Geoffrey Bonias
Machine Learning Engineer
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About
As an engineer with a diverse background, I am driven by a strong foundation in machine learning algorithms, mathematics, programming skills, and a passion for continuous learning, seeking to contribute to innovative projects and make a meaningful impact in the field.
Experience
Apziva Remote
AI Resident May 2023 – December 2023
● Developing a voice cloning and deep fake audio detection machine learning system.
● Implemented time series forecasting tools and developed a custom LSTM model for stock price prediction.
● Utilized computer vision through transfer learning, designed a custom CNN architecture for image classification, and prototyped a user interface with Gradio.
● Built a Natural Language Processing pipeline using Large Language Models (LLM) for semantic comparison.
● Optimized Random Forests, XGBoost, and Neural Networks for practical tasks.
University of Alberta Edmonton, Alberta, Canada
Research Assistant October 2022 – January 2023
● Engaged in substantial research, proactively staying current with field literature. Applied systematic synthesis of information for effective problem-solving. Documented and presented results with clarity and conciseness.
Education
University of Alberta (3.9 GPA) Edmonton, Alberta, Canada
Major in Materials Engineering (Master of Science) September 2019 – October 2022
● Modeled and optimized a metal Additive Manufacturing process as a Graduate Research Assistant.
● Presented MSc work at the 16th MCWASP International Conference and published a conference paper.
● Applied Machine Learning to an image segmentation task for superalloy microscopy images.
Mines Nancy Nancy, France
Top French “Grande Ecole” (Master of Science and Executive Engineering) September 2015 – August 2019
● Established a solid proficiency in Mathematics, with a focus on Linear Algebra, Statistics, and Data Science, with applications in Physics. Proficient in Python Programming, as well as skilled in utilizing Matlab and R.
● Valedictorian in Inferential Statistics and Descriptive Statistics.
