Hélène Tran is an AI Ph.D. candidate with nine years of hands-on experience building multimodal emotion recognition systems that fuse facial, vocal and textual signals for healthcare applications. She combines strong academic training (ENSIIE, University of Wollongong, University of Clermont Auvergne) with industry research experience—from deep learning for prostate MRI at Guerbet to front-end development of an open-source radiotherapy platform—bringing both model-building and product-minded engineering skills. Skilled in TensorFlow, PyQt, data augmentation and medical image preprocessing, she focuses on socially impactful projects and remote therapeutic education for chronic and mental health patients. Beyond research, she has led student and humanitarian initiatives, taught programming to youths, and organized international student integration efforts, reflecting a rare blend of technical depth and community commitment. Notably, her CIFRE thesis is being developed in partnership with a company and a lab, positioning her work for direct clinical transfer.
9 years of coding experience
1 year of employment as a software developer
Engineering Degree, Software Engineering, Engineering Degree, Software Engineering at ENSIIE
Master of Computer Sciences, Machine Learning and Big Data, Intelligent Systems, Master of Computer Sciences, Machine Learning and Big Data, Intelligent Systems at University of Wollongong
Baccalaureate, Sciences, Very Good distinction, Baccalaureate, Sciences, Very Good distinction at Collège Lycée Epin
Preparatory class for grandes écoles, Mathematics and Physics, Preparatory class for grandes écoles, Mathematics and Physics at CPGE Lycée Paul Valéry
Doctor of Philosophy, Artificial Intelligence, Doctor of Philosophy, Artificial Intelligence at University of Clermont Auvergne
Updated version of MultimodalDNN repository owned by University of Edinburgh Team G25 (first place in ACL 2018 Emotion Recognition Challenge using CMU-MOSEI data).
Contributions:2 PRs, 111 pushes, 5 branches in 11 months
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