Advances in Data Science 2019
More than 200 delegates came from around the world to Advances in Data Science 2019, a two-day conference exploring themes of Health & Wellbeing, AI & Robotics, NLP & Text Mining and Security & Privacy.
This year’s conference was organised by The University of Manchester’s Data Science Institute. The line-up of keynote speakers was comprised of world-leading academic and industry experts in data science, 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. Thank you to all of our speakers for contributing your expertise and presenting such a diverse range of research areas.
Day 1
- Danushka Bollegala, University of Liverpool – Language, meaning and meta-embeddings
- Byron Wallace, Northeastern University, USA- On the use and interpretation of neural attention mechanisms for biomedical natural language processing
- Elaine Farrow, University of Edinburgh- Text mining student discussion forum data:common pitfalls and how to avoid them
- Matthew Shardlow, Manchester Metropolitan University- Towards an Emoji WordNet
- Pierre Zweigenbaum, CNRS, Paris- Coping with large-scale terminology in a virtual patient dialogue system
- Georgio Metta, ITT Italian Institute of Technology, Genoa, Italy– Bespoke machine learning for humanoid robots
- Sarah Filippi, Imperial College London- Statistical hypothesis testing in a Bayesian non-parametric framework
- Frank Dondelinger, Lancaster University- Predicting progression in heterogeneous neurodegenerative diseases using a joint mixture model approach
- Catalina Vallejos, University of Edinburgh and The Alan Turing Institute- Statistical challenges in the analysis of single-cell gene expression data
- Paul Thompson, University of Manchester- Flexible, wide-coverage normalisation of medical concept mentions
- Akkapon Wongkoblap, Kings College London- Converting tweets into sequential data to detect depressed users
Day 2
- Bennett Kleinberg, University College London–Will Crime Science eventually become Data Science?
- Marion Oswald, University of Winchester- Old laws for new (algorithmic) tricks
- Paul Taylor, Lancaster University- The Synergy of Behavioural and Data Science in Security
- Lorenzo Cavallaro, Kings College London- When the Magic Wears Off: Flaws in ML for Security Evaluations (and What to Do about It)
- Michael Smtih, University of Sheffield- Adversarial Vulnerability Bounds for Gaussian Process Classification
- Silvia Chiappa, DeepMind– Fair Machine Learning
- Chris Williams, University of Edinburgh and The Alan Turing Institute- Artificial Intelligence for Data Analytics
- Reham Badawy, Aston University- Deconfounded Random Forests
- Kaspar Martens, University of Oxford- Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
- Giovanni Masala, Manchester Metropolitan University- ANNABELL integrated in iCub: towards a grounded multi language system
- Yiannis Demiris, Imperial College London – Machine Learning for personalisation in assistive robotics
THE CONFERENCE WAS CO-ORGANIZED BY:
-Professor Magnus Rattray (Data Science Institute/ University of Manchester)
-Professor Sophia Ananiadou (The University of Manchester)
-Professor Emma Barrett (The University of Manchester)
-Danielle Belgrave (Microsoft)
-Professor Angelo Cangelosi (The University of Manchester)