AI application engineer with rich experience in analyzing and building models. Having R&D experience in implementing and deploying innovative AI applications.
Developed model for hardware design verification to debug the errors faster.
Building a model to make
Worked on different models(i.e. 3D Unet, RNNt) to explore the operators in medical healthcare domain and speech processing.
Part of the core team for sensor based product design and development.
Build PoCs for Blood pressure and heart rate monitoring system using Photoplethysmography sensor. Build a realtime application to predict the heart rate and blood pressure.
Developed PoCs for activity detection, fall detection and activity monitoring using accelerometer and gyroscope for different clients in health care and mining section.
Developed model for gesture recognition for smart remote and locking system.
Worked on a solution for blurring and low light problem in computer vision for realtime attendance system using face recognition.
Extensively involved in feature engineering, signal processing, modeling , model evaluation and analysis.
Worked on SVM to port it on the embedded device.
Machine Learning, Data Science, Edge Computing
undefinedNon-invasive modeling of heart rate and blood pressure from a photoplethysmography by using machine learning techniquesNon-invasive modeling of heart rate and blood pressure from a photoplethysmography by using machine learning techniques
IEEE · Jan 8, 2020
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International Journal of Advanced Engineering and Global Technology Vol-2, Issue-1 · Jan 1, 2014