Saeed Damadi

Saeed Damadi is pursuing his PhD in sparse optimization and machine learning at the Department of Mathematics and Statistics, University of Maryland, Baltimore County (UMBC). Under the mentorship of Professor Jinglai Shen, his work focuses on advanced mathematical methods for sparse optimization.

During his PhD, he earned two master's degrees to deepen his knowledge of statistics and machine learning. He completed a master's degree at the Department of Computer Science and Electrical Engineering at UMBC, guided by Professor Hamed Pirsiavash, where he worked on compression of deep neural networks. This topic led to his PhD research where he appreciated the advantages of the theory of sparse optimization for building smaller AI models. Due to the need for understanding statistics as the bedrock of artificial intelligence and machine learning, he earned a master's degree in statistics to deepen his knowledge in this area.

He has two main research goals. First, he aims to compress neural networks to better understand how the brain works. Second, he is passionate about advancing quantitative trading through sophisticated deep neural networks and machine learning models.

In addition to his diverse interests in different sciences, he got his first master's degree in control from the Amirkabir University, Tehran, Iran. Saeed has also been a lecturer at UMBC and part time adjunct faculty at Towson University.