Welcome to Stephen DeSalvo's home page!
I am currently a quantitative developer at Praedicat in the modeling team. The technological aspects are what really got me excited to explore this opportunity, and I found the people involved to be quite exceptional and inspiring. This is a video I made for the launch of the new website design which describes part of the modeling team's activities. Below you will find my research interests and papers, many of which are still under review by refereed journals. Please feel free to reach out if you have any questions or comments with respect to these topics! Update 4222018: The paper Limit shapes via Bijections (with Igor Pak) has been accepted to the journal Combinatorics, Probability & Computing! Update 1262017: The paper The probability of avoiding consecutive patterns in the Mallows distribution (with Harry Crane and Sergi Elizalde) has been accepted to the journal Random Structures & Algorithms! Summary: my research is primarily in the subject of combinatorial probability, and I have an extensive background in applied and computational mathematics with emphasis in industrial problems. I taught a yearlong introduction to programming course at UCLA which covered C++11/14 (C++17 wasn't published at the time) as well as Qt. I am currently programming in Python with big data (cliche, yes, but in this case it is true), and making GUIs with PyQt. Research interests (see published papers below):
Postdoc at the University of California Los Angeles from 2012 to 2017, worked closely with Igor Pak and Georg Menz. PhD in applied mathematics at the University of Southern California in 2012 under the direction of Richard Arratia. Master's degree in statistics at the University of Southern California in 2009. I worked with Fadil Santosa as an undergraduate student in conjunction with the Minnesota Supercomputing Institute and an REU at the University of Minnesota. Papers Submitted
2018+
