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Full Stack Engineer with less than a year in IoT, Machine Learning & Web Technologies
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Highly motivated Computer Science & Engineering student specializing in IoT and Automation with a strong foundation in data structures, algorithms, machine learning, and cloud computing. Proficient in a range of programming languages and web technologies, I excel in developing innovative solutions for real-world problems. My experience includes building IoT systems, full-stack web applications, and implementing machine learning models for predictive analytics. I am adept at agile development, problem-solving, and collaborating effectively in distributed teams.
SASTRA Deemed University
Bachelor of Technology · Computer Science & Engineering (Specialization: IoT and Automation)
August 1, 2021 – June 30, 2025
Amalraj Matric Hr Sec School
Higher Secondary Education
June 1, 2019 – May 31, 2021
Oasis Infobyte (AICTE OIB-SIP)
Web Development & Design Intern
June 1, 2026 – Present
India
IoT-Based Water Quality Monitoring & Disease Prediction System
January 1, 2025 – May 1, 2025
Built an IoT system with ESP32 measuring pH, turbidity, TDS, and nitrate levels; achieved 99.78% accuracy using Random Forest classifier for waterborne disease risk prediction. Implemented TS-SMOTE algorithm for time-series data balancing, improving rare event detection by 25%. Developed LSTM forecasting model (MSE: 0.1631 for pH) enabling proactive water quality management. Designed real-time web dashboard with Chart.js for data visualization and automated contamination alerts. Applied SHAP for interpretable AI-driven risk predictions, enhancing decision-making transparency.
Comprehensive exploration of Emergency & Threat Management System
January 1, 2025 – May 1, 2025
Designed and developed full-stack web application using MongoDB, Express.js, React, and Node.js to efficiently manage emergency situations and coordinate rapid response. Integrated Geolocation API to automatically pinpoint accident locations and alert nearby hospitals, reducing ambulance dispatch time by 40% and improving emergency response efficiency by 30%. Engineered real-time data handling and mobile-responsive interface ensuring seamless emergency coordination.
Innovative Food Ordering Platform
January 1, 2024 – May 1, 2024
Developed fully responsive food delivery web application using React.js with dynamic cart management and real-time order tracking through efficient state management and component-based architecture. Integrated RESTful APIs for menu data retrieval and optimized order workflow for fast, reliable user interactions. Deployed on Netlify with performance tuning and accessibility optimization for seamless user experience.
IOT Based Smart College Bus Tracking System
January 1, 2024 – May 1, 2024
Developed real-time IoT-based tracking system using ESP8266 and GPS modules to optimize university transportation routes and reduce student waiting times. Built cloud-connected backend with Node.js and MongoDB for precise location tracking and predictive arrival times. Created mobile-responsive dashboard for real-time vehicle monitoring, improving transparency for students and administrators. Leveraged data analytics to monitor movement patterns and reduce route delays by over 30%.
Web Development Internship
Oasis Infobyte (AICTE OIB-SIP)
June 1, 2026 – Present
React Frontend Project
GreatStack
June 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning IoT, MERN stack, and machine learning applications, indicates a broad interest and willingness to explore different technical domains. The academic projects show initiative and a drive to apply learned concepts. The specialization in IoT and Automation, combined with full-stack development, suggests a candidate who can bridge different technical areas. This breadth of skills and project types indicates a good cultural fit for a role that values versatility and continuous learning, especially in a startup or innovative environment.
Soft Skills & Operational Fit
The candidate lists problem-solving, team collaboration, communication, adaptability, and continuous learning as soft skills. Project descriptions indicate collaboration and problem-solving. The academic nature of projects suggests a learning-oriented approach. The internship experience, though virtual, also highlights teamwork and debugging. These align well with operational fit for a dynamic engineering team.