Hello, I am Rishik Reddy

I am an aspiring Software Developer with a passion for building innovative web and mobile applications while diving into cutting-edge libraries and frameworks. I am currently pursuing my 3rd year of a bachelor's degree in Computer Science at SR University, where I’m immersed in learning and experimenting with emerging technologies in the software industry. My journey so far includes working on projects involving technologies such as Python, Java, React, Next.js, APIs, AI, SQL, MongoDB, and more. My journey is fueled by a love for coding and a curiosity for emerging technologies, which keeps me striving to learn and grow.

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Education

Bachelor of TechnologyComputer Science and Engineering
SR UniversityCGPA: 9.4
2022 - 2026

Skills

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Projects

Web Application: Paradise Resorts
  • Created a static web app featuring sections for 4 room types, activities, and special events, along with a customer support page, providing comprehensive resort information.
  • Ensured the site was responsive across devices, resulting in a 20% increase in user engagement during testing.
  • Applied a Maldives-inspired theme and optimized load times and navigation, leading to a 15% increase in positive design feedback and a smoother user experience.
Tech used: HTML, CSS, JavaScript, React, Github
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Scholar’s Companion
  • Developed an educational tool to track and improve academic performance, featuring an attendance tracker to meet goals and a score calculator for achieving target grades.
  • Created an attendance analysis tool that calculates the number of classes needed to maintain at least 75% attendance per subject, aiding academic planning.
  • Engineered an algorithm to determine the required scores for the second midterm to meet final semester targets, using a weighted rule (75% of the highest score and 25% of the lowest).
Tech used: C, Data Structures and Algorithms
Scholar Companion Image
Tic Tac Toe AI
  • Developed a Python-based Tic-Tac-Toe game with an AI-driven opponent utilizing decision-making algorithms for optimal move selection.
  • Engineered a dynamic, turn-based gameplay system that seamlessly integrates user inputs with automated AI responses, enhancing interactivity.
  • Designed and implemented a strategic AI decision-making mechanism, incorporating conditional logic and move evaluation techniques to optimize gameplay outcomes.
Tech used: Python, Artificial Intelligence
Restaurant Order Management System
Developed a dynamic food ordering system using C and linked lists, enabling efficient order management for small-scale restaurants. Implemented features for order addition, search, display, deletion, and total sales calculation. Ensured optimized data retrieval, seamless order tracking, and dynamic memory management to enhance system scalability and performance.
CO2 Emissions Prediction
Designed and implemented a predictive model for CO2 emissions using linear regression on vehicle fuel consumption data. Used Scikit-learn for model training and evaluation, achieving performance metrics through R² score and Mean Squared Error (MSE).Integrated data preprocessing and visualized insights with Matplotlib, showcasing expertise in machine learning and environmental analytics.
Image Recognition System
Developed a Convolutional Neural Network (CNN) for handwritten digit classification using the MNIST dataset. Employed Keras with the Adam optimizer and categorical cross-entropy loss to achieve high accuracy in image classification. Showcased deep learning proficiency, model training, evaluation, and deployment for AI-driven image processing applications.
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