Kevin Gullikson
About Kevin Gullikson
Kevin Gullikson is a Staff Data Scientist at SparkCognition and a Graduate Student at the University of Texas at Austin, with a strong background in open source code development and advanced statistical methods. He has contributed significantly to the scientific community, notably through his work on modeling telluric absorption features and his participation in the SciPy conference.
Work at SparkCognition
Kevin Gullikson has been employed at SparkCognition since 2016, where he currently holds the position of Staff Data Scientist. Over his tenure of eight years, he has contributed to various projects focusing on data science applications. His work involves leveraging advanced statistical methods to enhance data-driven decision-making processes within the organization.
Education and Expertise
Kevin Gullikson earned a Bachelor of Science in Physics from the Illinois Institute of Technology, where he studied from 2006 to 2010. He furthered his education at The University of Texas at Austin, obtaining a Doctor of Philosophy in Astronomy and Astrophysics from 2010 to 2016. His academic background equips him with expertise in advanced statistical methods, including Bayesian inference techniques and classification and clustering methods.
Background
Kevin Gullikson has a strong foundation in open source code development and publication, contributing significantly to the scientific community. He developed an open source code to model telluric absorption features from Earth's atmosphere, which aids in improving the accuracy of astronomical observations. Additionally, he has been a Graduate Student at the University of Texas at Austin since 2010.
Achievements
Kevin delivered a talk at the SciPy conference, where he showcased his expertise in scientific computing and data analysis. His contributions to the field include the development of open source tools that benefit both the scientific community and data science practices.
Personal Projects and Contributions
In addition to his professional work, Kevin maintains a personal blog where he applies his data modeling and statistical knowledge to various topics beyond astronomy. This platform allows him to share insights and engage with a broader audience interested in data science and its applications.