Advances in Data Science Conference 2018

ADS Conference

More than 185 delegates came from around the world to Advances in Data Science 2018, a two-day conference exploring data science's potential to support societal well-being.

This year's conference (21st and 22nd May 2018) was jointly organised by The University of Manchester's Data Science Institute and the Cathie Marsh Institute for Social Research. The line-up of keynote speakers comprised of world-leading academic and industry experts in data science and social sciences, and the two-day event provided a platform for the international community of researchers, analysts and industry leaders to connect and share research and expertise. The Data Science Institute would like to thank the speakers for contributing their expertise and presenting such a diverse range of research areas.

Key Applications

Focusing on Gaussian processes, Deep learning, latent variable models, subspace learning, network models, spatio-temporal models and longituinal data, the presentations explored the ways in which these methodologies can be used to address challenges faced by those working in the key application areas:

Health - Security - Criminology - Discrimination/Bias - Politics - Demographics - Urban Planning - Global Challenges - Social Media - Conservation

Day 1

  • Jasmine Latham, Office for National Statistics Data Science Campus - Data science for public good - harnessing the power of data science at the Data Science Campus, Office for National Statistics
  • John Quinn, UN Global Pulse, Uganda- Humanitarian Applications of Machine Learning with Remote Sensing Data
  • Michael T. Smith, University of Sheffield- Gaussian Process Models for Low Cost Air Quality Monitoring
  • Reham Badawy, Aston University- Automated quality control for sensor based symptom measurement performed outside the lab
  • Ciira Wa Maina, Dedan Kimathi University of Technology, Kenya- Leveraging Machine Learning, Citizen Science and Low Cost Sensors for Acoustic Monitoring of Ecosystems: A Case Study in Kenya
  • Reka Solymosi, University of Manchester - Everybody Lies but Not Everybody Tweets: Making Sense of the Bias in Your Data
  • Toby Davies, University College London- Understanding and Predicting Urban Patterns of Crime
  • Jonathan Carlton, University of Manchester- Using Low-Level Interaction Data to Explore User Behaviour in Object-Based Media Experiences
  • Peter Burnap, Cardiff University- Data Science for Cyber Security
  • Omar Costilla-Reyes, University of Manchester- Analysis of Spatio-temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks
  • Haiping Lu, Sheffield University- Tensor Analysis and Learning for Multidimensional Data in Brain Imaging

Day 2

  • Licia Capra, University College London-Offline biases in online platforms
  • Walid Magdy, University of Edinburgh- Online Users' Behaviour Understanding and Prediction with Data Science
  • Jonathan Nagler, New York University- Geo-Locating Twitters Users into Political Places
  • Niklas Loynes, University of Manchester/NYU- Forecasting the 2018 US midterms: A social panel approach
  • Federico Botta, Warwick University- Early indicators of the number of visitors to museums based on Google data
  • Ciro Cattuto, ISI Foundation, Italy- Social Networks in Physical Space
  • Danielle Belgrave, Microsoft Research and Imperial College London- Machine Learning for personalised healthcare
  • Giovanni Mizzi, University of Warwick- Tracking dengue in Rio de Janeiro using Google and Twitter: an operationally realistic approach
  • Glen Martin, University of Manchester- A Multiple-Model Generalisation of Updating Clinical Prediction Models
  • Elizabeth Buckingham-Jeffery, University of Manchester- Gaussian process approximations for fast inference from infectious disease data
  • Philip Bourne, University of Virginia- Student team hacking into problem of veteran suicide


Many thanks to the event sponsors, who kindly supported Advances in Data Science 2018: Royal Statistical SocietyAutoTrader and BJSS.

The conference was co-organized by:

-Professor Magnus Rattray (Data Science Institute/ University of Manchester)
-Professor Rachel Gibson (University of Manchester)
-Professor Mark Elliot (University of Manchester)
-Professor Neil Lawrence (Amazon)
-Dr Suzy Moat (University of Warwick)