About Me

I am Sahil Warade , From SCTRs Pune Institiute of computer Technology. Curretly Student in Final Year Information Technology Department. Seeking an internship opportunity that aligns with my skills, interests and aspirations, with the intention of transitioning this experience into a full- time role within the organization.

  • Programming Languages
    Python, C++
  • Web Development
    HTML,CSS, Javascrpit
  • Artifical Intelligence
    Model Making and Training
  • Machine learning
    TensorFlow , Object Detection
  • Advancements in Malware Detection
    Developed machine learning models to classify executables as malicious or benign using KNN,XGBoost,voting classifiers, and randomforests. Achieved high accuracy and reduced false positives through rigorous model validation.
  • YOUTUBE COMMENTS SENTIMENT ANALYSIS
    It is website made using Python and Flask (TeamProject). Website gives graph of sentiments in comments for that video.
  • Wanderlust
    (TeamProject) .Developed a full-stack hotel booking platform using the MERN stack (MongoDB, Express.js, React.js, Node.js) to enhance user experience in travel accommodations. Implemented secure user authentication with encrypted passwords and JSON WebTokens(JWT)for session management.
  • Real-time Chat Application
    (TeamProject) .This project is a dynamic, real-time chat application developed using the Flask framework. It provides a seamless communication experience through features such as user authentication (signup and login), public and private chat rooms, and real-time messaging capabilities powered by Flask-SocketIO. The application also incorporates file upload functionality, enhancing user interaction. A key highlight is the integration of an AI chat feature, demonstrating an understanding of artificial intelligence capabilities. The backend utilizes Flask-SQLAlchemy for robust data management and chat history storage, while Redis is implemented for efficient message brokering and real-time event handling. The responsive frontend is built with HTML, CSS, and JavaScript. This project showcases strong skills in full-stack web development, real-time communication protocols, database management, and API integration..
  • Portfolio Website
    This is a personal portfolio website built using HTML, CSS, and JavaScript to showcase my skills, projects, experience, and education. The website features a professional and minimalistic design with smooth animations, well-structured content, and a defined color theme for a visually appealing user experience.
  • STUDY SWAP(EcommerceWebsite)
    It is website made using HTML,CSS and javascript.(TeamProject). Website that can be used to list your old educational materials which may not be used In future and selling the material students in need at lower price as compared to original.
  • TASK MANAGEMENT
    It is website made using HTML,CSS and javascript.(TeamProject) .Website which manages our task and remind us abou tour tasks with to-do- list .
  • Rent Price Prediction Pune
    (TeamProject) .Developed a linear regression model to predict rental prices in Pune based on area and address, providing instant estimates through a user-friendly interface. Analyzed model performance and visualized rental trends to enhance insights into pricing patterns.
  • Piano Kit
    Created an interactive Piano Kit website using HTML, CSS, and JavaScript, enabling users to play piano sounds bypressing keyboard keys. Designed a responsive interface with visual feedback for an engaging user experience. https://sahilwarade.github.io/Piano-Kit/
  • Montfort School Nagpur
    Class 10(SSC) 90.4%
  • St Paul School Nagpur
    Class 12(HSC) 94%
  • SCTR'S Pune Institute of Computer Technology,Pune (SPPU) Final Year
    Information Technology SGPA 8.01
  • SCTR'S Pune Institute of Computer Technology,Pune (SPPU)
    Honours in DataScience(2024-2026)
  • https://drive.google.com/drive/folders/1hyj8IOMjmDS-xznusjGNAheYFEmqv1DP

Experiences

AI-Powered Drowsiness Detection System (Research Intern at PICT)

Developed a full-stack AI system to enhance driver safety by detecting drowsiness in real-time. Utilized Flask, OpenCV, and TensorFlow for video processing and eye state prediction, integrated with WebSocket for seamless frame handling. Implemented a React frontend and Bootstrap dashboard for live detection and event analytics, stored in SQLite. Incorporated a voice assistant using pyttsx3 and Ollama’s Gemma3 for interactive alerts. Overcame challenges in optimizing WebSocket performance and speech recognition. Demonstrated expertise in computer vision, machine learning, and full-stack development, creating a scalable solution for automotive safety.

AL-ML Virtual Internship

I gained hands-on experience in mobile AI development, focusing on product image search, object detection, and image classification. I learned to integrate on-device Object Detection for product search, optimize TensorFlow Lite models, and train custom object-detection models using Model Maker. This experience enhanced my understanding of neural networks, deep learning, and mobile AI optimization, allowing me to build efficient, real-world AI solutions for mobile applications.

Networking Cloud Virtual Internship

I gained hands-on knowledge of cloud computing, virtualization, and modern networking technologies. The internship focused on the JNCIA-Cloud (Juniper Networks Certified Associate - Cloud) certification pathway, where I completed modules covering fundamental cloud concepts, Linux virtualization, containerization, network virtualization, NFV (Network Functions Virtualization), SDN (Software Defined Networking), and OpenStack. Additionally, I learned about OpenStack networking and gained practical exposure to cloud infrastructure setup and configuration. The program also introduced Kubernetes networking concepts, enhancing my understanding of container-based cloud deployments. This internship strengthened my skills in cloud networking, virtualization technologies, and network automation, preparing me for modern cloud and SDN-driven network environments.

Publications

AI-Powered Drowsiness Detection using LLM

• At Journal of Technology, Volume-13-issue-6-2025, Page No: 954-958 at 93 Position. ISSN:10123407, DOI: 18.15001/JOT.2025/V1316.25.1666

Sentimental Analysis: A Comparative Study over Different Social Media Platforms

At PICT’s International Journal of Engineering and Technology , Vol 2 Issue2 PIJET 09 (Upcoming)

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