Lachlan Teale is a Machine Learning Engineer who works with large multi-national companies to optimise and improve their worflows through the use of digital twins or preventative maintenance systems, believing technology can aid human employees better analyse, interpret and utilise large amounts of data in making effecient decisions.
Lachlan has secured contracts and worked with clients on a global scale to achieve solutions, with his unique skillset combining both complex business and technological knowledge. These companies have ranged from telecommunications to mining and resources.
Lachlan is also studying a Bachelors of Business Management in Marketing and International Business from the University of Queensland, Australia.
Algorithmic trading framework utilising Serverless and AWS, Statistical analysis and Machine Learning. Written in Python for the backend, React.js for the frontend. Aiming to produce income by removing the need for involvement in investment portfolio management.
Only 0.2% of all mining data being utilised for decision-making onsite. Data is independent, with no correlations between datasets and significant information traffic. Dugg applies real-time data analysis to identify problems and provide accurate information of their cause. By correlating data, Dugg optimises onsite dispatching, allowing for quick and informed decision making.
Achieved second place at Unearthed Hackathon Brisbane 2018. Later aquired and inorporated into PETRA Data Science.