Ronit Chatterjee
About Ronit Chatterjee
Ronit Chatterjee is an Associate Software Product Engineer at Wadhwani AI in New Delhi, India, where he has worked since 2022. He holds a B.Tech in Computer Science Engineering with a specialization in Cyber Security and Forensics from UPES and has experience in developing applications and solutions that prioritize accessibility and data privacy.
Work at Wadhwani AI
Ronit Chatterjee has been employed at Wadhwani AI as an Associate Software Product Engineer since 2022. His role involves contributing to the development of software products that leverage artificial intelligence for social impact. The position is based in New Delhi, India, and follows a hybrid work model.
Education and Expertise
Ronit Chatterjee completed his B.Tech in Computer Science Engineering with a focus on Cyber Security and Forensics at UPES from 2019 to 2023. Prior to that, he studied at Don Bosco High School in India, where he achieved the ISC in Science from 2007 to 2019. His educational background equips him with a strong foundation in software development and security.
Professional Experience
Ronit Chatterjee has held various positions in software development. He worked as a React Native Developer at Drona Pay for three months in 2022 and at Qressy for one year from 2020 to 2021. Additionally, he served as a Frontend Developer at Roughpaper Technologies for four months in 2021 and as a Frontend Engineer at Fello for one month in 2022.
Projects and Contributions
Ronit Chatterjee has developed a user-friendly app using React Native, emphasizing accessibility and engagement, and included language internationalization features. He designed a data anonymization dashboard for Tuberculosis Data utilizing AWS Services to uphold data privacy standards. He also collaborated with the Buddhist Digital Resource Center to digitize Buddhist manuscripts and contributed to the Cough Against Tuberculosis project, enhancing public health services.
Innovative Solutions in Health Care
Ronit implemented a Health Care Worker Solution that employs real-time AI-driven responses based on cough sound analysis. This solution utilizes an innovative offline inference model, showcasing his ability to integrate advanced technology into health care applications.