Avinash Panneerselvam
About Avinash Panneerselvam
Avinash Panneerselvam is a Data Scientist with expertise in computer vision and generative AI, currently employed at Inito since 2023. He has a background in machine learning from previous roles at Ola Electric Mobility and ShareChat, and holds a Dual Degree in Computational Engineering from the Indian Institute of Technology, Madras.
Work at Inito
Avinash Panneerselvam has been employed as a Data Scientist at Inito since 2023. In this role, he focuses on leveraging his expertise in computer vision and generative AI to develop innovative solutions. His work contributes to the company's mission of enhancing health-related applications through advanced data analysis and machine learning techniques.
Previous Experience at Ola Electric Mobility
Prior to his current role, Avinash worked at Ola Electric Mobility Pvt. Ltd. as a Machine Learning Engineer from 2020 to 2021. During his tenure in Bengaluru, Karnataka, he gained experience in developing machine learning models, which laid the groundwork for his subsequent roles in the industry.
Experience at ShareChat
Avinash served as a Machine Learning Engineer at ShareChat from 2021 to 2023. His responsibilities included building machine learning models and implementing solutions that addressed various challenges. This position allowed him to further develop his skills in a remote work environment while contributing to the company's technological advancements.
Education and Expertise
Avinash Panneerselvam holds a Dual Degree in Computational Engineering from the Indian Institute of Technology, Madras, where he studied from 2015 to 2020. His educational background provides a strong foundation in mathematics and coding, which he applies in his work as a Data Scientist. He continues to enhance his knowledge in natural language processing, complementing his existing expertise in computer vision and generative AI.
Specialization in Health-Related Applications
Avinash specializes in developing machine learning models for health-related applications. His work includes predicting menstrual cycle length and fertility ratings, demonstrating his focus on applying technology to improve health outcomes. This specialization highlights his ability to combine technical skills with a meaningful impact in the health sector.