Projects

I completed a number of projects and participated in several hackathons. I have experience using Django and Spring Boot for backend development and prefer React for front-end design. For relational databases, I work with Oracle DB and PostgreSQL. In my deep learning projects, I utilize PyTorch.

Academic Projects

  1. CMSC629: A Case Study on a Website Using Design Principles
    Dataset

    Description: This portfolio documents work completed for HCC 629: Fundamentals of Human-Centered Computing at the University of Maryland, Baltimore County. It presents a structured case study applying seven core interaction design principles to a real-world website, following the DEFINE case study format.

  2. CNN From Scratch
    Libraries: opencv, matplotlib, tqdm, numpy, pandas, pickle, scipy
    Architecture: Convolutional Neural Network (LeNet)
    Dataset

    Description: I developed this CNN-LeNet architecture from scratch (Using a very restricted number of libraries). I used opencv to read files, matplotlib for data visualization, numpy and pandas for data manipulation, and scipy for performance metrics and statistics. The project does not utilize any advanced framework such as PyTorch or Tensorflow. Thus, I had to implement all the layers with both forward and backward propagation. I used MNIST dataset to measure its performance.
    [CODE]

  3. Retinal Disease Classification
    Libraries: numpy, matplotlib, pandas, PyTorch
    Restricted Boltzmann Machine, Convolutional Neural Network (AlexNet)
    Dataset

    Descriptoin: The main objective of this project is to use retinal images to recognize and classify various retinal illnesses, including age-related macular degeneration and diabetic retinopathy. At first, we did some study on several research articles on the related topic and initially decided to choose the Restricted Boltzmann Machine as our architecture for this project. But in the end, we went with a traditional CNN-AlexNet architecture.
    [CODE]

  4. Auc-dais
    Tools & technologies used: Spring Boot, React, Bootstrap, PostgresSQL
    Dataset

    Description: This is an online auction platform that we developed in our software engineering course. We used the Spring Boot framework and PostgresDB to handle the back end of the application and utilized React and Bootstrap to implement the front end of the application.
    [FRONTEND-CODE] [BACKEND-CODE] [VIDEO]

  5. Cricbuzz
    Tools & Technology: JavaFX, Oracle Database
    Dataset

    Description: This is a Java based desktop application inspired by cricbuzz. We developed this application for our Database Management Systems course. However, unlike the cricbuzz web application this is a back-end application designed for administrators. We used JavaFX to implement the graphical user interface of the application and OracleDB to handle the database.
    [CODE] [VIDEO].

  6. Scientific-Calculator
    Tools & Technology: C, Atmel Studio, Proteus, ATmega32, Arduino
    Dataset

    Description: We built this project for our undergraduate course Microprocessors, Microcontrollers, and Embedded Systems. As the name suggests we built a scientific calculator on proteus and wrote a program on Atmel Studio to do the necessary calculations.
    [CODE] [VIDEO].

  7. C-subset Compiler Tools & Technology: C, Flex, Bison

    Description: Description: This project is on the development of a compiler that is a subset of the C programming language. The operations in can handle are as follows: arithmetic operations, functions, recursion, print, comment, loops, variables. The compiler was built step by step, started with the implementation of a symbol table, then lexical analyzer, syntax and semantic analyzer, and finally intermediate code generator. 8086 assembly language was used as the intermediate representation. Code optimization process was also included in the intermediate code generator step.
    [CODE].