I am a Research Associate in Data Analytics within the STEM unit at the University of South Australia (UniSA). I received my PhD in Data Science from UniSA in 2021. My research interests span methodological advances in machine learning as well as applied AI in high-impact domains.

My recent research focuses on three main areas:
- Remote Sensing and Earth Observation: Development of onboard AI for early fire-smoke detection using hyperspectral satellite imagery. My work addresses the challenges of lightweight, energy-efficient model deployment on constrained satellite platforms, with applications to upcoming missions. More broadly, my research contributes to advancing AI for Earth observation tasks, including emulation studies, efficient onboard processing, and robust smoke localization.
- Biomedical Applications: Predictive modeling of epileptic seizures using intracranial EEG and scalp EEG data. My work explores both deep learning and signal-processing-based approaches, including channel coherence analysis and time-series modeling, to improve accuracy, robustness, and clinical interpretability. This research contributes to the broader field of AI for healthcare, with implications for personalized medicine and neurological disorder management.
- Anomaly Detection: Development of novel frameworks that integrate dependency, proximity, and probabilistic modeling for effective detection of rare and abnormal events. My contributions include general frameworks, benchmarking methodologies, and algorithms such as LogDP and LoPAD, which advance both the theoretical foundation and practical applications of anomaly detection across domains.
Alongside my academic research, I bring more than 20 years of experience across academia and industry. Before joining UniSA, I spent over a decade as a software engineer and project manager at Huawei Technologies, contributing to more than 26 international patents in wireless communication. I also have extensive expertise in large-scale software development (Python, R, C, and C++) and project management, leading teams ranging from small groups to projects with over a thousand members.