rich healthcare applications in close collaboration with end users, so as to inform decision-making in healthcare. The DSI will play a central role in this new Centre to link mathematical research with medical industry and clinicians to conduct data driven healthcare research projects.

EDUCATION

2 Case studies We will train and educate the new generation of data scientists 1. We will work with employers, our network of alumni and College departments to develop MSc plug-in modules that can be embedded into a number of existing College MSc courses, ensuring that Imperial graduates are prepared for data science challenges in the workplace. 2. We will participate in the establishment of doctoral training bases, such as Centres of Doctoral Training (CDT), to build up education platforms for advanced data science specialists. 3. We will promote the training of PhD students through setting up cross-disciplinary PhD scholarships and provide access to our unique facilities for their research. 4.We will engage with education authorities to ensure that young people in our secondary schools understand the importance that data science will play in future society. 5. We will work with businesses to provide bespoke data science training for their employees to help industry deal with data science challenges. 6. We will engage and support our data science student community through providing opportunities for networking, entrepreneurship, and links with industry. 7. We will promote best practice in data science teaching by co-ordinating College wide student data challenges such as Best Thesis Prize and Data Challenge Hackathons. MSc in Business Analytics The Data Science Institute aims to ensure that an education in data science skills and theory is available to all students across the breadth of Imperial s four faculties. Through collaboration with Imperial College Business School the DSI is providing two compulsory modules on Imperial s new MSc course in Business Analytics: Very Large Data Management and Advanced Analytics and Machine Learning. Starting in the academic year 2015/16 these modules will teach the cohort of 50 students how to manage and analyse very large data sets, using text mining and machine learning methods to solve practical problems. Through such initiatives the DSI seeks to position Imperial graduates at the forefront of the data revolution, equipped with the technical skills and knowledge necessary to use big data to help solve today s challenges in industry and academia. Data Science Society The Imperial College Data Science Society (ICDSS) launched in October 2015 and is an opportunity for students to engage with and learn about data science. With members from various degree backgrounds, including Engineering, Natural Science, Medicine and the Business School, ICDSS has an extensive student reach within the Imperial college student community. Further to creating awareness regarding the scope and potential of data science amongst the student body, ICDSS is working towards harnessing the intelligence and creativity of Imperial s talented students to become the UK s leading assemblage of data scientists and entrepreneurs. Striving to become a think-tank for invention and innovation, ICDSS draws inspiration from industry, by inviting companies to share their involvement and application of data science. This provides a bilateral platform for interaction between Imperial students and industry.

TECHNOLOGIES

3 Case studies KPMG Data Observatory We will develop data management and analysis technologies and services for supporting data driven research 1. We will continue to work with academia and industry to maintain and further invest in our state-of-the-art facilities and develop new technologies in data management and analysis. 2. We will promote a culture of innovation and entrepreneurship to further develop ways in which these technologies can be used as widely as possible for the academic and industrial communities. 3. We will engage closely with our stakeholders to understand the future technologies and services that are required for world leading, cutting-edge research. 4. We will continue to work with the academic community to promote and enhance the College s Research Data Management strategy. The KPMG Data Observatory officially launched in November 2015. This Data Observatory is a state-of-the-art data visualisation and decision-making studio comprising over 100 million-pixel display environment with 64 screens supported by an immense data-processing and analysis capacity. It is the largest facility of its kind in Europe and one of the highest resolution visualisation suites in the world. It provides a multi-dimensional and immersive environment to analyse large and complex data sets and provide deeper insights for solving business issues and creating new value from data. This DSI facility brings together academics, data scientists and businesses from across industries, to translate data into visible knowledge and insights for supporting decision making. Data Assimilation Lab Data Assimilation is the process through which observations are collected over a period of time and incorporated into computer models, with applications typically within the fields of weather forecasting and hydrology. This technology has now been further developed for data driven modelling and simulation. The technology bridges the gap between computational science and data science and can be broadly applied to complex systems and engineering. A new Data Assimilation Lab has been formed as a DSI Lab to support the development and application of this technology. Professor Christopher Pain (Earth Science Engineering) will head the Lab which will seek to communicate and expand the world class research being undertaken at Imperial College in this area with a broad spectrum of applications ranging from physiological modelling to nuclear safety.

TRANSLATION

Case studies 4 1. We will enable the translation of data science innovation by close collaboration with partners including industry and supporting commercialisation We will strive to become the partner of choice for industry collaborators. 2. We will work with our external advisory board, data science alumni and industry experts to understand, engage with and address the needs of industry. 3. We will work with College to ensure the processes of collaboration are smooth and efficient, allowing us to develop innovative cross-college collaboration models for working with industry partners. 4. We will strengthen the support available to our academic community through acting as a facilitator to developing long-lasting relationships with partners for collaborations. 5. We will continue our success in building industrial funded research labs as a vehicle for closely coupled collaborative research activities with industry. Huawei Technologies An investment from Huawei Technologies in 2014 has made possible the launch of the Imperial College-Huawei Data Innovation Lab. The mission of this Lab is to foster cooperation between Imperial College London and Huawei by funding research projects at Imperial College in the area of big data and its application. Like the Institute, the Lab strives to encourage interdisciplinary research and in particular, to show that innovative data analytics methods developed in one application domain (e.g. health care) can be reused successfully in another (e.g. telecommunication networks). In early 2016, the Lab will release a call for applications for top-up funding for projects across the College focusing on the development of innovative algorithms for high performance data analysis in a number of application areas including smart cities and healthcare. Genomics England In Autumn 2015, Genomics England (GeL) and the DSI committed to a joint collaboration programme on Translational Informatics. The aim is to carry out research in building the most advanced informatics infrastructure for translational medical research. The Programme will be situated within the DSI, thus working jointly with the etriks research teams in the Institute (etriks is a 23M European project in building up translational informatics infrastructure for medical research). Such a setting will enable GeL s requirements to be responded to in a timely manner by the development team in the DSI working on the world s most adaptable medical infrastructure system, TranSMART. The DSI and GeL have a mutual desire to further develop the joint collaboration programme with more corporate partners to be the leading translational informatics research collaboration programme in the country.

PROMOTION

5 1. Case studies We will promote data science and its applications to the general public and to influence policy makers We will continue to use the latest digital and social media to ensure that information on events, discoveries and latest advances in data science reaches a wide and diverse audience. 2. We will continue to deliver and engage in a wide programme of events and activities to promote data science to the public and wider community such as Imperial Festival, Fringe events and high profile lecture series. 3. We will promote data science advances on the visual corridor screens on the South Kensington Campus. 4. We will actively engage with the Data Science Society to promote data science advancements across the student body. 5. We will continue to promote data science on a global scale through hosting international conferences and developing collaboration programmes with world-leading universities. 6. We will work with our academic colleagues to produce white papers to influence policy makers. Thomson Reuters Data Insight Series Since 2014 the Data Science Institute has partnered with Thomson Reuters to hold our flagship speaker series, Data Science Insights. The series, open to all, invites high profile speakers from a range of backgrounds to offer their insight into how academia, industry, policy and society are being disrupted by the data revolution. In our most recent Data Insights event, Steve Furber, Professor of Computer Engineering at the University of Manchester gave a talk at the Royal Institution scheduled as part of London Technology Week. His talk, Building Brains: Learning from Data, explored the development and impact of machine learning on our lives today and in the coming years, from self-driving cars to real-time machine translation. Other talks in the series have explored improbability, how data can be used to influence human decisions, and how big data is changing what you eat and buy. Zhejiang University The Imperial College-Zhejiang University Joint Lab for Applied Data Science was created in 2014. Over the past twelve months, the Lab has achieved much in the way of promoting data science internationally through developing three joint research projects and hosting a number of visiting researchers and professors. One of the greatest achievements of the Joint Lab to date was an in depth data analysis of Chinese Migration in last five years. This analysis was turned into a visual demonstration and shown to the Chinese President Xi Jinping upon his visit to the DSI in October 2015 as an example of how policies can affect the structure of societies and the country s urbenisation.