Dr Waddah Saeed

Job: Lecturer in Data Analytics

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Address: De Montfort University, The Gateway, Leicester, LE1 9BH

T: N/A

E: waddah.saeed@dmu.ac.uk

 

Personal profile

Waddah Saeed is a lecturer in data analytics and the deputy program leader of MSc Business Intelligence and Data Mining / Data Analytics in the school of computer science and informatics. He received his Ph.D. degree in information technology from Universiti Tun Hussein Onn Malaysia in 2019, accompanied by the Gold Award (Publication Category) for his thesis.

Before joining DMU, he was a postdoctoral research fellow at the University of Agder in Norway. Prior to this, he was a lecturer at the Asia Pacific University of Technology & Innovation (APU) in Malaysia.

The areas of research he is interested in are time series analysis and forecasting, machine learning, and explainable AI.

Research group affiliations

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

Publications and outputs

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

Research interests/expertise

  • Time series analysis and forecasting
  • Machine learning
  • Explainable AI (XAI)

Qualifications

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

Courses taught

Business Intelligence

Honours and awards

  • 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.

Professional licences and certificates

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