Hello! Welcome to my portfolio

I'm Mahendra Murari

Full Stack Developer

UI/UX Designer

Data Enthusiast

React Developer

Let Me Introduce Myself

Hi, I’m Mahendra — a full stack developer with a strong interest in UI design. I enjoy building web applications that not only work well but also look and feel great for users.

What I do:

    UI-Focused Frontend: I design and develop clean, modern interfaces using React.js, JavaScript, and CSS, with attention to layout, accessibility, and visual consistency.

    User-Centered Thinking: I apply basic UI/UX principles to improve usability and deliver better customer experiences.

    Backend Development:I build robust APIs using Java and Spring Boot, connecting them seamlessly to databases with Spring Data JPA.

    End-to-End Delivery:I manage full-stack workflows using Git, GitHub Actions, and CI/CD tools — from frontend polish to backend logic.

FIND ME ON

Feel free to reach-out.

© 2025 Mahendra Murari. All rights reserved.

Contact for inquiries

University of Bridgeport, CT, USA

Master of Science in Computer Science

Relevant Coursework: OOP With Design Patterns, Analysis of Algorithms, Web Application Development, Python for Data Science, Deep Learning, NLP, Ethical Hacking


Gudlavalleru Engineering College, Andhra Pradesh, India

Bachelor of Technology in Computer Science and Engineering

Relevant Coursework:Data Mining, Data Structures, Python, DBMS, C, OOP Through Java, WEB Technologies, Project Management

Technical Skills

Languages: Python, SQL, Java, HTML, CSS, JavaScript (ES6+)

Databases: MySQL, Microsoft SQL Server

Frontend: React.js, Bootstrap, Tailwind CSS, Flexbox, Media Queries

Tools: Git, GitHub, VS Code, Chrome DevTools

Visualization: Excel, Power BI, Tableau (basic)

APIs: Worked with REST APIs for data integration

Testing: Basic understanding of unit testing and debugging techniques

UI/UX Development

Design Tools : Figma (or Adobe XD/Sketch for wireframing and prototyping)

Wireframing : Creating basic layouts and user flows

Prototyping : Building interactive prototypes for user feedback

Design Principles : Understanding of typography, color theory, and visual hierarchy

Soft Skills

Eagerness to learn and adapt to new technologies

Strong problem-solving and logical thinking

Attention to detail in design and code

Good communication and teamwork skills

Time management and ability to meet deadlines

Creativity and a user-focused mindset

Tools & Technologies

Code Editors : VS Code, Sublime Text

Version Control : Git, GitHub

Design Tools : Figma, Adobe XD, Canva (for basic designs)

Projects & Learning

Built responsive websites using HTML, CSS, and JavaScript

Designed wireframes and prototypes for personal and academic projects

Practiced debugging and improving website performance

Contributed to open-source projects and collaborated on GitHub

My Work

01

Real Estate Management Platform

UI/UXReact.jsFigmaProfessional

A responsive platform designed to modernize the property search and booking experience. As the UI/UX Developer, I translated user research into a seamless and intuitive digital product.

Key Contributions

  • Built a responsive real estate web platform featuring dynamic property listings, a "recently sold" carousel, and customer testimonial sections to improve user engagement and site credibility.
  • Designed and implemented a conversion-focused hero section with clear Calls-to-Action (CTAs) for viewing listings, contacting agents, and searching for homes.
  • Engineered reusable frontend components using **React** and advanced **CSS (Grid/Flexbox)**, ensuring a consistent and performant experience across all devices and browsers.
  • Developed a powerful property search and filtering system (by location, price, and type) by integrating **RESTful APIs** to fetch and display real-time data.
  • Collaborated with the backend team to implement secure **CRUD operations** for property management and designed API structures to support future analytics and automation.
Real Estate UI Mockup 1
Real Estate UI Mockup 2
Real Estate UI Mockup 3
02

Plant Seedling Classification

Deep LearningCNNPythonInternship

An AI system using a custom Convolutional Neural Network (CNN) to accurately identify 12 different plant species, helping to distinguish crops from weeds in precision agriculture.

Key Contributions

  • Developed a deep learning image classification system to identify 12 different species of plant seedlings from a dataset of over 4,700 labeled images.
  • Implemented extensive data preprocessing and augmentation, including image resizing, normalization, rotation, and flipping, to improve the model's ability to generalize.
  • Utilized transfer learning by building upon the pre-trained Xception CNN architecture, fine-tuning it for this specific classification task.
  • Customized the deep learning model by adding Flatten and Dense output layers to the Xception base, tailoring it to the 12 specific plant classes.
Plant seedling classification UI
Augmented training data for plants
Augmented training data for plants
Augmented training data for plants
Augmented training data for plants
Augmented training data for plants
03

Diabetes Prediction ML App

Machine LearningScikit-learnGradio

An end-to-end machine learning application that predicts diabetes risk from medical data and provides a real-time web interface for users, achieving 77.9% accuracy.

Key Contributions

  • Developed a predictive model to identify diabetes risk using the PIMA Indians Diabetes dataset (768 patient records, 8 medical features).
  • Managed the dataset within a PostgreSQL database, utilizing SQL queries to extract and prepare data for model training.
  • Conducted comprehensive data preprocessing, including feature scaling, handling of missing values, and visualizing feature correlations.
  • Identified Logistic Regression as the optimal model, achieving **77.9% accuracy**, after evaluating a suite of seven ML algorithms.
  • Deployed the final model as an interactive web application using Gradio, enabling real-time predictions from user inputs.
Gradio web interface for diabetes prediction
Data correlation heatmap for diabetes features
Data correlation heatmap for diabetes features
04

IoT Accident Detection and Prevention System

IoTHardwareArduino

A hardware prototype that integrates multiple sensors to prevent vehicle accidents and automatically sends a GPS location alert upon crash detection.

Key Contributions

  • Engineered an end-to-end IoT safety system designed to prevent accidents and provide automated emergency reporting.
  • Programmed an ATmega328P microcontroller using the Arduino IDE as the central processing unit.
  • Integrated an MQ3 alcohol sensor to detect driver alcohol consumption and automatically immobilize the vehicle.
  • Utilized a MEMS sensor and an accelerometer for real-time crash and fall detection.
  • Implemented a GPS module and a GSM module to automatically send an SMS alert with the vehicle's precise coordinates upon crash detection.
Full view of the IoT hardware prototype board
Close-up of the microcontroller and sensors
Close-up of the GPS and GSM modules
Close-up of the microcontroller and sensors
Close-up of the microcontroller and sensors
Close-up of the microcontroller and sensors
Close-up of the microcontroller and sensors
Close-up of the microcontroller and sensors
05

Driver Drowsiness Detection

Computer VisionOpenCVDlib

A real-time application that uses a webcam to track a driver's eyes, calculating eye aspect ratio to detect fatigue and trigger an alert.

Key Contributions

  • Developed a real-time computer vision application in Python to detect driver drowsiness using OpenCV and Dlib.
  • Utilized Dlib's pre-trained 68-point facial landmark predictor to accurately map and track the coordinates of a driver's eyes.
  • Engineered the core detection logic by implementing the Eye Aspect Ratio (EAR) algorithm to quantify eye opening in real-time.
  • Designed a system to monitor the EAR value over consecutive frames and trigger an alert if it drops below a calibrated threshold.
  • Integrated a multi-level alert system with an audible alarm and a secondary email notification with geo-location.
Drowsiness detection system showing 'Active' state
Drowsiness detection system showing 'Sleeping' state

Feel free to reach out for inquiries or potential roles

Open to new opportunities and collaborations! If you're looking for a dedicated professional to bring value to your team or project, let’s connect.