Embedded Machine learning engineer | TinyML enthusiastic | Innovating solutions for Real world problems
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IntruderDetectionSystem
August 21, 2025 – August 21, 2025
IntruderDetectionSystem — GitHub repository
View ProjectPredictiveMaintenance
March 26, 2022 – March 26, 2022
PredictiveMaintenance — GitHub repository
View ProjectVehiclePredictiveMaintenance
December 14, 2021 – December 14, 2021
VehiclePredictiveMaintenance — GitHub repository
View ProjectBatteryLifeCyclePredictor
August 22, 2021 – August 22, 2021
BatteryLifeCyclePredictor — GitHub repository
View ProjectCovidPatientHealhAssessingDevice
June 19, 2021 – June 20, 2021
A medical device which will have SpO2 , respiratory rate , heart rate , body temperature and on the top it will run by TinyML model using Edge impulse to predicts the patient condition. The classification is based on research papers.
View ProjectnRF5340-DK-ECG_Analyzer
June 17, 2021 – June 17, 2021
ECG analyzer library is a C library with all predefined signal processing to split the filtered ECG wave into R-R wave and PR wave .
View ProjectTinyML
May 9, 2021 – June 2, 2021
I will be updating the Tensor Flow lite tutorials with application oriented projects.
View ProjectDriverBrakingPatternAnalyzer
April 24, 2021 – May 9, 2021
I have developed a TinyML model using Edge impulse software . This model can predict your braking skills in speed breakers and potholes. I have added external sensors over my brake pedal and accelerometer for data capturing. This model will classify your braking into : Good Braking Over Braked Under Braked Flat Road Drive
View ProjectECGAnalyzer
March 13, 2021 – June 17, 2021
I worked on a TinyML application powered by Edge Impulse to develop a mini-Diagnosis ECG analyzer device which can fit on a pocket and it can diagnose heart diseases independently without an Internet.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal, self-directed initiatives, primarily in TinyML and embedded AI. While this demonstrates strong individual drive, there is no evidence of team collaboration or experience in diverse project environments, which might impact cultural integration in a collaborative team setting. The projects align well with a Machine Learning Engineer role, particularly one with an embedded or edge computing focus.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a self-starter attitude and a focus on practical application, but collaboration, communication, and problem-solving under pressure cannot be evaluated without further interaction.