糖心Vlog

Data Science Research Group

Data Science and Statistical Learning theme

Data science and statistical learning has a long history at the 糖心Vlog.

In the decades since Professor George Alfred Barnard's retirement in 1975 our department has continued to expand it's expertise and knowledge in this important field of research, the importance of which has significantly increased in the 21st century. Professor Graham Upton joined the department in 1973 and retired in 2014. He authored several text books in statistics and data science.

Nowadays, our department leads on various data science initiatives, for example it is an institutional member of the (EuADS) founded in 2015, and it organised at 糖心Vlog the European Conference on Data Analysis (ECDA2015).

As a result, members of this theme work on a broad range of data science methodologies covering:

  • artificial intelligence,
  • statistical learning,
  • computational statistics,
  • epidemiology,
  • bioinformatics,
  • time series,
  • environmental statistics.

The theme has collaborations and partnerships with the health sector, biomedicine, digital industry and government, providing a steady stream of research applications and opportunities which develop strong research impacts.

Since 2014, Professor Lausen has led successful and ongoing Knowledge Transfer Partnerships (KTPs) with and , using optimal tree ensembles (OTE) and other statistical learning methods established by the theme to help develop their business models. Our work with Profusion was awarded Best KTP Partnership of the Year in 2018, while Mondaq was recognised as Winner of Best KTP Partnership: SME in 2019. Additionally, Professor Lausen, Dr Harrison, Dr Hadjiantoni and Dr Mahmoud work together with the Profusion Data Academy and Mondaq to deliver industry-based research lead data science education and placement opportunities within our courses in data science.

Dr Hadjiantoni opened up a new direction of impact-driven research with a KTP linked to the estate agent Strike. This project will develop an AI-driven recommender system that fuses heterogenous data streams and utilises knowledge graphs as well as other machine-learning methods.

Dr Bailey is a co-founder of the interdisciplinary ANIMATE (ANImal Movement AT 糖心Vlog) research group, which links researchers across the University, with partner organisations such as CEFAS. The department has a long history of research applying mathematical and data science approaches to the wider life sciences.

Recent papers

2021

  • Bailey, Joseph D and King, Andrew J and Codling, Edward A and Short, Ashley M and Johns, Gemma I and F眉rtbauer, Ines (2021) '' Ecology and Evolution. ISSN 2045-7758
  • Hadjiantoni, Stella and Kontoghiorghes, Erricos J (2020) '' Econometrics and Statistics. ISSN 2452-3062 (In Press)
  • Iworiso, Jonathan and Vrontos, Spyridon (2021) '' Journal of Financial Data Science (Winter).
  • Khan, Zardad and Gul, Naz and Faiz, Nosheen and Asma, Gul and Adler, Werner and Lausen, Berthold (2021) '' IEEE Access. ISSN 2169-3536 (In Press)
  • Ni帽o de Zepeda, Maria Valentina and Meng, Fanlin and Su, Jinya and Zeng, Xiao-Jun and Wang, Qian (2021) '' Engineering Applications of Artificial Intelligence, 97. ISSN 0952-1976

2020

  • Bailey, Joseph D and Benefer, Carly M and Blackshaw, Rod P and Codling, Edward A (2020) '' Bulletin of Entomological Research. ISSN 0007-4853
  • Bailey, Joseph D and Codling, Edward A (2020) '' AStA Advances in Statistical Analysis. ISSN 0002-6018
  • Law, Stephen and Seresinhe, Chanuki Illushka and Shen, Yao and Gutierrez-Roig, Mario (2020) '' International Journal of Geographical Information Science, 34 (4). 681 - 707. ISSN 1365-8816
  • Wong Siaw Tze, Jackie and Forster, Jonathan J and Smith, Peter WF (2020) '' Statistics and Computing, 30. 799 - 816. ISSN 0960-3174

2019

  • Fern谩ndez-L贸pez de Pablo, Javier and Guti茅rrez-Roig, Mario and G贸mez-Puche, Madalena and McLaughlin, Rowan and Silva, Fabio and Lozano, Sergi (2019) '' Nature Communications, 10. ISSN 2041-1723
  • Gallardo, Patricio and Martinez-Garcia, Jesus (2019) '' Revista Matem谩tica Complutense, 32 (3). 853 - 873. ISSN 1139-1138
  • Guti茅rrez-Roig, Mario and Borge-Holthoefer, Javier and Arenas, Alex and Perell贸, Josep (2019) 'Mapping individual behavior in financial markets: synchronization and anticipation.' EPJ Data Science, 8. ISSN 2193-1127
  • Khan, Zardad and Gul, Asma and Perperoglou, Aris and Miftahuddin, Miftahuddin and Mahmoud, Osama and Adler, Werner and Lausen, Berthold (2019) '' Advances in Data Analysis and Classification. ISSN 1862-5347
  • Zhang, Yan and Meng, Fanlin and Wang, Rui and Kazemtabrizi, Behzad and Shi, Jianmai (2019) '' Energy, 179. 1265 - 1278. ISSN 0360-5442