Principal Investigator
Lab Staff
Adarsh is a database analyst within the PhIAT Group, led by Dr. Dubis, within the University of Utah’s Department of Ophthalmology & Visual Sciences. In this role, Adarsh focuses on developing data-driven solutions for ophthalmology, including designing and maintaining robust and scalable database structures to manage diverse datasets such as imaging, genetic data, and electronic health records. His work supports the Dubis Lab's mission to enable advanced downstream applications by integrating data from both internal and external sources.
Previously, Adarsh gained valuable experience as a customer software engineer at Accenture, where he led data integration efforts using Tibco BW and SQL, streamlining workflows and enhancing system efficiency. His academic and professional projects have further honed his expertise, such as building predictive models for Home Credit Default Risk, analyzing Super Bowl social media data to derive marketing insights, and optimizing transit tracking systems for better data retrieval and storage.
Adarsh is passionate about leveraging data analytics and database design to create impactful, innovative solutions. With a strong foundation in Python, R, SQL, and visualization tools like Tableau and Power BI, he combines technical proficiency with analytical insight to contribute effectively to research and development initiatives.
Sai Krishna Bollina joined the PhIAT Group in September 2024 as a software design engineer specializing in scalable platforms for eye imaging data. With expertise in software design and development, He creates solutions that simplify workflows, enhance data labeling, and improve data analysis in medical imaging.
After earning a master’s degree in software development from the University of Utah in 2024, Sai honed his skills in system design, architecture, and problem-solving. With two years of experience as a software developer, he successfully built full-scale applications from scratch, showcasing his ability to transform ideas into robust systems.
Currently, Sai leverages advanced software engineering practices like modular design, database management, and RESTful APIs to optimize eye imaging workflows. He designs and develops user-friendly, scalable systems that ensure reliable and efficient data handling.
Sai is also passionate about bridging technology and healthcare through innovative software solutions to improve patient care and research outcomes.