Dr Merve Alanyali is a Data Scientist at LV= with more than five years experience in academic research. She draws on an interdisciplinary background in computer science, complex systems and behavioural science. Prior to joining LV=, she worked at The Alan Turing Institute as a research associate leading a group of data scientists on a short-term collaborative project with one of the top electronics companies. She completed her doctoral degree on “Quantifying human behaviour using online images ” at the University of Warwick with Chancellor’s International Scholarship and The Alan Turing Institute Enrichment Scheme funding. She was awarded a double degree Masters degree in Complex Systems Science by the University of Warwick and Chalmers University of Technology, Sweden. Her work has been featured by television and press worldwide including coverage in Financial Times and Bloomberg Business.
- data science,
- machine learning,
- artificial intelligence,
- deep learning,
- computational social science (social data science),
- quantifying human behaviour through online data (and any similar topics)
In today’s digital world, we are generating unprecedented amounts of data via interacting with technological devices and the online services they are connecting us to. Automatic analysis of these gigantic datasets are offering numerous benefits in governmental and commercial arena from shedding light onto everyday human behaviour to equipping decision makers with the most up to date information as possible.
However, due to the diverse nature of information sources, data can come in many forms including time series, text data or visual media such as pictures. It is therefore crucial to understand the distinctive characteristics of the underlying data and choose an appropriate approach to extract meaningful information from these raw datasets. This need has led to the emergence of the field data science.
As a data scientist with more than five years of research experience, I am enthusiastic about combining diverse set of machine learning methods to address complex data science problems. I give talks on a wide range of topics around data science including introductory talks focusing more on the applications and possibilities data science opens up as well as advanced talks and workshops on more specialised subjects such as traditional machine learning approaches and deep learning. My talks/workshops can be customised based on the previous knowledge and expertise of the target audience.