Jeremy Georges-Filteau

jeremygeo@gmail.com | 581-849-1348 | jeremygf.com

Machine Learning Engineer, Computational Biologist

I am a highly adaptable programmer with an advanced background in machine learning and computational biology. I excel at understanding complex problems rapidly and proposing practical solutions that bridge various fields.

Skills

Experience

2021 - 2023 Founder NeoAI Health – Utrecht, Netherlands
  • Launched a healthcare generative AI startup, leveraging expertise developed during my doctoral research.
  • Conducted in-depth market research to assess the potential for synthetic data solutions in the healthcare sector.
2018 - 2021 Doctoral Researcher Radboud University and The Hyve – Nijmegen and Utrecht, Netherlands
  • Collaborated with academia and industry as an MSCA-ITN, Early-stage Researcher fellowship recipient.
  • Explored the innovative use of Generative Adversarial Networks (GANs) for privacy-preserving healthcare data synthesis and authored a foundational literature review on the topic.
Jan - Jul 2020 Research Project Supervisor The Hyve – Utrecht, Netherlands
  • Supervised and mentored an MSc student on a research project exploring database performance and analytical queries within observational health data.
  • Provided technical guidance and support in Python-based data analysis and database management.
  • Fostered critical thinking, problem-solving, and research skills in a real-world data science project.
Jun - Jul 2019 Visiting Researcher Data Science Institute, Imperial College – London, UK
  • Secondment program under MSCA-ITN grant: Conducted focused research on cutting-edge applications of generative machine learning and GANs within the healthcare domain.
2017 - 2018 Lead Teaching Assistant McGill University – Montreal, Canada
  • Coordinated a team of TAs, providing leadership and ensuring a consistent student experience.
  • Developed evaluation materials and managed online assessments for courses in Bioinformatics and Java.
Jan - Aug 2016 Full-stack Developer Institute of integrative biology and systems – Québec City, Canada
  • Collaborated with researchers to create a web platform for proteomics research data.
  • Translated complex scientific data into intuitive visualizations using D3.js.
  • Implemented a responsive and efficient web application using Node.js and AngularJS frameworks.
May - Aug 2015 Frontend Developer (Internship) The Hyve – Utrecht, Netherlands
  • Prototyped a new UI for an open-source clinical research platform, improving data accessibility.
  • Developed a scalable plugin architecture to support advanced statistical analysis functionalities and future growth.
  • Built an efficient and modular web application using AngularJS, JavaScript, HTML, CSS, and R.
Mar 2015 Bioinformatician (Internship) IBMC - Réponse Immunitaire et Développement chez les Insectes – Strasbourg, France
  • Adapted a protein identification algorithm from literature for use with Drosophila melanogaster.
  • Performed data analysis and manipulation in Python to support genetics research.

Projects

2024 - Present ML Readme A technical blog on machine learning research and applications.
2024 Web development I helped the non-profit organization 'Cours ta réussite' update their website.

Certificates

2024 DeepLearning.AI TensorFlow Developer Coursera
2024 TensorFlow: Advanced Techniques Coursera

Education

2016 - 2018 MSc Computer Science McGill University – Montreal, Canada
  • Thesis: Machine learning and population genetics
2012 - 2016 BSc Bioinformatics Université Laval – Québec City, Canada
  • International Profile (Fall 2014 - Winter 2015): Université de Strasbourg - Strasbourg, France

Publications

2020 J. Georges-Filteau and E. Cirillo, Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?, arXiv preprint arXiv:2005.13510
2020 B. Katsma and J. Georges-Filteau, Benchmarking big observational health data, Authorea Preprints
2020 J. Georges-Filteau, R. C. Hamelin, and M. Blanchette, Mycorrhiza: Genotype assignment using phylogenetic networks, Bioinformatics, vol. 36, no. 1, pp. 212–220
2019 J. Georges-Filteau, Machine learning methods for genotype assignment, McGill University
2018 K. Kenyon-Dean et al., Sentiment analysis: It’s complicated!, Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018, pp. 1886–1895

Grants

2018 - 2021 PhD funding, Early-stage Researcher fellowship Marie Skłodowska-Curie Actions, EU
2016 - 2018 MSc funding BIOSAFE project, Genome Canada

Interests

Languages