Loc Tran

Senior Algorithm Researcher @ SOPHiA GENETICS

About Loc Tran

Loc Tran is a Senior Algorithm Researcher at SOPHiA GENETICS in Vaud, Switzerland, where he has worked since 2021. He has a strong background in applied mathematics and machine learning, with previous roles at CHUV and EPFL.

Work at SOPHiA GENETICS

Loc Tran has been employed at SOPHiA GENETICS as a Senior Algorithm Researcher since 2021. In this role, he contributes to the development of algorithms that enhance the capabilities of genomic data analysis. His work focuses on integrating machine learning techniques with mathematical analysis to improve the accuracy and efficiency of data interpretation in the field of genetics.

Previous Experience in Computational Cancer Biology

Prior to his current position, Loc Tran worked at CHUV | Lausanne University Hospital as a Postdoctoral Researcher in the Laboratory of Computational Cancer Biology from 2020 to 2021. His responsibilities included conducting research that applied computational methods to cancer biology, contributing to advancements in personalized medicine. He also served as a Research Collaborator in the same hospital's Laboratory of Analytical Personalized Oncology for six months in 2020.

Educational Background

Loc Tran holds a PhD in Applied Mathematics from École Polytechnique Fédérale de Lausanne (EPFL), where he studied from 2014 to 2018. He also earned a Master’s Degree in Applied Mathematics from Université d'Orléans in 2014. His undergraduate studies were completed at VNUHCM - University of Science, where he obtained a Bachelor’s degree in Mathematics and Computer Science from 2009 to 2013.

Research Focus and Interests

Loc Tran has a background that integrates mathematical analysis, statistical methods, and computer science. He has a keen interest in machine learning, which he applies to various educational disciplines. His research emphasizes the integration of machine learning with mathematical analysis and statistical methods, aiming to enhance data-driven decision-making in scientific research.

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