Allyson Morgenthal
About Allyson Morgenthal
Allyson Morgenthal is a Data Scientist II at SparkCognition, where she leads projects on anomaly detection for liquefied natural gas systems and manages the offshore contractor data science team. She has a background in neuroscience and computer science, having previously worked in various research and engineering roles.
Current Role at SparkCognition
Allyson Morgenthal currently holds the position of Data Scientist II at SparkCognition, where she has been employed since 2021. In this role, she leads a project focused on anomaly detection for liquefied natural gas (LNG) systems. Additionally, she manages the offshore contractor data science team, overseeing various data science initiatives. Morgenthal is also a member of the culture committee, contributing to the workplace environment and team dynamics.
Previous Experience
Prior to her current role, Morgenthal worked at SparkCognition as a Data Scientist I from 2020 to 2021. She has also gained valuable experience through internships, including a position as an Image Analysis/Machine Learning Intern at Regeneron Pharmaceuticals, Inc. in 2019, and as a Software Engineering Intern at Advanced Scanners from 2018 to 2019. Her early research experience includes roles as an Undergraduate Research Assistant at The University of Texas at Austin's Huth Lab and Drew Lab, as well as a Summer Intern at Bar-Ilan University's Memory Lab.
Education and Expertise
Morgenthal earned her Bachelor's degree in Neuroscience from The University of Texas at Austin, where she studied from 2016 to 2019. She is currently pursuing a Master of Science in Computer Science at the same institution, expected to complete her studies in 2024. Her academic background equips her with a strong foundation in both neuroscience and computer science, contributing to her expertise in data science and machine learning.
Research and Development Contributions
Morgenthal has contributed to research and development in her field, notably by developing a patented workflow for modeling approaches. This work is set to be published and presented at the International Mechanical Engineering Congress & Exposition (IMECE). She is also involved in a Visual AI project aimed at enhancing school safety, demonstrating her commitment to applying data science in practical and impactful ways.