Divyansh Dilip Renkuntlawar

Tech-driven Computer Engineering student at Vishwakarma University with practical experience in IoT, AI/ML, and database systems. Completed a 6-month project internship focused on drone systems, specializing in edge AI integration with Raspberry Pi and Hailo processors. Proficient in Python, C++, and SQL, with a keen interest in Cybersecurity and emerging technologies. Committed to utilizing embedded systems and intelligent automation to address real-world challenges.

• 🥇 1st Place – Poster Making Competition (Mathematics Day) Designed a creative poster on Srinivasa Ramanujan
• 🏆 Finalist – Smart India Hackathon (SIH) 2024 Co-lead in AIML domain; worked on a solution for Drug-Drug Interaction Detection
• 🥉 3rd Place – Visionary Hackathon (IoT Track) Developed a Smart Traffic System | Vishwakarma University
• 🎖️ Participation – Visionary Hackathon (IoT Track) Built a Smart GPS Tracking System | Vishwakarma University

🚀 Face Recognition Attendance System
Python, OpenCV, SQLite

• Developed a face recognition-based attendance system using OpenCV and Haar cascades.
• Integrated SQLite to store and retrieve attendance logs securely.

📦 Inventory Management System
Python (Tkinter), SQL

• Built a desktop-based inventory management tool with GUI for product entry, stock updates, and sales reporting.
• Utilized SQL for backend storage and implemented basic CRUD operations.

🚆 IRCTC Clone – Train Ticket Booking Platform
React, Node.js, Express.js, MySQL

• Developed a full-stack web application replicating train booking functionality similar to IRCTC.
• Designed RESTful APIs for booking, search, and user authentication; connected to MySQL for data persistence.

🌫️ Air Quality Index Monitoring System
Arduino, IoT Sensors (MQ135), LCD Display

• Designed and implemented an IoT-based system to monitor AQI using environmental gas sensors.
• Displayed real-time AQI values on an LCD and triggered alerts for critical levels.

💊 Drug-Drug Interaction Management System
Python, Pandas, Neural Networks (CUDA)

• Developed an AI-based system to detect harmful drug combinations using neural networks and large pharmaceutical datasets.
• Implemented data preprocessing, model training, and GPU-based computation using CUDA to accelerate learning.
• Designed the project to assist healthcare systems in improving patient safety through automation.

🧠 License Plate Recognition System
YOLOv8, EasyOCR, OpenCV, Python

• Built an AI-based license plate recognition pipeline using YOLOv8 for detection and EasyOCR for number extraction.
• Handled live video stream inputs and processed frames in real time for traffic surveillance.

🔧 System Health Monitoring Tool (Internship Project at Syngenta)
Python, Azure, REST APIs

• Developed Python automation scripts for internal diagnostics and performance monitoring.
• Integrated with REST APIs and Azure services to analyze logs and generate health reports.

• Tech Volunteer – First Tech Challenge (FTC)
  Handled robot inspections and ensured match compliance during official events
• Student Coordinator – World Water Day (College Event)
  Planned and led the event execution with task delegation and coordination

• IT Fundamentals for Cybersecurity – IBM, Coursera
• Computer Network Security Fundamentals – Coursera
• Google Cybersecurity Certificate – In progress
• BI Dashboards with IBM Cognos Analytics and Google Looker – Coursera
• Workshop on Embedded Systems and IoT – Vishwakarma University, hands-on training on IoT hardware and embedded systems integration