About

Sparsh Agarwal is a talented individual with a strong background in Software Development and Machine Learning. Currently working as an Associate Consultant at FinMechanics, he has gained valuable experience through internships, coursework, and personal projects. Sparsh is passionate about applying his skills and knowledge to the field of Corporate Finance. Sparsh is a problem solver who enjoys participating in hackathons, collaborating with others on projects, and working on innovative ideas that could have an impact on everyday life. He has worked on projects in various domains such as robotics, NLP, computer vision, blockchain, reinforcement learning, software development, and data analysis. This has enabled him to learn new things quickly and efficiently. During his internship at Siemens, Sparsh created a Battery Simulation using NASA prognostics algorithm and employed reinforcement learning for prediction of the Remaining Useful Life (RUL) of a battery. He also modeled Battery Calibration as a tracking problem and solved it using advanced reinforcement learning algorithms Soft Actor Critic (SAC) and Deep Deterministic Policy Gradients (DDPG). At IITK Summer of Code, he designed and created a responsive and scalable Web App for the community of IIT Kanpur to find, share, and download study resources across a plethora of courses on any platform. Sparsh holds a Bachelor of Technology in Mechanical Engineering from IIT Kanpur and has completed his Senior Secondary (CBSE) education from GRM School, Bareilly. He is proficient in a variety of technologies such as Reinforcement Learning, Blockchain, Software Engineering, Computer Vision, NLP, ML, Research Science, NoSQL, Frontend, Web, and AngularJS. With 0.35 years of relevant experience, Sparsh is always looking for new challenges and opportunities to expand his skillset. He welcomes any messages or inquiries from those who are interested in collaborating with him.