Proud to secure Rank 71 out of 16,837 participants in the Junior Coding Olympiad by Newton School of Technology! Grateful for the support and looking forward to more milestones ahead.

NST Junior Coding Olympiad

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Bachelor of Technology

Artificial intelligence

Intermediate (Class XII)

Science

Matriculation (Class X)

Not Applicable

As a front-end development intern, my role focuses on creating visually engaging and user-friendly web applications. I specialise in Interactive Website Development, ensuring that websites are dynamic and provide an engaging user experience. I utilize CSS for Styling, allowing for seamless customisation and visually appealing layouts. Responsive Design is a key priority, enabling websites to adapt smoothly across various devices and screen sizes.I also focus on creating Interactive Buttons that respond intuitively to user actions, enhancing the website’s functionality and user engagement. Task API Integration is another area of expertise, enabling smooth data exchange between the front-end and back-end, allowing users to interact with real-time data seamlessly.For styling, I emphasise Styling and Validation to ensure the design is both visually pleasing and functional. I use Component-Based Styling, where each component has its own style and functionality, making the codebase modular and reusable. This approach not only streamlines development but also ensures that the design is consistent and easy to maintain across the project.

Front-end Developer

As the team leader for the "Automated Bus Management System" project in the Smart India Hackathon, I've helped shape our tech stack to focus on robust AI and data processing solutions to address real-time public transportation challenges with intelligent, adaptive methods.- Programming Language: Python serves as the core language for backend scripting, enabling efficient data manipulation and streamlined development.- Machine Learning &amp; AI Frameworks: &nbsp;- PyTorch and scikit-learn: Used for predictive models to optimise bus schedules, manage routes, and forecast delays. &nbsp;- TensorFlow: Supports deep learning models for advanced, real-time decision-making and pattern recognition.- Data Handling: &nbsp;- Pandas and NumPy: Facilitate data processing, cleaning, and transformation to ensure high-quality training data. &nbsp;- SQL databases: Store structured data. &nbsp;- MongoDB: Manages unstructured data, allowing flexible data processing from various sources.- Cloud Infrastructure: &nbsp;- AWS and Google Cloud Platform: Provide scalable storage and computing power essential for handling large-scale, real-time data streams.- Mapping &amp; Navigation: &nbsp;- Initially using Ola Maps API for localised navigation and route mapping. &nbsp;- Planning to transition to Google Maps API for broader coverage and more robust features in a city-wide deployment.- **Traffic and Weather Prediction**: &nbsp;- Intelligent algorithms analyse traffic and weather data to adjust routes and schedules dynamically, helping buses navigate around congestion and adapt to weather conditions.- Crowd Density Analysis: &nbsp;- An AI model estimates crowd density in buses and at stops to dynamically adjust bus frequency and capacity, matching demand and enhancing commuter experience.This tech stack empowers us to design a responsive, intelligent transit solution that can adapt to both current and future urban mobility needs.

Team Leader

Rishihood University

India

B.Tech student specialize in Computer Science and Artificial Intelligence at Newton School of Technology. Passionate about leveraging technology to solve real-world problems. Experienced in C++ and Java. Enthusiast of machine learning, aiming to contribute to innovative projects. Always eager to learn and grow in the dynamic field of technology.

Ankit Kumar PandeyIndia

Social Accounts

Achievements

Experience

Front-end Developer

Team Leader

Education

Rishihood University

R.D. International School

Army Public School, Delhi Cantt

Certificates

NST Junior Coding Olympiad

Skills