Anand Kumar
About Anand Kumar
Anand Kumar is a Senior Software Development Engineer at SOPHiA GENETICS in Boston, Massachusetts. He holds a Bachelor's degree in Computer Science from the Indian Institute of Technology, Patna, and a Master's degree from New York University, and has contributed to significant projects in software development and performance optimization.
Work at SOPHiA GENETICS
Anand Kumar has been employed at SOPHiA GENETICS as a Senior Software Development Engineer since 2023. He is based in Boston, Massachusetts, United States. In this role, he contributes to the development of software solutions that enhance genomic data analysis and improve healthcare outcomes.
Education and Expertise
Anand Kumar holds a Bachelor of Technology (BTech) in Computer Science from the Indian Institute of Technology, Patna, where he studied from 2013 to 2017. He further advanced his education by obtaining a Master's degree in Computer Science from New York University, attending from 2021 to 2023. His expertise encompasses a variety of programming languages and technologies, including Java, Python, C, C++, JavaScript, ReactJS, Redux, AWS, GCP, Azure, Kubernetes, CI/CD, Terraform, BDD, and TDD.
Professional Background
Prior to his current position, Anand Kumar completed a Software Developer Internship at Adobe in 2022, where he gained experience in software development. He also served as an Undergraduate Research Assistant at A*STAR - Agency for Science, Technology and Research in 2016. Additionally, he worked on diverse projects during his master's studies, focusing on Software Defined Networking and parallel programming.
Achievements in Software Development
Anand Kumar has made significant contributions in his field, notably improving the boot time performance of Samsung's TIZEN operating system by approximately 300 milliseconds. He played a pivotal role in developing a full-stack internal web dashboard at Adobe, utilizing technologies such as React, Redux, and AWS. Furthermore, he automated the infrastructure pipeline of TIZEN's image test-debug cycle, reducing human intervention by over 90% and accelerating the cycle by around 70%.