About

Kunal Punjabi is an experienced engineer associate currently working at Qualcomm, where he is part of the System Performance Team. With a background in Electrical Engineering from IIT Roorkee and a Master's Degree in Operations Research from the University of Texas, Kunal has a strong foundation in both engineering and data analysis. Kunal has a proven track record of successfully implementing Machine Learning techniques to improve battery life and power consumption on Qualcomm Chips. He worked on the workload classification project, where he developed an algorithm that led to an 8% improvement in power consumption on two Qualcomm Chipsets. Kunal's work on this project resulted in a patent application for the resultant invention. Kunal has experience working with video hardware and high-level synthesis tools, where he was responsible for generating production quality RTL from C++ code. He has also worked as a Placement Manager for the Training and Placement Cell at IIT Roorkee, where he led and managed the central placement team. Under his leadership, the team received the highest number of offers (1195) and the highest number of companies visited (230). Kunal's technical skills include expertise in Machine Learning, with a strong toolkit in Perl and Octave. He has 7.18 years of relevant experience and a passion for using technology to solve complex problems. With a strong foundation in both engineering and data analysis, Kunal is a valuable asset to any team looking to develop innovative solutions.