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Dr DILEK CELIK, PhD

Holds  PhD in Computer Science

from Birkbeck, University of London. 

IBM, Stanford University and Massachusetts Institute of Technology certified professional in Data Science and Machine Learning with advanced Java, Python, R and Machine Learning expertise and experiences.

RESEARCH INTEREST

An applications of bio-inspired Machine Learning algorithms in particular neural networks in finance contexts in particular financial trading. 

ABOUT

ME

Dilek Celik is a lecturer at Northumbria University, London. She obtained her Ph.D. (2019) degree from the Computer Science and Information Systems Department of Birkbeck College under the supervision of George D Magoulas. She obtained her MA degree from San Francisco State University and her BSc degree in Computer Science and Instructional Technologies (2010) at Ege University. She involved in the UK's National Institute of Coding Project in learning analytics as part of Knowledge Media Institute of Open University (2018). Outcomes of her research are published in major computer and education conferences such as EC-TEL and ICWL.
 

TEACHING

LECTURER, NORTHUMBRIA UNIVERSITY, LONDON
  • Data Analytics
  • Business Intelligence/Analytics
  • Big Data
TEACHING ASSISTANT, UNIVERSITY COLLEGE LONDON
  • ​Introductory Programming - Python
  • Programming I - Java
  • Programming II - Java
  • Foundations of Machine Learning and Data Science
 
TEACHING ASSISTANT, BIRKBECK COLLEGE, UNIVERSITY OF LONDON
 
 

RESEARCH

 

PhD in Computer Science and Information Systems, Birkbeck College, University of London

Research Scientist, Knowledge Media Institute of Open University

  • Carried out research as a part of the Institute of Coding Projects (www.instituteofcoding.org), a national initiativewith Åí20m funding aiming to enhance the education and employability.

  • Delivered improvements in end-to-end automated learning data analytics including transferring data into experience API statements for standardisation, sending data into Learning Record Store (LRS), extracting data from LRS, and developing machine learning (a subfield of Artificial Intelligence) models for students’ performance prediction.

  • Performed analyses: building statistical models, apply machine learning techniques using various software libraries, building models and simulations and applying optimisation techniques.

  • Collaborated with research colleagues and academics from other institutions to design data mining experiments.

  • Deployed data science cycle (understand the problems, collect, manage, and clean data, exploratory analysis, build a model and validate model) and built technical reports.

  • Design, planning and developing software for communication with users.

  • Moved prototypes into a production environment.

SELECTED PUBLICATIONS

  1. Celik D., Mikroyannidis A., Hlosta M., Third A., Domingue J. (2019) ADA: A System for Automating the Learning Data Analytics Processing Life Cycle. In: Scheffel M., Broisin J., Pammer-Schindler V., Ioannou A., Schneider J. (eds) Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science, vol 11722. Springer, Cham

  2. Celik D., Magoulas G.D. (2019) Challenging the Alignment of Learning Design Tools with HE Lecturers’ Learning Design Practice. In: Scheffel M., Broisin J., Pammer-Schindler V., Ioannou A., Schneider J. (eds) Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science, vol 11722. Springer, Cham

  3. Celik D., Magoulas G.D. (2016) Approaches to Design for Learning. In: Chiu D., Marenzi I., Nanni U., Spaniol M., Temperini M. (eds) Advances in Web-Based Learning – ICWL 2016. ICWL 2016. Lecture Notes in Computer Science, vol 10013. Springer, Cham

  4. Celik D., Magoulas G.D. (2016) A Review, Timeline, and Categorization of Learning Design Tools. In: Chiu D., Marenzi I., Nanni U., Spaniol M., Temperini M. (eds) Advances in Web-Based Learning – ICWL 2016. ICWL 2016. Lecture Notes in Computer Science, vol 10013. Springer, Cham

  5. Celik, D., & Magoulas, G. D. (2016). Teachers’ Perspectives on Design for Learning Using Computer-BasedInformation Systems: A Systematic Literature Review. In 21st UKAIS Conference. University of Oxford, United Kingdom. Available at https://www.researchgate.net/publication/301685917_TEACHERS%27_PERSPECTIVES

 

CONTACT

DILEK CELIK

 ADDRESS

Birkbeck, University of London

Malet St.

London, UK WC1E 7HX

 

Tel: 020 7631 8151

Fax: 020 7631 6727

 

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