I’m Uthpala, a computational physicist passionate about empowering researchers to push the boundaries of discovery through advanced computing. With over a decade of experience in research computing, data science, and high-performance computing, I help teams across disciplines turn ambitious ideas into scalable, high-impact research. As a Sr. Engagement Specialist with Duke Research Computing, I work with researchers and educators across the Duke community and throughout North Carolina to advance discovery through collaboration, innovation, and computational expertise.
Previously, I was a postdoctoral researcher in the Ab-Initio Materials Simulations (AIMS) lab at Duke University, where I developed and applied computational methods to design and characterize novel materials for semiconductor and energy applications.
This website serves as my digital corner in cyberspace where I share insights and musings about my research and other interests through my blog. You can explore a list of my publications derived from my research endeavors and a portfolio of projects I have contributed to. For an in-depth overview of my professional journey, please refer to my CV. Learn about the talks I've given over the years and check out the about page for a more personal glimpse into my life and passions.
I invite you to browse, read, and interact. Whether it's a thoughtful comment on a blog post or a question about my research, I would love to hear from you!
Publication announcement: our latest publication in Nature highlights our collaborative research that led to the discovery of a new mechanism explaining supe...
Leveraging DCC’s NVIDIA Tesla P100 GPUs, in this post I demonstrate how GPU acceleration within FHI‑aims and ELPA can speed up all-electron DFT calculations ...
Accurate error estimation is highly beneficial for quantifying differences in band structures of materials. This post explores utilizing the root-mean-square...
Efficient resource monitoring is key to maximizing HPC performance. In this post, I explore techniques for advanced resource monitoring on HPC clusters and p...