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Geoffrey Bonias

Edmonton, Alberta, Canada +1-780-***-**** ad4o5k@r.postjobfree.com

linkedin.com/in/geoffrey-bonias/ github.com/Geoffrey-42/ Driving License 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. I am open to relocation. CORE SKILLS & INTERESTS

Hard: 1) Mathematics, Data Science and Statistics + Computer Science (Master degrees) 2) Machine Learning, Deep Learning, Neural Networks, Random Forests & XGBoost (Certified) 3) Tools: Python, Tensorflow, Keras, Scikit-learn, Numpy, Pandas, Matlab, R, etc 4) Time Series Analysis and Forecasting, Video Event Detection (Motion), Image Segmentation 5) Language Models, Natural Language Processing (LSTM, BERT, Transformers) 6) Clustering algorithms, Anomaly detection, Dimensionality Reduction 7) Pipelines, Data processing, Cloud computing, Prototyping and Deployment 8) Reinforcement Learning, Recommender Systems

Soft: 1) Autonomy, Proactivity. 2) Collaborative, Communication of results. 3) Innovative, Continuous Learning Interests: Appreciates nature and the Rocky Mountains in Banff National Park. Enjoys hiking, skiing, bouldering, kickboxing and drinking espressos or tea while reading a good book. EXPERIENCE

Apziva Remote

AI Resident May 2023 – March 2024

● 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.

● Performed automatic image classification and video event detection leveraging transfer learning with CNN architectures, also designed a light custom CNN architecture and prototyped the model 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. PROJECTS

Ongoing Project January 2024 – March 2024

● Developing advanced deep fake audio detection using Temporal Convolutional Networks (TCN) and integrating a voice cloning system for model training. Project 1 October 2023 – December 2023

● Engineered a trading recommender system leveraging diverse time series forecasting techniques including fbprophet and ARIMA, implemented a custom LSTM model for precise stock price predictions. Page 2 / 2

Project 2 August 2023 – September 2023

● Image classification task using pre-trained Convolutional Neural Network (CNN) architectures including VGG16, MobileNetV2, ResNet50. Designed a custom lightweight CNN architecture for efficient inference.

● Prototyped the custom model, resulting in a user-friendly interface accessible through a web browser. Project 3 June 2023 – July 2023

● Built a recommender system streamlining hiring processes through a pipeline using Natural Language Processing (NLP) libraries and the SBERT (Sentence-BERT) transformer-based sentence embedding technique to perform semantic comparison for automated candidate screening and ranking. Project 4 May 2023 – June 2023

● Improved marketing success rates and personalized communication using XGBoost on customer data. Project 5 May 2023

● Conducted sentiment analysis on customer reviews, extracting key factors influencing satisfaction. Project U October 2022 – January 2023

● Implemented a research paper’s for the automatic segmentation of superalloy microscopy images. EDUCATION

University of Alberta (3.9 GPA) Edmonton, Alberta, Canada Machine Learning, 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 (Top French “Grande Ecole”) Nancy, France Mathematics, Computer Science (Master of Science and Executive Engineering) September 2015 – August 2019

● Established a solid proficiency in Mathematics, with a focus on Statistics, Data Science, Linear Algebra, and Computer Science, with applications in Physics. Proficient in Python Programming, skilled in Matlab and R.

● Valedictorian in Inferential Statistics and Descriptive Statistics. CERTIFICATIONS

Machine Learning Engineer for Production (MLOps) Remote Deep Learning AI, Stanford University March 2024

Reinforcement Learning Specialization Remote

University of Alberta, Amii February 2024

Deep Learning Specialization Remote

Deep Learning AI, Stanford University September 2023 Natural Language Processing Specialization Remote

Deep Learning AI, Stanford University August 2023

Machine Learning Specialization Remote

Deep Learning AI, Stanford University June 2023

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