معرفی
Daniel Jerison is an Assistant Professor in the Department of Mathematics and Statistics at the University of San Francisco, where he supports undergraduate programs in mathematics and data science. He holds a PhD in Mathematics from Stanford University (2016) and a BA in Mathematics from Harvard University (2007).
His educational background includes:
- PhD in Mathematics, Stanford University, 2016
- BA in Mathematics, Harvard University, 2007
Professor Jerison specializes in discrete probability theory, with research focusing on circle packing and discrete complex analysis, abelian sandpile and rotor-router models, and Markov chain convergence and mixing times. His work bridges theoretical mathematics with applications in statistical physics and computer science. His research demonstrates a consistent trajectory toward understanding the properties of random objects and stochastic processes, particularly in discrete settings where traditional continuous methods face challenges.
His scholarly contributions include publications in prestigious journals such as Advances in Mathematics, Communications in Mathematical Physics, and Transactions of the American Mathematical Society, reflecting his significant contributions to the field of probability theory.
Professor Jerison has been actively involved in teaching a wide range of mathematics courses including probability theory, stochastic processes, complex analysis, and linear algebra. He has also contributed to mathematics education through involvement with PROMYS and SUMaC, summer programs for high school students, where he directed research labs and served on admission committees.
His academic journey includes postdoctoral positions at Cornell University working with Lionel Levine and at Tel Aviv University under Asaf Nachmias, establishing him within a strong network of researchers in probability theory and discrete mathematics.
