Joshua Kerrigan
About Joshua Kerrigan
Joshua Kerrigan is a Senior Data Scientist at FreeWheel, specializing in data analysis and machine learning. He holds a Ph.D. in Physics/Astrophysics from Brown University and has extensive experience in research and academia.
Work at FreeWheel
Joshua Kerrigan has been employed at FreeWheel as a Senior Data Scientist since 2020. In this role, he focuses on data-driven solutions to optimize advertising strategies. His work involves the design and implementation of algorithms that enhance ad inventory delivery and revenue balance. Kerrigan's expertise in data science contributes to the company's efforts in improving advertising efficiency and effectiveness.
Education and Expertise
Joshua Kerrigan holds a Doctor of Philosophy (Ph.D.) in Physics/Astrophysics from Brown University, which he completed from 2014 to 2019. He also earned a Master’s Degree in Physics from Brown University between 2014 and 2016, and a Bachelor's Degree in Physics from the University of Massachusetts Amherst from 2011 to 2014. His academic background provides a strong foundation for his work in data science and machine learning.
Background
Before joining FreeWheel, Joshua Kerrigan held various research positions. He was a PhD Candidate at Brown University's Pober Lab from 2016 to 2019 and served as a Postdoctoral Researcher for two months in 2019. He also worked as an Associate AI/ML Researcher at RAND Corporation from 2019 to 2020. Earlier in his career, he was an Undergraduate Researcher at the University of Massachusetts Amherst from 2013 to 2014 and a Squad Leader in the US Army from 2006 to 2011.
Research and Projects
Kerrigan has contributed to various research projects throughout his career. He designed a Monte Carlo market/exchange simulation to optimize ad inventory delivery. He has also developed a U-Net based model for identifying radio frequency interference in radio interferometry data. Additionally, he created a hybrid language model that combines BERT with linguistic scoring to analyze conspiracy theories on social media. His work often explores the implementation of Reinforcement Learning algorithms.
Technical Focus
Joshua Kerrigan's technical focus includes the challenge of domain adaptation, particularly in transitioning from simulated environments to real-world applications. He explores advanced machine learning techniques, including Reinforcement Learning algorithms such as A2C, A3C, and DQN. His expertise in these areas supports his contributions to data science and machine learning initiatives at FreeWheel.