Hrishikesh Reddy

Computer Science (AIML) student

Hyderabad, TG, India
26skills
2education
5credentials

About

Computer Science (AIML) student with projects in deep learning, machine learning, web applications, data analytics, and carbon tracking.

Education

Chaitanya Bharathi Institute Of Technology

B.E., Computer Science (AIML)

2024 – 2028

9.73 CGPA

P. Obul Reddy Public School

High School, Math, Physics, Chemistry, Economics

2021 – 2023

94%

Skills

C/C++PythonJavaSQLJavaScriptHTML/CSSReactTailwindCSSExpress.jsNode.jsFastAPIMySQLMongoDBSQLiteGit/GitHubVS CodeNumPyPandasMatplotlibPlotlyScikit-learnPyTorchPillowData Structures and AlgorithmsObject-Oriented ProgrammingDatabase Management Systems

Projects

Pothole Detection and Road Damage Reporting System

Developed a deep learning system to detect and classify road potholes from images using the YOLOv8 object detection model. Built a REST API using FastAPI to process uploaded images and return identified pothole locations and severity levels. Designed a React-based web interface allowing users to upload road images and visualize detected potholes. Integrated geolocation-based reporting so detected potholes can be mapped and prioritized for municipal repair. Implemented a dashboard to visualize pothole reports and metadata for monitoring road conditions.

Agrithon: Crop Yield Prediction System

Built a regression-based machine learning model to predict crop yield using environmental and soil parameters. Developed a preprocessing pipeline using Scikit-Learn for categorical encoding, feature scaling, and model inference. Created an interactive Streamlit dashboard enabling users to input parameters and obtain real-time yield predictions.

Image Compressor Web Extension

Created a Chrome extension (Manifest V3) that captures the current browser tab and allows users to compress images directly. Built a local FastAPI backend using Pillow to compress images with configurable format (JPEG/WebP), quality, and resizing options. Implemented a browser-based fallback compression mechanism using the Canvas API when the backend server is unavailable.

Footprint: Gamified Carbon Tracking Platform

Architected a full-stack web application to track, visualize, and gamify personal CO2 emissions. Made a custom user authentication system with personalized data storage to manage individual user profiles. Engineered the core tracking and analytics engine to provide real-time visual insights into carbon usage. Designed a gamification module that incentivizes eco-friendly user behavior through measurable reward metrics.