Sowmya Raghavan
About Sowmya Raghavan
Sowmya Raghavan is a Senior Machine Learning Engineer at Vant AI, with a focus on computer vision and bioinformatics. She holds a Master's degree in Electrical and Electronics Engineering from Southern Illinois University Edwardsville and has experience in cheminformatics and molecular modeling.
Work at Vant AI
Sowmya Raghavan has been employed as a Senior Machine Learning Engineer at Vant AI since 2020. In this role, she focuses on developing machine learning solutions, particularly in the area of computer vision. Her tenure at Vant AI has allowed her to contribute to various projects that leverage advanced machine learning techniques to solve complex problems.
Work at Roivant Sciences
In addition to her role at Vant AI, Sowmya Raghavan has also been working at Roivant Sciences as a Senior Machine Learning Engineer since 2021. Her work at Roivant involves applying her machine learning expertise to enhance the company's capabilities in data analysis and interpretation, particularly in the life sciences sector.
Education and Expertise
Sowmya Raghavan holds a Master's degree in Electrical and Electronics Engineering from Southern Illinois University Edwardsville, where she studied from 2014 to 2016. She also earned a Bachelor's degree in Electrical, Electronics, and Communications Engineering from Anna University, completing her studies from 2010 to 2014. Her educational background provides a strong foundation for her expertise in machine learning and computer vision.
Previous Experience at Flagship Pioneering
Before joining Vant AI, Sowmya Raghavan worked as a Machine Learning Engineer at Flagship Pioneering from 2016 to 2020. During her four years in this position, she contributed to various machine learning initiatives, further developing her skills and knowledge in the field.
Technical Proficiencies
Sowmya Raghavan specializes in computer vision projects and is proficient in using Biopython for bioinformatics applications. She also has expertise in using Rdkit for cheminformatics and molecular modeling, which enhances her ability to work on interdisciplinary projects that intersect machine learning and biological sciences.