Professional Work
Passionate about building scalable AI/ML systems to solve practical problems, with a special interest in recommender systems, search, and ranking applications.
Experience
Staff Machine Learning Engineer | Shopify, Canada | 2023–present
- Building foundation models for commerce and personalized recommendations.
Senior Data Scientist | Shopify, Canada | 2021–2023
- Led Shop app personalized recommendations retrieval and ranking.
Applied Scientist | Amazon, Canada | 2018–2021
- Enhanced Alexa’s natural language understanding through novel deep learning methods for entity resolution.
Senior Data Scientist | Canopy Labs, Canada | 2017–2018
Data Scientist | Canopy Labs, Canada | 2015–2017
- Built recommender systems and propensity models driving revenue growth for retail and travel clients.
Research & Teaching Assistant | York University, Canada | 2013–2015
- Designed reinforcement learning solutions for optimizing user interactions in configuration processes.
Research Assistant | Institute of Cybernetics, Mathematics and Physics, Cuba | 2011–2013
- Developed statistical modeling packages for optimization algorithms based on copulas and vines.
Education
Master’s degree, Information Systems & Technology | York University, Canada | 2013–2015
Data Science Specialization | Johns Hopkins University through Coursera | 2014–2015
Bachelor’s degree, Computer Science | University of Havana, Cuba | 2006–2011
Patents
- Entity Resolution Using Acoustic Data, U.S. Patent No. US11817090B1. Work done at Amazon; filed December 2019, granted November 2023.
Publications
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Y. Gonzalez-Fernandez, S. Hamidi, S. Chen, S. Liaskos. (2019). Efficient Elicitation of Software Configurations Using Crowd Preferences and Domain Knowledge. Automated Software Engineering, 26(1), 87–123.
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Y. Gonzalez-Fernandez, S. Chen. (2015). Leaders and Followers – A New Metaheuristic to Avoid the Bias of Accumulated Information. In IEEE Congress on Evolutionary Computation, 776–783. IEEE.
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Y. Gonzalez-Fernandez, S. Chen. (2014). Identifying and Exploiting the Scale of a Search Space in Particle Swarm Optimization. In Conference on Genetic and Evolutionary Computation, 17–24. ACM.
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Y. Gonzalez-Fernandez, M. Soto. (2014). copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas. Journal of Statistical Software, 58(9), 1–34.