Christopher Aicher

Christopher Aicher's work experience includes a role as a Quantitative Researcher at Citadel Securities beginning in 2020. Prior to that, they worked as a Research Assistant at the University of Washington from 2015 to 2020, where they collaborated on developing scalable approximate inference procedures for sequential data models. Christopher also served as a Graduate Teaching Assistant for a brief period in 2014. In 2017, Christopher worked as a Research Intern at Microsoft AI & Research, focusing on short-form text clustering. Christopher presented their work at an internal conference. In 2016, they were a Research Scientist Intern at Amazon, working on forecasting sales of Kindle devices. Christopher also evaluated different time-series models to improve short-term distribution forecasting. Christopher also gained experience as a Research Intern at Dato in 2015 and as an Undergraduate Research Assistant at the University of Colorado from 2012 to 2014, where they worked on statistical inference in networks and developed a novel weighted version of the stochastic blockmodel. Christopher also worked as a Learning Assistant during that time. Additionally, they served as a REU Student at the Santa Fe Institute in 2013.

Christopher Aicher earned their Bachelor's degree in Applied Mathematics with a minor in Computer Science from the University of Colorado Boulder between 2010 and 2014. Later, they pursued a Master's degree in Applied Mathematics from the same institution during the same time period. Afterward, they went on to the University of Washington, where they obtained their Doctor of Philosophy (Ph.D.) in Statistics between 2014 and 2020.