Boyan Kostadinov

Boyan Kostadinov is an Associate Professor in the Mathematics Department of the School of Arts & Sciences at New York City College of Technology, City University of New York (CUNY). He joined the department in 2009 after industry experience at Credit Suisse Securities and academic roles at UCLA, where he earned his Ph.D. in Mathematics in 2005.

His educational background includes:

• Ph.D. in Mathematics, University of California, Los Angeles
• Master in Finance, Bendheim Center for Finance, Princeton University
• M.A. in Mathematics, University of California, Los Angeles
• M.S. in Physics, Sofia University

Professor Kostadinov specializes in computational thinking and data science applications across STEM education, with emphasis on creating interactive visualizations for mathematics and physics concepts. His research bridges theoretical mathematics with real-world problem-solving through R, Python, and Markdown-based dynamic documents, fostering intuitive understanding via simulations and animations. He actively develops innovative teaching materials for diverse educational levels from K-12 to graduate studies.

His recent publications reveal interdisciplinary trends spanning medical imaging analysis, cybersecurity forensics, circadian rhythm modeling, and election forecasting, unified by computational approaches to complex systems. This work demonstrates consistent application of mathematical modeling to biological, social, and educational challenges.

His scientific recognition includes:

• Robert Sorgenfrey Distinguished Teaching Award (UCLA)

Professor Kostadinov has mentored over 40 undergraduate researchers whose work has been presented at national conferences. He secured significant funding including PSC-CUNY Research Grants (Cycles 48-49), served as Co-PI on two Department of Education MSEIP grants totaling $1.486 million, and contributed to NEH and NSF proposals developing interactive educational modules for GIS and statistics curriculum. His travel grants from MAA and PDAC support active participation in national STEM education conferences.

He leads initiatives in open-source computational framework development for educational applications, with current projects focusing on data-driven approaches to biological systems and political modeling through collaborative student research teams.