I am delighted to announce that our final list of speakers for DataTech19 is now available. DataTech (National Museum of Scotland, Edinburgh, 14 March) will bring together academics, members of industry and the public sector to share technical expertise, and engage in networking and collaboration. Registering for the event will provide access to talks covering a variety of topics, from supercomputing and deep learning, to tools for data visualisation and test-driven data analysis, plus many more (see below).
As a reminder following previous communications, our keynote speakers are:
- Debbie Bard, expert in machine learning at scale and data-intensive computing for experimental science, from the National Energy Research Scientific Computing Center (NERSC). Debbie will be discussing "Supercomputing and the scientist: How HPC and large-scale data analytics are transforming experimental science".
- Mine Çetinkaya-Rundel, Associate Professor of the Practice, Duke University, and Data Scientist + Professional Educator, RStudio. Mine's talk will focus on data workflows and reproducibility, explaining how to avoid situations where "The results in Table 1 don’t seem to correspond to those in Figure 2".
- Jared Lander, Chief Data Scientist of Lander Analytics and Adjunct Professor of Statistics at Columbia University. Jared will discuss the relationship between statistics, machine learning and AI, in his talk: "Making Sense of AI, ML and Data Science".
In addition, DataTech will feature a host of talks and poster presentations. Please find below a (non-exhaustive) list of speakers part of DataTech:
- Nick Radcliffe (CEO at Stochastic Solutions; Visiting professor, Department of Mathematics at the University of Edinburgh): "The Science of Bad Data"
- Valentin Radu (Research Associate at the University of Edinburgh’s School of Informatics): "Multimodal Deep Learning for Mobile and Wearable Sensing"
- Ben Moews (postgraduate student at the University of Edinburgh’s Institute for Astronomy): "Cosmology and beyond: Solutions for high-dimensional parameter estimation"
- Boris Mitrovic (Lead Data Scientist at Mudano): "Fraud Detection using Active Learning to reduce False Positives"
- Benjamin Bach (Lecturer for Design Informatics and Visualization at the University of Edinburgh): "Tools for Data Visualization"
Details on all the individual talks/posters can be found here: https://www.datafest.global/data-tech
Tickets will increase in price from the 1st of March, so pick one up before then.
If you have questions, please get in touch at: firstname.lastname@example.org
Dr. Caterina Constantinescu
Data Scientist, The Data Lab
Bayes Centre, 47 Potterrow, Edinburgh, EH8 9BT