Selected Projects

Data Analysis

• Mammalian Sleep Data Analysis
  Performed exploratory data analysis on the msleep dataset: cleaned data, visualized patterns using ggplot2, and extracted insights on sleep behavior across mammal categories. View full PDF report with plots and tables

• Statistical Analysis and Modeling of the Iris Dataset in R
  Analyzed the Iris dataset in R using statistical and visual techniques. Built regression models to predict sepal length and explored species-specific patterns. Applied the model for practical prediction. View full PDF report with plots and tables

• Predictive Modeling of Diabetes Onset in Pima Indian Women
  Built a logistic regression model using EDA, mean imputation, and AIC-based variable selection to predict diabetes onset with 77.4% accuracy. View full PDF report with plots and tables
• Key skills: R, Tidyverse, Data wrangling, Data visualization, Exploratory data analysis(EDA), Correlation analysis, Linear regression, Logistic regression, Statistical modeling, Model evaluation.

Programming

• Word Counting
  Built a simple text processing tool in Python to tokenize text, remove stopwords, and compute word frequencies. Practiced core programming concepts and explored basic NLP techniques like statistical word analysis. View full PDF report

• Numeral Base Evaluator
  Created a Python script to convert numbers between binary, decimal, hexadecimal, and nonary bases. Built logic dictionaries and implemented conversion with error handling. View full PDF report

• Key tools: Python, dictionaries, lists, string operations, Loops, conditionals, functions, file handling,
  
• Key skills Python Programming Algorithm Design, Numeral System Conversion, Data Validation & Error Handling, Dictionary & List Manipulation, Mathematical Reasoning, Functional Decomposition, Modular Code Structure

Machine learning

• Proposing and implementing a novel deep learning model by using feedforward neural networks and bidirectional long short-term memory (LSTM) to improve the prediction accuracy of protein secondary structure prediction based on benchmark datasets
• Proposing and implementing Reinforcement learning (RL) algorithms such as Q-learning and deep reinforcement learning (DRL) algorithms such as double Deep Q-network (DDQN) for energy management system (EMS) to improve the vehicle energy efficiency and convergence rate based on the data from Alternative Fuels Data Center (AFDC).
• Proposing and implementing the bidirectional long short-term memory (LSTM) network introduced to improve the deep Q-learning-based EMS (Energy manage system) improve the energy efficiency based on the synthesized data.

  Software engineering

• Using Solidworks to create detailed 3D models with complex shapes and geometries, using parametric modeling to govern the behavior of the model and using simulation tools to test and analyze the designs virtually.
• Using Python to simulate real-time sensor data processing and analysis, aiding in decision-making for autonomous systems, predictive maintenance, and performance optimization.
• Using Python to implement the coding, running and testing in the task management system project and using Git to track the project’s version history