I am Gopal Chitalia, a graduate student at Purdue University and working with Prof. Jan Anders Mansson on fault detection in motors using deep learning in a joint project with Wistron. Additionally, I'm working with Prof. Junjie Qin on transfer learning application using LLMs for optimizing power networks.
I have had the privilege of working at Center for Building Science Lab under the supervision of Prof. Vishal Garg. I have previously been a Research Assistant/Visiting ML Scholar at the Smart Grid Research Unit (SGRU) under Manisa Pipattanasomporn (Adjunct Faculty, Virginia Tech).
In addition to my academic pursuits, I have also contributed to the industry in the domains of Energy Efficiency, IoT, and Machine Learning. I have worked at ClevAir (Norway) as a Data Scientist and Growthworks.ai (CA, USA) as an ML Scientist/Energy Demand Expert.
My research work on predicting short/long-term energy prediction in office/residential buildings using machine learning is published in Applied Energy. The results improve the state-of-the-art results by 20-40%. I am also an active reviewer at Applied Energy. Furthermore, I have collaborated on a building-level dataset paper which has been published in Nature Scientific Data.
Previously, I have also worked with Prof. Jyotirmay Mathur at the Centre for Energy & Environment, MNIT Jaipur on Predicting time ahead heating/cooling energy demand HVAC systems. Moreover, as an independent research student, I also collaborated with Prof. Praveen Paruchuri of Machine Learning Lab, IIIT-H for Reinforcement Learning (RL) applications for controlling HVAC systems.