Supported by SAMS, BAM Ebusiness & Egovernment SIG, Queen Mary University of London, Coventry University, Newcastle University Business School,
Organisers: Dr Panos Panagiotopoulos, Prof. Maureen Meadows, Prof. Savvas Papagiannidis
Further details: https://ebusiness.ncl.ac.uk/news/events/24_02_workshop.php
This is the 3rd of the three data science workshop organised. For more information about this event series, please click here.
Registration
The event is free to attend. As there are limited spaces you need to register before attending. To register please email: Dr Panos Panagiotopoulos p.panagiotopoulos@qmul.ac.uk. Thanks to the generous support provided by SAMS and the BAM Ebusiness & Egovernment SIG we can offer a number of travel bursaries to doctoral students (first-come-first-served basis).
Doctoral and Early Career Researcher Symposium
New forms of data, data science and data analytics have reshaped social science research over the past years. Rapid growth has been spurred on by the proliferation of complex and rich data in science, industry and government, which are potentially available for research. As a result, (big) data analytics are no longer the preserve of engineering and computer science students, but as big datasets are increasingly becoming common in most domains, analytical skills have become essential to most fields of study and practice, and certainly to social science and Business School students. These trends have set new expectations about research questions, data collection and analysis methods as well as the general skills of doctoral students in social science research. Social science doctoral programmes have responded to the challenge of integrating new methods at the intersection of the computational and social sciences with new programmes and communities. Beyond these specialised programmes, the vast majority of doctoral courses have not caught up methodologically with advances in the area or are not able to harness the potential fully.
Programme
Location: Digital Environment Research Institute, Queen Mary University of London, Empire House, 67-75 New Rd, London E1 1HH (MAP)
Programme: : 19th February 2024
| 09.00 – 09.30 | Arrival and registration |
| 9.30 – 09.45 | Welcome by the workshop organisers |
| 09.45 – 10.30 | Embedding data science principles in doctoral research projects Dr Valentin Danchev, Lecturer in Business Analytics and author of the Reproducible Data Science with Python textbook |
| 10.30 – 11.00 | Coffee Break |
| 11.00 – 12.00 | Data science and AI upskilling: resources and initiatives at the Alan Turing Institute Mishka Nemes, Skills and Training Manager at the Alan Turing Institute |
| 12.00 – 13.00 | Lunch |
| 13.00 – 14.00 | Generative AI in academic research: overview and practical considerations Dr Panos Panagiotopoulos, Reader in Information Management and Fellow of the Alan Turing Institute |
| 14.00 – 14.15 | Coffee Break |
| 14.15 – 16.00 | Data Challenges Café: presentations and group discussion |
| 16.00 – 16.15 | Wrap-up and close |