Moe Amanzadeh (BEng, MEng, MPhil, PhD.C., Prof)DATA SCIENTIST AND EXPLORISTMoe Amanzadeh is a seasoned data science manager and leader in the field of analytics, data science, and machine learning. With over 15 years of experience in delivering high-value software and analytical solutions to the industry, Moe is recognized for his expertise in the use of statistical modeling, machine learning, and artificial intelligence to develop predictive, optimization, and decision-making models and tools. As a pioneer in AI applications, Moe built high-performing teams and has led innovative digital solutions that have improved safety, productivity, and reduced maintenance and operational costs. He holds a Bachelor of Engineering in Electrical Engineering and has an in-depth understanding of sensing and automation solutions. Moe further honed his skills in the application of advanced analytics in the mining industry while earning his Master of Electrical and Master of Mining Engineering, where he conducted extensive research on machine learning algorithms for gas sensing and rapid step change mining technologies. Moe is finishing his Ph.D. at The University of Queensland in the field of AI applications in mechanical and mining engineering. Through his Ph.D. research, he has developed cutting-edge robotic algorithms that use statistical and machine learning methods to increase drilling accuracy and reduce mine-to-mill costs in underground mines. As a project leader and data scientist at Mining3 / CRCMining, Moe revolutionized the use of machine learning and AI methods in combination with distributed sensing. He worked with leading mining companies, including Anglo American, Hope Downs Group, Rio Tinto, and Vale, and original equipment manufacturers, such as Caterpillar, Sandvik, Joy Global, Optasense, Luna Inc, and Scott's Automation. This collaboration resulted in two patents, a successful commercial product, and two software products. In addition to his work in the mining industry, Moe has also contributed to AI projects in other fields, including cyber security, roadway maintenance, marketing, and medicine. Moe's work and development projects have been published in international journals and have been presented at keynotes and invited talks at prestigious conferences worldwide, including ICRA and CLEO. He is well-equipped to work on complex problems in technical and multi-disciplinary teams, thanks to his extensive industry experience. In the recent years, he has deve Education:
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Areas of Interest: data science, data engineering, artificial intelligence, algorithms and sensors, machine learning, deep learning, mining technology, business improvement, robotics and control systems, fiber optic sensors, 3D guiding of drilling and surgical systems, optics simulation, IIOT, gas sensing and spectroscopy, .... |