Deepika Yeramosu
About Deepika Yeramosu
Deepika Yeramosu is a computational biologist currently working at the Broad Institute of MIT and Harvard. She has a background in bioinformatics and computational biology, with previous research and internship experiences at notable institutions including UPMC Children's Hospital and Bristol Myers Squibb.
Work at Broad Institute
Deepika Yeramosu has been employed as a Computational Biologist at the Broad Institute of MIT and Harvard since 2023. In this role, she engages in research that combines biology with computational techniques to advance understanding in the field. The Broad Institute is known for its contributions to genomics and biomedical research, providing an environment for innovative scientific exploration.
Previous Experience in Computational Biology
Prior to her current position, Deepika Yeramosu worked as a Graduate Student Researcher in the Computational Biology Department at Carnegie Mellon University from 2021 to 2022. She also served as a Student Researcher at UPMC Children's Hospital of Pittsburgh from 2018 to 2020. Additionally, she held the role of Associate Data Scientist at BigHat Biosciences for four months in 2022 and completed a BI&A Summer Internship at Bristol Myers Squibb in 2021.
Education and Expertise
Deepika Yeramosu earned her Bachelor's degree in Bioinformatics from the University of Pittsburgh, where she studied from 2016 to 2020. She furthered her education by obtaining a Master's degree in Computational Biology from Carnegie Mellon University, completing her studies from 2020 to 2022. Her academic background provides her with a strong foundation in both biological sciences and computational methodologies.
Teaching and Research Roles
During her academic career, Deepika Yeramosu served as an Undergraduate Teaching Assistant for Organic Chemistry at the University of Pittsburgh from 2019 to 2020. This role involved supporting undergraduate students in their coursework and enhancing their understanding of organic chemistry principles. Her teaching experience complements her research background in computational biology.