profile

Tran Duc Quynh is an established academic lecturer and senior researcher currently based at the International School of Vietnam National University (VNU) in Hanoi. Throughout her career, she has successfully bridged advanced mathematical theory with practical computational applications, specializing in optimization models, machine learning architectures, and quantitative methods applied to business, finance, and logistics.

Her academic journey is rooted in a strong foundation in mathematics, beginning with a Bachelor’s degree in Mathematics in 2003 and followed by a Master’s degree in Calculus in 2006, both earned from the Hanoi National University of Education. She then expanded her academic horizon internationally, completing her Ph.D. in Informatics in 2011 at the University of Lorraine (formerly known as Paul Verlaine University of Metz) in France.

Today, Dr. Tran Duc Quynh balances active scientific research with a dedicated teaching career. She instructs advanced quantitative courses across both technical and management curricula, covering core subjects such as Artificial Intelligence, Machine Learning, Optimization, and Operations Research. On the business side, she teaches Business Analytics, Quantitative Approaches for Business, and Financial Mathematics, with a specific focus on portfolio selection and management models.

Her research output is well-published and focuses on solving complex allocation, predictive analysis, and logistical bottleneck problems. She frequently utilizes DC (Difference of Convex functions) programming and modern data science models to address these challenges. Her notable co-authored works include advanced studies on forecasting stock market trends using LSTM architectures, applying machine learning to predict customer behavior, and developing optimization algorithms for supply chain management and multi-stage production systems.