I recently graduated from the Master of Computer Science program at Concordia University, Montreal, Canada. My research focus was on semantic text search (kNN with sentence embeddings) and deep learning NLP models (Seq2Seq LSTMs, Transformer). I applied these models to the "English-to-code" task, which consists of finding or generating code snippets that are relevant to a given problem, formulated in natural language.I have also worked previously as a software engineer on music generation with deep learning. Specifically I worked on combining rules with the outputs of neural networks to produce coordinated instrument parts for different musical styles. Before that I have done some data mining and web development. I'm passionate about software engineering and machine learning engineering, implementing ML and DL models in production, preparing data pipelines, extracting features, and testing different models on a new project or task. I also like to stay up-to-date on the latest ML and DL research and I like to try new open source codebases to see how they work. Recently, I've been interested in measuring generalization in deep learning models; I'm also interested in knowledge graphs and how they can be combined with deep learning to solve hard NLP tasks. I'm also very interested in non-gradient-based, evolutionary algorithms for training neural networks; I believe I have a few insights on the inner workings of GAs and I have some experiments I've been wanting to run. If anyone is working on this, please contact me. Don't hesitate to message me if you have any questions, or want a copy of my full CV.