Daniel Boley

Dr. Daniel Boley serves as Professor of Computer Science and Engineering at the University of Minnesota, where he specializes in matrix computation methods, data mining, and machine learning algorithms. Through his Coursera course "Matrix Methods," which has enrolled over 12,900 students, he helps learners understand fundamental matrix operations, linear equations, orthogonality, and singular value decomposition. His research contributions include pioneering work in principal direction divisive partitioning, document categorization, and clustering algorithms. His expertise spans mathematical computing, control systems, and data analysis, with significant publications in prestigious journals including IEEE Transactions and SIAM Journal on Optimization. His course combines theoretical foundations with practical applications, particularly focusing on matrix methods' applications in machine learning and data analysis. The course includes optional Python examples to help students experiment with algorithms while maintaining mathematical rigor