Enea Dodi
About Enea Dodi
Enea Dodi is a Machine Learning Engineer 2 at WPS Health Solutions, where he has worked since 2022. He has a strong background in computer science, having graduated with a high GPA from the University of Massachusetts Amherst and previously held positions in research and IT support.
Current Role at WPS Health Solutions
Enea Dodi currently serves as a Machine Learning Engineer 2 at WPS Health Solutions. He has held this position since 2022 and works remotely. In this role, he applies his expertise in machine learning to develop innovative solutions that enhance the company's operational efficiency and data analysis capabilities.
Previous Experience in Academia
Enea Dodi has a background in academia, having worked at the University of Massachusetts Amherst. He served as an Undergraduate Course Assistant and Tutor in 2020 for four months, and again in 2021 for three months. During his time at UMass, he contributed to the educational development of students while gaining hands-on experience in a teaching environment.
Research Experience at National Science Foundation
In 2021, Enea Dodi worked as a Researcher at the National Science Foundation (NSF) for six months. This role allowed him to engage in research projects that likely contributed to advancements in his field, enhancing his analytical skills and understanding of scientific methodologies.
Education and Academic Achievements
Enea Dodi graduated with a high GPA of 3.971 from the University of Massachusetts Amherst, where he studied Computer Science and Philosophy, earning a Bachelor of Science degree from 2019 to 2021. Prior to that, he completed his Bachelor's degree in Computer Science at Chapman University from 2017 to 2019. His academic background has provided him with a solid foundation in computer science principles.
Technical Skills and Interests
Enea Dodi possesses a range of technical skills, including application development and database management using Java. He has expertise in UI development utilizing React and Material UI. Additionally, he has a strong interest in decentralization, data science, and machine learning, which informs his approach to problem-solving and coding projects.