01 Profile_Brief
I am a research-focused BCA (Honours with Research) student and experienced ML Lead. My work sits at the intersection of Artificial Intelligence and hardware security, specializing in building end-to-end autonomous systems from the ground up.
02 Experience_Log
Machine Learning Lead
Vigilantia Praesidium Pvt. Ltd.
OCT 2025 — MAR 2026
Python
Deep Learning (CNN)
FaceNet
MTCNN
OpenCV
ESP32
Firebase
Telegram API
ECC
- ▹Led development of multiple AI-powered systems across domains including smart security, agriculture, and automation.
- ▹Designed and trained deep learning models for face recognition, object detection, and behaviour analysis.
- ▹Conducted Research & Development (R&D) to improve model accuracy, optimize performance, and explore innovative AI solutions.
- ▹Built real-time computer vision pipelines using FaceNet, MTCNN, and OpenCV for practical deployment.
- ▹Developed and deployed systems like smart home security, attendance monitoring, traffic analysis, and agriculture automation.
- ▹Integrated IoT devices (ESP32) with AI models for real-world system interaction and control.
- ▹Implemented secure communication using ECC and AES-GCM encryption in AI-based IoT systems.
- ▹Integrated APIs (Telegram, Firebase) for real-time alerts, cloud storage, and monitoring.
- ▹Optimized models for low-latency, real-time inference on laptops and edge devices.
- ▹Collaborated with teams to convert research ideas into scalable, production-ready solutions.
03 Project_Inventory
Automated Student Attendance Monitoring & Analytics
PythonOpenCVFaceNetMTCNNPandasTelegram API
- • Implemented an automated attendance system using real-time face recognition to mark student presence with high accuracy.
- • Built the recognition pipeline using MTCNN for face detection and FaceNet embeddings for face recognition, enabling multi-student detection in a single frame.
- • Designed a CSV-based storage system for maintaining attendance logs locally, ensuring portability.
- • Integrated a Telegram bot to provide instant notifications to faculty and daily attendance reports.
- • Developed a system to handle multiple students simultaneously with averaged embeddings to reduce recognition errors.
- • Created an analytics module for insights, including daily, weekly, and monthly trends.
- • Optimized for low-latency processing on standard laptops for cost-effective deployment.
Identity Defenders – AI Security System
ECCAES-GCMESP32FaceNetTelegram API
- • Real-time face detection with webcam using FaceNet and MTCNN.
- • Automated alerts sent via Telegram when unknown faces are detected.
- • Simulated secure ‘lock/unlock’ messaging using ECC + AES-GCM cryptography.
- • ESP32-controlled solenoid lock for physical access protection.
Road Guard AI – Collision & Drowsiness Detection
Deep LearningYOLOCNNArduinoUltrasonic Sensor
- • Real-time driver drowsiness detection using eye aspect ratio (EAR) and facial landmark analysis.
- • Smart collision avoidance using ultrasonic sensor for precise distance measurement.
- • Instant audio/buzzer alert when driver fatigue or close obstacles are detected.
- • AI-powered object detection for obstacle identification using YOLO.
- • Integrated microcontroller-based hardware alert mechanism for real-world deployment.
Smart Agriculture Field System
ESP32FirebaseIoT SensorsPython
- • Smart irrigation and fertilizer system with automated resource management.
- • Voice command and WhatsApp alert integration for remote monitoring.
- • AI-based plant disease detection module currently in R&D phase.