About
Engineering student with a strong foundation in Python, C/C++, and machine learning, with hands-on experience in embedded, IoT, and AI-driven systems. Built and deployed projects spanning signal processing, CNN-based classification, and cloud-based applications.
Skills
Tools / apps / platforms
Projects
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Obstacle Avoiding Robotic CarEmbedded C, Arduino IDE, Arduino, Ultrasonic Sensor, IR Sensor
Built an autonomous robotic vehicle capable of detecting and avoiding obstacles in real time. Used an ultrasonic sensor to measure distance to nearby objects and trigger navigation logic. Implemented obstacle detection and motor control logic in Embedded C. Improved navigation reliability through real-time, sensor-based decision making.
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Animal Voice Detection and Classification SystemPython, TensorFlow, Librosa, NumPy, Pandas
Built a machine learning system to classify animal species from audio vocalizations. Performed audio preprocessing, noise reduction, and generated Mel-spectrograms using Librosa. Trained a CNN model to recognize distinct animal sound patterns. Evaluated model performance on unseen audio samples to measure prediction accuracy.
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Cloud-Based ECG Signal Analysis for Real-Time Cardiac Rhythm Monitoring Using AIPython, TensorFlow, MongoDB, AWS EC2, ESP32, AD8232
Developed a real-time ECG monitoring system using an ESP32 microcontroller and AD8232 ECG sensor. Applied signal preprocessing techniques including filtering, normalization, and R-peak detection. Built a 1D CNN model in TensorFlow to classify normal and abnormal cardiac rhythms. Deployed the backend and AI model on AWS EC2 and built a web dashboard for visualization, prediction results, and report generation.
Courses & certifications
- Automation Anywhere Essentials — Automation Professional · Automation Anywhere
- Deloitte Data Analytics Job Simulation · Deloitte
- Google AI Essentials · Google
⚽ Extracurricular activities
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NSS Volunteer
🎯 Hobbies & interests
- Artificial Intelligence
- Machine Learning
- Embedded Systems
- Software Development