Eric H.
About Eric H.
Eric H. is a Lead Machine Learning Engineer at BigBear.ai, with a strong background in electrical engineering and extensive experience in machine learning applications. He has contributed to various projects, including improving autonomous cleaning vehicles and developing forecasting models for maritime logistics.
Current Role at BigBear.ai
Eric H. serves as the Lead Machine Learning Engineer at BigBear.ai, a position he has held since 2021. In this role, he focuses on developing and optimizing machine learning models to enhance operational efficiency. His work contributes to the company's mission of providing advanced analytics and AI solutions.
Previous Experience in Machine Learning
Prior to his current role, Eric H. worked as a Machine Learning Engineer at Trabus Technologies from 2019 to 2021. He developed models for forecasting estimated time of arrivals for ships on U.S. inland waterways. His optimization of forecast models using time series analysis led to a 50% improvement in the baseline's mean average error.
Educational Background in Electrical Engineering
Eric H. completed his Bachelor of Science in Electrical Engineering at UC San Diego from 2013 to 2017. He further advanced his education by obtaining a Master of Science in Electrical Engineering from the same institution, studying from 2017 to 2018. His academic background laid the foundation for his expertise in machine learning and engineering.
Internship Experience at Brain Corp
In 2018, Eric H. interned at Brain Corp as a Platform/Machine Learning Intern for three months. During this internship, he focused on improving autonomous cleaning vehicles, gaining practical experience in machine learning applications within the robotics field.
Contributions to Academia and Research
Eric H. has contributed to academic projects, including publishing a paper on object recognition aimed at assisting children with autism. He also worked as a Teacher's Assistant and Engineering Hands-On Group Project Tutor at UC San Diego, where he supported students in their engineering coursework.