ABOUT ME

Introduction

Jay Charangat

I am a senior Computer Science and Mathematics student at the University of Maryland, College Park, specializing in Machine Learning and Statistics. I'm passionate about using data to help solve real-world problems and make an impact.

My technical experience includes Python, SQL, Java, R, SAS, and MATLAB, with hands-on experience developing end-to-end AI and data projects spanning data ingestion, transformation, business analysis, predictive modeling, computer vision, and natural language processing.

Throughout my professional experience, I have developed hands-on experience with industry tools such as Excel, Microsoft Fabric, Power BI, and Power Automate. I have also gained experience working with financial data.

As I approach graduation, I'm actively seeking full-time opportunities in Machine Learning, Artificial Intelligence, Data Science, Data Analytics, or Software Engineering. I'm excited to apply my technical and analytical skills to meaningful problems while continuing to learn and grow professionally.

MY WORK

Featured Projects

AI / NLP / COMPUTER VISION

Document Intelligence RAG Pipeline

An AI-powered document processing pipeline combining OCR, computer vision, natural language processing, and retrieval-augmented generation to extract and retrieve information from documents. Inlcudes a user friendly interface for uploading documents and querying information.

Python OCR NLP RAG
View GitHub →

DATA SCIENCE / ANALYTICS / VISUALIZATIONS / ML

Tree Risk Analysis

An interactive Power BI dashboard analyzing vegetation risks near utility infrastructure using Python, SQL, Microsoft Fabric, and large-scale environmental government data. Conducts health and risk analysis of trees to predict potential hazards and provide actionable insights for utility companies to mitigate risks and ensure public safety.

Python Microsoft Fabric Power BI SQL DuckDB Pandas/GeoPandas
View GitHub →

MACHINE LEARNING / NLP

Sentiment Analysis Classifier

A machine learning classifier that analyzes text and predicts sentiment using natural language processing, feature engineering, and model evaluation techniques.

Python scikit-learn NLP
View GitHub →

DATA SCIENCE / ML

Global GDP Prediction Model

A data science project analyzing global economic trends using exploratory data analysis and statistical hypothesis testing, including t-tests, ANOVA, and post-hoc analysis. Developed a neural network model to identify relationships between demographic, geographic, and political factors and GDP, and predict economic output based on country characteristics.

Python Pandas Numpy Matplotlib Seaborn SciPy PyTorch scikit-learn
View GitHub →

TECHNOLOGIES

Skills

Programming Languages

Python Java SQL R Rust SAS C MATLAB OCaml x86 Assembly

Machine Learning

PyTorch scikit-learn TensorFlow Keras NLP Computer Vision OCR RAG Pipelines

Data Transformation, Analytics, and Visualizations

Pandas NumPy Microsoft Fabric Power BI Power Automate Matplotlib Seaborn Tableau Alteryx

Tools

Git/Github Microsoft Office (Excel, Word, Access) VS Code Jupyter

ACADEMIC BACKGROUND

Relevant Coursework

Computer Science

  • Algorithms (CMSC 351)
  • Applications of R for Data Science (DATA 110)
  • Artificial Intelligence (CMSC 421)
  • Capstone in Machine Learning (CMSC 473)
  • Computational Methods (CMSC 460)
  • Computer Systems (CMSC 216)
  • Data Management (BSOS 180)
  • Data Science (CMSC 320)
  • Discrete Structures (CMSC 250)
  • Machine Learning (CMSC 422)
  • Natural Language Processing (CMSC 470)
  • Object-Oriented Programming I & II (CMSC 131 & CMSC 132)
  • Organization of Programming Languages (CMSC 330)
  • Python Programming for Data Science (DATA 120)
  • Web Application Development with JavaScript (CMSC 335)

Mathematics & Statistics

  • Actuarial Mathematics (STAT 470)
  • Applied Probability and Statistics I & II (STAT 400 & STAT 401)
  • Calculus I-III (MATH 140, MATH 141, MATH 241)
  • Differential Equations (MATH 246)
  • Introduction to MATLAB (MATH 206)
  • Linear Algebra (MATH 461)
  • Linear Optimization (MATH 423)
  • Statistical Computing with SAS (STAT 430)

Interested in my experience?

Take a look at my resume for more information about my education, experience, and technical background.

View Resume

CONTACT ME

Let's Connect

I'm always interested in connecting with people working in machine learning, AI, data science, or software engineering.

GitHub LinkedIn Email: jaycharangat@gmail.com