Alex is a trained statistician and data scientist working in the field of data analytics and Machine Learning on tabular data. He received his M.Sc. degree from the School of Mathematics and Statistics, Victoria University of Wellington, New Zealand, where he is currently pursuing a Ph.D degree in data science. He currently works as a principal analyst at Ministry of Business, Innovation and Employment (MBIE) and lead researcher of an Integrated Data Infrastructure (IDI) project, exploring the application of data synthesis on social data. His research interests include data-centric AI, tabular data synthesis and explainable AI application on social data.

Impacts / Research Outputs
TBA
A Synthetic Minority Oversampling Technique using Edited Displacement-based k-Nearest Neighbors.
TBA
Challenges and opportunities of generative models on tabular data.
TBA
Early detection of depression using machine learning and social well-being survey data during the early phase of the COVID-19 pandemic.
TBA
Enhancing Data Governance through Data-Centric AI: Case Study in New Zealand Government Sector.
TBA
Enhancing Public Research on Citizen Data: An Empirical Investigation of Data Synthesis using Statistics New Zealand’s Integrated Data Infrastructure
01/01/2024
The Impact of Synthetic Data Generation Techniques in IDI Research
02/07/2023
Data-Centric AI to Improve Early Detection of Mental Illness
24/03/2023
Data-Centric AI to Improve Churn Prediction with Synthetic Data
06/02/2023
Ensemble k-Nearest Neighbors based on Centroid Displacement
24/11/2022
Implementation and Analysis of Centroid Displacement-Based k-Nearest Neighbors