Dr. Mostafa Reisi is an Assistant Professor in the Department of Industrial Engineering at the University of Florida. He received his PhD in industrial and systems engineering from Georgia Institute of Technology and M.Sc. degrees in transportation engineering and applied mathematics from the Southern Illinois University Edwardsville. His research interests focus on developing efficient methodologies and algorithms for modeling and monitoring systems with high-dimensional or network data in precision agriculture, manufacturing, healthcare, and transportation systems. He is also interested in adaptive sampling and multi-accuracy data fusion.
In this podcast episode, Dr. Reisi discusses his journey in the field of operations research, particularly focusing on high-dimensional data and machine learning. He elaborates on his work with tensor data for modeling and monitoring high-dimensional systems, emphasizing applications in healthcare and manufacturing. Dr. Reisi explains the concept and advantages of tensor regression, federated learning for data privacy, and robust models to handle outliers. He also shares valuable advice for graduate students, highlighting the importance of self-teaching and finding good mentors.
Podden och tillhörande omslagsbild på den här sidan tillhör Clemson University INFORMS Student Chapter. Innehållet i podden är skapat av Clemson University INFORMS Student Chapter och inte av, eller tillsammans med, Poddtoppen.
