Jordan M.

Key Skills

Software

Other

Top Subject Matter

Machine learning for polymer biodegradation materials discovery

Supervised learning model training (linear regression)

Experimental physics data collection and preprocessing

Top Data Types

Text

Computer Code Programming

Top Task Types

Text Generation

Data Collection

Freelancer Overview

ML Materials Discovery Research (LLM + regression; data cleaning/organization). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Georgia Institute of Technology (2027) and Bachelor of Science, The Pennsylvania State University (2024). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Text Generation, Computer Programming, and Coding.

Labeling Experience

ML Materials Discovery Research (LLM + regression; data cleaning/organization)

OtherTextText Generation

Worked on an ML materials discovery research project involving using LLMs alongside regression models for polymer biodegradation analysis. Conducted data cleaning and organization as part of preparing datasets for modeling and parameter tuning. Applied iterative tuning to improve model performance and alignment with research targets. • Cleaned and organized collected polymer biodegradation data for downstream modeling • Used LLMs and regression models together for analysis • Performed parameter adjustment and tuning • Focused on preparing model-ready training inputs

2026 - Present

Linear Regression Model (Python training & evaluation)

Other

Built and trained a linear regression model in Python to fit multiple datasets. Applied data processing and error minimization concepts to improve fit quality. Studied overfitting and underfitting to understand training outcomes on different datasets. • Programmed linear regression in Python • Trained models to find linear fits across multiple datasets • Applied data processing and error minimization • Learned over/underfitting behavior for model tuning

2025 - 2025

ML Heat Transfer (gradient boosting; model training)

Other

Participated in a machine learning heat transfer research project focused on developing universal heat transfer correlations. Applied gradient boosting machine learning techniques to provided datasets to learn correlation parameters. Collaborated with undergraduate/graduate team members on research tasks and model development. • Developed heat transfer correlations using ML • Applied gradient boosting to training datasets • Worked collaboratively on modeling and research deliverables • Used Python-based ML workflows for experimentation and results

2024 - 2025

Muon Detector (data import/processing for analysis)

OtherTextData Collection

Performed a physics research project building a muon detector and processing measurement data with Python. Managed data import and preprocessing steps to support analysis and presentation of results. Conducted troubleshooting on the hardware and associated circuits to ensure usable data for downstream evaluation. • Built muon detector hardware using a plastic scintillator • Wrote Python code to import and process detector data • Troubleshot circuits to improve data quality • Presented project findings and analysis to class

2024 - 2024

Education

Work History