Dr Waddah Saeed

Waddah Saeed is a Senior Lecturer in data analytics and holds the position of Program Lead for MSc Data Analytics and MSc Business Intelligence and Data Mining in the School of Computer Science and Informatics at De Montfort University (DMU). He earned his Ph.D. in information technology from Universiti Tun Hussein Onn Malaysia in 2019, where he received the Gold Award in the Publication Category for his thesis. Before joining DMU, he worked as a postdoctoral research fellow at the University of Agder in Norway. Prior to that, he held a lecturing position at the Asia Pacific University of Technology & Innovation (APU) in Malaysia. His research interests encompass time series analysis and forecasting, machine learning, and explainable AI.

• Institute of Artificial Intelligence (IAI)
• Centre for Computing and Social Responsibility (CCSR)

A full and updated list of publications can be found in the Google Scholar link below.
https://scholar.google.com/citations?user=2pqJUFEAAAAJ

• Time series analysis and forecasting
• Machine learning

Data Mining Techniques and Applications, Advanced Data Analytics, Data Visualisation, Business Intelligence, and Database Design.

• PhD in Information Technology.
• Master in Computer Science (Soft Computing).
• BSc in Computer Science.

MSc Data Analytics, Business Data Analytics BSc (Hons), Business Information Systems BSc (Hons), and BSc Applied Computing.

• Gold Award (Publication Category), Universiti Tun Hussein Onn Malaysia, Malaysia, 2019.
• Best Paper Award, 3rd international conference of reliable information and communication technology, Malaysia, 2018.
• Best Paper Award, 2nd international conference on soft computing in data science, Malaysia, 2016.

Fellow of the Higher Education Academy (FHEA), Advance HE-UK, 2023  - Present.

• University Pedagogy Course, University of Agder, Norway, 2022.
• NVIDIA DLI Certificate – Fundamentals of Deep Learning for Multi-GPUs, NVIDIA Deep Learning Institute, 2021.

Guest Editor, Special Issue "Intelligent Energy Forecasting Solutions: Machine Learning Driving Renewable Energy Advancements", Applied Sciences (IF = 2.7) , MDPI

https://www.mdpi.com/journal/applsci/special_issues/T5G3U361F1

- External grant reviewer, Dutch Research Council.

- Reviewer for various publishers such as Elsevier, Springer, MDPI, Hindawi, and IET.

- Technical Program Committee member for various international conferences worldwide, including those held in Spain, Finland, Norway, Malaysia, United Arab Emirates, Bahrain, and Egypt.

Prospective students with their own funding are encouraged to reach out. Please provide a brief overview of your research interests and academic background. I am particularly interested in the following areas:

• Hierarchical Time Series Forecasting
• Forecasting Large Collections of Time Series Data
• Explainable AI for Time Series Forecasting
• Forecast Reconciliation
• Graph Neural Networks for Time Series Forecasting

If you have a specific project or concept in mind that aligns with my research interests, please include it in your introduction.