Harsh Dolhare

Harsh Dolhare is currently a Quantitative Researcher at Dolat Capital since July 2022. Previously, Harsh worked as a Research Assistant at Aalto University, where a Bayesian Reinforcement Learning model was implemented for optimizing robotic control trajectories. An experience as an Analyst at American Express involved analyzing the impact of Covid-19 on various products. Additionally, Harsh served as a Research Assistant at the Indian Institute of Technology, Bombay, where an efficient supervised learning algorithm for decoding LDPC codes used in wireless communication was devised, and extensive research on deep learning techniques for error correction in 5G standards was conducted. Harsh also contributed as a Teaching Assistant in the Data Analytics and Visualization Team at IITB. Harsh holds a Bachelor of Technology degree in Electrical and Electronics Engineering from the Indian Institute of Technology, Bombay, completed in 2022.