Jonathan Hanke is a distinguished mathematician currently serving as a Visiting Lecturer at Princeton University, where he leverages his expertise in AI and Data Science to inspire the next generation of thinkers. His specialization in Stochastic Portfolio Theory and Number Theory positions him uniquely at...
Jonathan Hanke is a distinguished mathematician currently serving as a Visiting Lecturer at Princeton University, where he leverages his expertise in AI and Data Science to inspire the next generation of thinkers. His specialization in Stochastic Portfolio Theory and Number Theory positions him uniquely at the intersection of mathematics and finance, particularly in developing innovative portfolio strategies for equity markets. Jonathan's research interests also delve into the arithmetic of quadratic forms and automorphic forms, where he employs advanced computational techniques to tackle complex mathematical problems.
In his role at Princeton, Jonathan has designed and taught an engaging Freshman Seminar titled "Secrecy, Search, and Society" (FRS185). This course introduces students to the often-overlooked yet critical influence of mathematics and algorithms in contemporary society, fostering a deeper understanding of how these elements shape various aspects of daily life. Currently, he is teaching "Research Projects in Data Science" (SML312), a course that provides students with hands-on experience in data analysis and algorithm development. This course emphasizes practical applications of mathematical modeling and equips students with the skills necessary to navigate the rapidly evolving landscape of data science.
With extensive experience in teaching and mentoring, Jonathan is dedicated to cultivating a collaborative learning environment where students can explore the intricacies of algorithms and quantitative finance. His proficiency in programming languages such as Python and C++ enhances his ability to guide students in implementing effective solutions to real-world problems. Jonathan Hanke's commitment to education and research not only enriches the academic community at Princeton but also contributes significantly to the broader fields of mathematics and data science.
