Shubham Jindal

Shubham Jindal is a Computer Science MS graduate student at SUNY Stony Brook University, focusing on Systems and Security, particularly distributed systems optimization.

With 2 years of industry experience, Shubham has a strong background in Linux systems, programming languages like C/C++, Java, Python, and C#.NET, and shell scripting.

Having worked at Drishti Soft Solutions and Samsung Electronics, Shubham gained expertise in GWT, Java OSGi framework, Android mobile application development, and machine learning initiatives.

During his tenure at Samsung Electronics, Shubham contributed to projects related to machine learning and obtained a software design patent.

Additionally, Shubham interned at Uber, where he worked on designing and implementing isolation in the Risk Platform team's feature access landscape.

Currently, Shubham is focused on optimizing Pinot, a real-time distributed OLAP datastore project by LinkedIn, under the guidance of Prof. Anshul Gandhi at PACElab.

Shubham excels in handling multiple projects under pressure, meeting tight deadlines, and exhibits a strong aptitude for learning and problem-solving beyond traditional approaches.

His skill set includes C, C++, Java, Python, OOPS, Machine Learning, Distributed Systems, Linux, and Android.

Shubham holds a Master's degree in Computer and Information Sciences from Stony Brook University Graduate School, with a GPA of 3.87/4.0, and a Bachelor's degree in Computer Software Engineering from Dr. B. R. Ambedkar National Institute of Technology, Jalandhar.

He has also been associated with organizations like Oracle, Uber, PACELab at Stony Brook University, Samsung Electronics, Drishti Soft Solutions, and Frankly.me.