Proposed and built machine learning solutions for fault detection and condition monitoring in diverse systems at AGL's power stations. Contributed to cost savings exceeding $6M.

- Worked on machine learning systems for robust performance in uncertain and dynamic environments.- Applied expertise to optimise electricity generation based on fluctuating prices in short intervals.- Specialised in online optimisation, control theory, machine learning, and information theory; - Co-supervised a PhD student exploring gaps in optimization and control.

The responsibilities of an Academic Mentor is to support Engineering/IT students in developing their professional skills, guide students on managing and making the most of their experiences in their workplace, assessing them through reports and presentations.

• Key responsibilities: - Developed fundamental bounds and design methods to estimate signals (time-series data) when distorted by different noises and correlations with partial measurements. Successfully addressed two long-standing (over 70 years) problems in Control Engineering. - Communicated with the principal supervisor, co-supervisors and colleagues regarding schedule changes, plans, and peer reviewers during the publishing process. • Key achievements: - Developed fundamental bounds and design methods to estimate signals (time-series data) when distorted by different noises and correlations with partial measurements. - Solved two long-standing problems in two different areas of Information Theory and Networked Systems.

Taught data modelling, database concepts, and workshops for Signal Processing, Control Systems, Database and Distributed Algorithms.

• Key responsibilities: - Engineered, implemented, and supported data analytics infrastructure and additional components for various data sources. - Sourced, extracted and analysed data from multiple sources, applications, and processes. - Authored technical and non-technical reports based on analysis and presented to a broad range of audiences, including management. - Managed a team of 3 casual employees and led them to be employed permanently.• Key achievements: - Developed informative systems and reporting capabilities for predicting anomalies, deployed on different platforms, leading to automatic report generation, saving time and cost. Achieved a high true-positive rate in anomaly detection, reducing workload on monitoring teams and detecting numerous anomalies. - Initiated and designed Machine Learning and prediction models (supervised and unsupervised) for Anomaly Detection. Achieved a high true-positive rate in anomaly detection, leading to a workload reduction on monitoring teams and numerous anomalies detected. - Achieved strong communication skills by working in a team including more than 30 data analysts, data scientists, control experts, and software developers.

Supervisor of two labs (Control Systems and Electrical Engineering) during which I taught, proposed and designed experiments for the Electrical engineering subjects.

Designed, managed and took exams and projects.