Developing the Management Studies Community: Data Science Workshops

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



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 . 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 – 13.45

Big data projects and academic research
Prof Savvas Papagiannidis, Newcastle University Business School

13.45 – 14.30

Generative AI in academic research: overview and practical considerations
Dr Panos Panagiotopoulos, Reader in Information Management and Fellow of the Alan Turing Institute

14.30 – 14.45

Coffee Break

14.45 – 16.00

Data Challenges Café: presentations and group discussion

16.00 – 16.15

Wrap-up and close