Shankara Anand
About Shankara Anand
Shankara Anand is an Associate Computational Biologist currently working at the Broad Institute of MIT and Harvard. He has extensive experience in computational biology and medical research, with a focus on cancer genomics and drug design.
Work at Broad Institute
Currently, Shankara Anand serves as an Associate Computational Biologist at the Broad Institute of MIT and Harvard. He has held this position since 2018, contributing to various projects in the Greater Boston Area. His role involves applying computational biology techniques to support research initiatives, particularly in the field of cancer genomics.
Education and Expertise
Shankara Anand completed his Bachelor of Science (BS) at Stanford University from 2013 to 2017. He furthered his education by obtaining a Master of Science (MS) from Stanford University School of Medicine, which he completed in 2019. He is currently pursuing a Doctor of Medicine (MD) at Boston University School of Medicine, expected to be completed in 2024. His academic background provides a strong foundation in both computational methods and medical research.
Background in Research
Shankara Anand has extensive research experience in various institutions. He worked as a Student Researcher at Stanford University School of Medicine from 2014 to 2015 and later as a Researcher at Stanford University School of Engineering for five months in 2018. His internships at Cytokinetics and Genentech in 2015 and 2016, respectively, further enhanced his research skills in the biotechnology sector.
Internship Experience
In addition to his current roles, Shankara Anand has gained valuable experience as a Computer Aided Drug Design Intern at Novartis Institutes for BioMedical Research since 2017. He has also worked as a Discovery Biology R&D Intern at Cytokinetics and as a Research Intern at Genentech, where he contributed to projects focused on drug discovery and development.
Contributions to Open Source Projects
Shankara Anand has actively contributed to open-source projects related to computational biology on GitHub. His involvement in these projects reflects his commitment to advancing the field and sharing knowledge with the broader scientific community.