Kashish Kumar
About Kashish Kumar
Kashish Kumar is a Data Scientist at ExxonMobil with a background in machine learning, structural engineering, and sustainability.
Title and Current Role
Kashish Kumar is currently employed at ExxonMobil as a Data Scientist. He holds this position since 2024 and is based in Bengaluru, Karnataka, India. His work focuses on leveraging data science techniques to drive efficiencies and innovations within the company.
Previous Positions
Kashish Kumar has a rich professional background with several notable positions. He was a Data Scientist at ExxonMobil from 2022 to 2023 in Bengaluru. Prior to that, he served as a Senior Associate at upGrad from 2021 to 2022. He also worked as a Machine Learning Engineer at IDrive Inc. / IDrive Ventures LLC. from 2019 to 2020. Additionally, he held positions such as Graduate Student Researcher at IIT Madras (2018-2019), Graduate Engineer at Mahindra Susten (2016-2017), and Research Intern at IIT Kanpur in 2015.
Education and Expertise
Kashish Kumar completed his Master of Technology at the Indian Institute of Technology, Madras, from 2017 to 2019. He also holds a Bachelor of Engineering degree from Punjab Engineering College, which he achieved between 2012 and 2016. His academic background provides him with a solid foundation in engineering, machine learning, and data science.
Research and Projects
While studying at IIT Madras, Kashish contributed to an interdisciplinary research project aimed at applying machine learning algorithms to improve structural optimization processes. At ExxonMobil, he developed a notable computer vision project designed to detect industrial equipment and classify them based on corrosion damage levels, showcasing his innovative approach to practical problems.
Professional Interests and Personal Activities
Kashish Kumar has a diverse set of interests that include sustainability, personal finance, and structural engineering, in addition to his professional focus on machine learning. He dedicates time to writing, teaching, mentoring, and coding. He is actively engaged in utilizing advanced data science techniques, such as retrieval augmented generation and few-shot learning with open-source LLMs like LLama2 and Mixtral, for predictive analytics in industrial contexts.