

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 Scientist and Machine Learning Engineer with advanced Python, SQL, and Tableau skills.
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RESEARCH INTEREST
An applications of bio-inspired Machine Learning algorithms in particular neural networks in finance contexts in particular financial trading and fraud detection.
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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
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Data Analytics
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Business Intelligence/Analytics
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Big Data
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TEACHING ASSISTANT, UNIVERSITY COLLEGE LONDON
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​Introductory Programming - Python
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Programming I - Java
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Programming II - Java
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Foundations of Machine Learning and Data Science
TEACHING ASSISTANT, BIRKBECK COLLEGE, UNIVERSITY OF LONDON
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Big Data Analytics using R
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Software and Programming I - Java
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Software and Programming II - Java
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Introduction to Programming - Python

Dilek Celik' Research Group
My Active Research Projects
An application machine learning algorithms and NLP techniques to predict cryptocurrency prices using Twitter Data
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An application machine learning algorithms to agriculture - A Deep Learning-Based Herb Pair Discovering
Data: Plants
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An application machine learning algorithms to man football - A Deep Learning-Based predictive models
Data: Fifa2022
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An application machine learning algorithms to health data
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Past Research
PhD in Computer Science and Information Systems, Birkbeck College, University of London
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Research Scientist, Knowledge Media Institute of Open University
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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.
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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.
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Performed analyses: building statistical models, apply machine learning techniques using various software libraries, building models and simulations and applying optimisation techniques.
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Collaborated with research colleagues and academics from other institutions to design data mining experiments.
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Deployed data science cycle (understand the problems, collect, manage, and clean data, exploratory analysis, build a model and validate model) and built technical reports.
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Design, planning and developing software for communication with users.
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Moved prototypes into a production environment.
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SELECTED PUBLICATIONS
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Celik, D., Jain, S. (2024). Implementation of Machine Learning and Deep Learning in Finance. In: Jahankhani, H., Bowen, G., Sharif, M.S., Hussien, O. (eds) Cybersecurity and Artificial Intelligence. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-52272-7_3
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Celik, D., Herzog, N.J., Sulaiman, R.B. (2024). Artificial Intelligence in Healthcare and Medical Records Security. In: Jahankhani, H., Bowen, G., Sharif, M.S., Hussien, O. (eds) Cybersecurity and Artificial Intelligence. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-52272-7_2
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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
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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
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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
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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
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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
For any general inquiries, please fill in the following contact form: