Marc Wolpert

Computer Science Graduate & Full-Stack Developer

Specializing in JavaScript, TypeScript, React, Node.js, and Next.js with machine learning research experience.

About Me

Recent Computer Science graduate with hands-on experience in full-stack development and machine learning research experience

Background

I'm Marc Wolpert, a Computer Science graduate from UNLV with a passion for creating innovative web applications. I bring fresh perspectives and cutting-edge technical skills to every project I work on.

My background spans from machine learning research analyzing 100,000+ physics data points to full-stack development with modern frameworks. I thrive on rapid learning and applying complex concepts to solve real-world problems.

Core Strengths

Problem SolvingQuick LearningTeam CollaborationInnovation Focus

What I Do

Full-Stack Development

React, Next.js, Node.js, TypeScript, JavaScript (ES6+)

Machine Learning Research

Python, TensorFlow, PyTorch, Data Analysis, HDBSCAN

DevOps & Tools

Docker, Git, Testing, Cloud Computing, REST APIs

Experience & Education

Bachelor of Science in Computer Science

University of Nevada, Las Vegas

2024

Relevant Coursework: Algorithms, Data Structures, Machine Learning, Operating Systems, Cloud Computing, Databases

Machine Learning Researcher

University of Nevada, Las Vegas

February 2023 - May 2024
  • Developed a machine learning model analyzing 100,000+ physics data points, discovering previously unidentified patterns
  • Implemented HDBSCAN in multiprocessing environment using Bayesian optimization for globally optimal clustering
  • Applied Principal Component Analysis to reduce dimensionality from 304 to 12 dimensions
  • Contributed to the discovery of 4 distinct clusters using sophisticated ML techniques

Featured Projects

Music Transcription Application

August 2023 - December 2023

Led a team of 5 to develop a deep learning app that transcribes live audio into sheet music, reducing costs from $22/hr to under $0.01/hr.

TensorFlowPyTorchNeural Networks30K+ Datasets

Map Analogy

In Progress

When going to a new city, it's hard to know where is safe and where is not, along with the places that are expensive and the places that are cheap. Map analogy uses machine learning to relate a big city you're familiar with to where you're currently traveling to.

Next.jsTypeScriptMachine LearningPython

Pollyglot - Language Learning

In Progress

Learning a new language is hard, and the difficulty to learning the vocabulary is not intuitive. This system scales the difficulty so that you're always challenged but not overwhelmed, and seeing the words in-context as you learn them in real world usage.

Next.jsTypeScriptMachine LearningPython

Technical Skills

Languages

JavaScript (ES6+)TypeScriptPythonCC++HTMLCSSSQLAssembly

Full-Stack

ReactNext.jsNode.jsExpress.jsTailwindREST APIsResponsive DesignFigma

Tools & ML

DockerGitGitHubPyTorchTensorFlowPandasMatplotlibTestingWebpack

Let's Connect

Ready for new opportunities and collaborations!