Aline Talhouk

Background

About Aline Talhouk

I work at the intersection of health data science, machine learning, and women’s health. My focus is on developing practical, responsible applications of AI in clinical and research settings, with an emphasis on collaborative science, data ethics, and translational outcomes. At UBC and OVCARE, I lead and contribute to several projects involving AI in gynecologic oncology, federated data systems, and digital infrastructure. Much of my work involves close collaboration across institutions, from designing governance frameworks to co-developing data-driven tools with clinicians, scientists, and patient partners. I also teach machine learning for health science trainees and mentor research staff and students. Recently, I’ve been involved in projects using foundational models in microbiome NLP, ultrasound imaging, and literature synthesis in oncology. I’m motivated by questions that matter to patients, the complexity of working with real-world health data, and the opportunity to make research infrastructure more open, ethical, and useful.