FREE TALK | Machine Learning-based Integrated Earned Value Method
Registration: By Dr Pang Der-Jiun, PhD, PMP, PMI-ACP, ITIL, CITPM, COBIT, AWS-CLP
Program Synopsis:
IT project success rate has remained low over the past two decades (The Standish Group, 2015). Significant projects collapsed or partially failed, resulting in considerable losses to many organisations in Malaysia and Singapore (Low & Ling, 2018; Idrus et al., 2019) and worldwide (Rosato, 2018; Jorgensen, 2019). It lacks effective tools and techniques to improve the project success rate (Janssen, 2019). Therefore, a novel machine learning-based integrated earned value method (IEVM) was introduced to increase the IT project success rate. This method serves as an early warning system, allowing project practitioners to identify problematic projects as early as possible in the project lifecycle, providing a window of opportunity to de-risk and get the project back on track.
This 1.5-hour forum aims to share its background and challenges, literature review, and findings through a quantitative survey explaining IEVM in addressing a critical IT project risk factor. Later, IEVM design, experiments, and verification results are shared. This session ends with a discussion by giving an overview of AI, ML, and DL and their potential impacts.
Program Content:
- Introduction
- Literature Review
- Quantitative Survey
- IEVM
- Experiments and Results
- Verification and Discussion
Speaker Profile:
Dr. Pang Der Jiun (a.k.a “DJ”)
- PhD, Certified PMP, PMI-ACP, ITIL, CITPM, COBIT, AWS-CLP
DJ graduated from the University of Leicester (UK) with a B.Eng. in Electrical and Electronics Engineering with 1st Class Honours. He subsequently finished his studies at the National University of Singapore with a dual M.Sc. degree in Electrical Engineering and Management of Technology. DJ later completed his PhD in Project Management from the International University of Malaya-Wales. He has successfully implemented over one hundred projects in various industries in the Asia Pacific Region, specialising in PMO, program, portfolio, and project management and governance.
Tentative Program Flow:
8:15 pm – 8:30 pm: Registration and Self-Introduction
8:30 pm – 8:45 pm: Introduction and Literature Review
8:45 pm – 9:00 pm: Quantitative Survey. IEVM
9:00 pm – 9:15 pm: Experiments and Results
9:15 pm – 9:30 pm: Verification. AI and its potential
9:30 pm – 9:45 pm: Q&A
Program Logistics:
Date: To be determined
Time: 8:30 pm – 10:00 pm
Venue: Live Online via ZOOM
Contact Dr Mui Kai Yin, [email protected], hp: +6012-431 9290