Highly adaptable Machine Learning Engineer and Computational Biologist with an advanced background in generative AI and synthetic data. Proven ability to translate complex scientific problems into practical, cross-disciplinary solutions, evidenced by leadership in a healthcare AI startup and pioneering doctoral research. Drives innovation at the intersection of machine learning and biological sciences, delivering high-impact technical solutions.
Founder
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Summary
Spearheaded a healthcare generative AI startup, leveraging deep expertise in GANs to develop innovative synthetic data solutions.
Highlights
Launched a healthcare generative AI startup, leveraging expertise developed during doctoral research to address critical data privacy and accessibility challenges.
Conducted in-depth market research to validate demand for synthetic data solutions in the healthcare sector, identifying key product-market fit opportunities.
Managed all aspects of startup operations, including product strategy, technical development, and early-stage business development initiatives.
Applied advanced machine learning techniques to create privacy-preserving synthetic data, demonstrating potential for secure data sharing and research acceleration.
Doctoral Researcher
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Summary
Conducted pioneering research on Generative Adversarial Networks (GANs) for privacy-preserving healthcare data synthesis as an MSCA-ITN fellow.
Highlights
Awarded the highly competitive MSCA-ITN Early-stage Researcher fellowship, fostering collaborative research between academia and industry stakeholders.
Pioneered research into Generative Adversarial Networks (GANs) for privacy-preserving healthcare data synthesis, resulting in a foundational literature review and novel methodological contributions.
Executed a specialized secondment program, conducting cutting-edge research on the application of generative machine learning and GANs within complex healthcare datasets.
Authored and co-authored multiple peer-reviewed publications on synthetic data and machine learning in computational biology, advancing scientific knowledge.
Research Project Supervisor
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Summary
Directed and mentored an MSc student on a research project focused on database performance and data analysis in observational health data.
Highlights
Supervised and mentored an MSc student through a comprehensive research project, optimizing database performance and analytical queries for observational health data.
Provided expert technical guidance in Python-based data analysis and robust database management, ensuring project success and student skill development.
Cultivated critical thinking, problem-solving, and advanced research skills within a real-world data science project, enhancing student capabilities for complex challenges.
Visiting Researcher
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Summary
Conducted specialized research at a leading institution, focusing on advanced data science methodologies and their applications.
Highlights
Contributed to cutting-edge data science research initiatives, applying advanced analytical techniques to complex datasets.
Collaborated with senior researchers on projects involving machine learning algorithms and data modeling, enhancing project outcomes.
Presented research findings and actively participated in academic discussions, fostering knowledge exchange within the institute.
Lead Teaching Assistant
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Summary
Led and coordinated a team of TAs, enhancing student learning and assessment in Bioinformatics and Java courses.
Highlights
Led and coordinated a team of 5+ Teaching Assistants, ensuring consistent delivery of high-quality instruction and a positive learning experience for over 150 students.
Designed and implemented comprehensive evaluation materials and managed online assessments for core Bioinformatics and Java courses, impacting student learning outcomes.
Provided direct instructional support and mentorship to students, enhancing their understanding of complex programming and biological concepts.
Full-stack Developer
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Summary
Developed a full-stack web platform for proteomics research, enhancing data visualization and researcher collaboration.
Highlights
Collaborated cross-functionally with researchers to architect and develop a robust web platform for complex proteomics research data management.
Transformed complex scientific datasets into intuitive and interactive visualizations using D3.js, significantly improving data interpretability for researchers.
Engineered a responsive and highly efficient web application using Node.js and AngularJS frameworks, enhancing user experience and system performance.
Frontend Developer (Internship)
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Summary
Prototyped and developed a new UI and scalable plugin architecture for an open-source clinical research platform.
Highlights
Prototyped and refined a new user interface (UI) for an open-source clinical research platform, improving data accessibility and user engagement.
Engineered a scalable plugin architecture that enabled advanced statistical analysis functionalities and supported future platform growth.
Constructed an efficient and modular web application utilizing AngularJS, JavaScript, HTML, CSS, and R, improving code maintainability and development velocity.
Bioinformatician (Internship)
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Summary
Adapted a protein identification algorithm and performed data analysis to support genetics research.
Highlights
Adapted and optimized a protein identification algorithm from scientific literature for specific application in Drosophila melanogaster research, enhancing data processing efficiency.
Executed comprehensive data analysis and manipulation using Python, generating critical insights that directly supported genetics research objectives.
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MSc
Computer Science
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BSc
Bioinformatics
Awarded By
Marie Skłodowska-Curie Actions, EU
Awarded a prestigious fellowship supporting doctoral research in advanced machine learning and computational biology.
Awarded By
Genome Canada
Secured funding for MSc research project on machine learning and population genetics within the BIOSAFE initiative.
Published by
arXiv
Summary
Explored the potential of Generative Adversarial Networks (GANs) for generating synthetic observational health data, discussing its implications for medical research and digital twin technologies.
Published by
Authorea Preprints
Summary
Conducted a comprehensive benchmarking study on large-scale observational health data, evaluating performance and efficiency of various analytical approaches.
Published by
Bioinformatics
Summary
Developed a novel method for genotype assignment using phylogenetic networks, published in Bioinformatics, demonstrating advancements in computational biology.
Published by
McGill University
Summary
Presented research on machine learning methodologies applied to genotype assignment, contributing to the field of population genetics.
Published by
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Summary
Authored a paper on the complexities of sentiment analysis, presented at a major computational linguistics conference, highlighting challenges and advancements in the field.
Issued By
Coursera
Issued By
Coursera
Machine Learning, Deep Learning, Generative AI, GANs, NLP, Data Analysis, Data Visualization, Scientific Research.
Python, R, TensorFlow, PyTorch, HTML, CSS, JavaScript (JS), Node.js, AngularJS, D3.js, Databases.
Computational Biology, Bioinformatics, Phylogenetics, Population Genetics.
Technical Writing, Teaching, Mentoring, Problem-Solving, Strategic Planning, Project Management, Cross-functional Collaboration.
Web Development, Full-stack Development, Frontend Development.
Reading, Learning, Arts and Music, Climbing, Cycling, Running, Gaming, Board Games, Traveling.
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Summary
Contributed to updating the website for 'Cours ta réussite', a non-profit organization, enhancing their online presence and user engagement.
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Summary
A technical blog on machine learning research and applications, serving as a platform for knowledge sharing and thought leadership.
