Apurva Surya

Integrated WebRTC M116 into the company's product network pipeline and enabled over-the-network communication between services using sockets. Debugged several issues arising from using the latest XR libraries in Unity, including loss of FPS control and product crashes.

Applied machine learning and econometrics to analyze rural labor market data. This research involved complex statistical modeling and data interpretation to derive insights into economic trends.

Developed topic models and panel regressions on large-scale Indian survey datasets. This involved advanced statistical techniques to extract meaningful patterns and relationships from extensive data.

Automated employee allocation using classification models and comparative scoring, which significantly improved planning efficiency. This involved developing and implementing machine learning models to streamline the allocation process.

Built software pipelines for driver distraction and anomaly detection using machine learning techniques on the STAIRS dataset. This project focused on developing robust systems for real-time analysis of driver behavior.

Created an LSTM-based text generator trained on classic literature. This project involved deep learning techniques for natural language processing and generative model development.

Suggested automation enhancements and GPS-based targeting for T-92 tank systems. This involved analyzing existing systems and proposing technological improvements to enhance operational efficiency.

Grade: 7.5 CGPA

Graduated with a dual degree in Electronics and Instrumentation. Achieved a CGPA of 7.5.