TARA — Multimodal Assistant
Voice and camera-enabled assistant with navigation, automation, and notification features. Built using Jetson, ESP32, and local ML models.
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“I create innovative solutions by blending electronics, circuits, and communication systems with software and AI. From solving complex circuit problems to developing IoT and robotics projects, I thrive on building smart, connected, and efficient systems.”
Innovative Electronics & Communication Engineer with a strong foundation in embedded systems, IoT, and automation. Skilled in combining hardware and software to create efficient, real-world solutions. Adept at problem-solving, quick to adapt to new technologies, and driven to turn ideas into working prototypes through a mix of creativity, technical skill, and hands-on experience.
Voice and camera-enabled assistant with navigation, automation, and notification features. Built using Jetson, ESP32, and local ML models.
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Prototype for object detection and navigation using camera input and real-time control loops.
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Machine learning-based system for monitoring and detecting suspicious network activity in real time.
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Embedded device for on-site soil analysis and crop recommendations to improve sustainable agriculture practices.
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This project implements the(AODV)routing protocol for MANETs. It focuses on efficient route discovery, maintenance, and adaptability in dynamic networks. Performance is evaluated using OMNeT++ through metrics like packet delivery ratio and delay.
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This project implements a deep learning model for generating descriptive captions for images. It utilizes Convolutional Neural Networks (CNN) for feature extraction and Long Short-Term Memory (LSTM) networks for sequence generation.
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Using OpenMP to enable parallel execution, Reduced computation time and improved scalability for large datasets. Optimized data handling and matrix operations for better performance.
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Arduino-based distance measurement shown on an LCD. Useful for obstacle detection and robotics projects.
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Completed Machine Learning course from Great Learning.
Certified in Junos Networking Fundamentals by Juniper Networks.
Published research paper at ICTCS 2024 on Intrusion Detection Systems.
Successfully completed course on Multicore Architecture & Programming from Bosch Global Software Technologies collaborated with college.
This course covered essential software development workflows, including managing project history, branching, and merging via the command line. Key skills include tracking code changes, resolving conflicts, and collaborating on projects through pull requests to ensure project integrity.
Completed 17-week internship in Artificial Intelligence and Machine Learning at Abhyudyaya Techno Solutions Pvt. Ltd.
This course covered the core hardware components that form the backbone of a network, including routers, switches, and hubs. Key skills developed include identifying essential network devices and understanding the characteristics, advantages, and applications of various network architectures.
Successfully completed MATLAB Onramp, Simulink Onramp training courses by MathWorks, gaining foundational skills in MATLAB programming, data visualization, Simulink modeling & simulation for engineering applications.