Alfredo R.

Key Skills

Software

Other

Top Subject Matter

COVID-19 mobility analytics and transmission trend prediction

Molecular-dynamics simulation automation and rare-event dataset generation

Top Data Types

Image

Text

Document

Top Task Types

Classification

Data Collection

Freelancer Overview

Research Assistant, Johnson Lab (X-SIG) — AI/ML-based analysis and predictive modeling using mobility datasets. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Internal, and Proprietary Tooling. Education includes Doctor of Philosophy, University of Vermont (2032) and Bachelor of Science, Gettysburg College (2026). AI-training focus includes data types such as Geospatial, Tiled Imagery, and Computer Code and labeling workflows including Classification and Data Collection.

Labeling Experience

Research Assistant, Powers Lab (X-SIG) — automated ML-oriented data generation from simulation trajectories

Data Collection

Developed and deployed automated trajectory control and rare-event detection workflows for simulation outputs. Used Python tooling to manage simulation runs and detect rare events in molecular-dynamics trajectories, producing structured results for further analysis. Automated data storage and job submission to ensure consistent generation of analysis-ready datasets. • Automated trajectory control via a custom Python package • Rare-event detection from simulation trajectories • Supercomputer deployment and automated job submission • Systematic data storage for downstream analysis

2024 - Present

Research Assistant, Johnson Lab (X-SIG) — AI/ML-based analysis and predictive modeling using mobility datasets

OtherClassification

Conducted analysis of COVID-19 mobility data using geospatial and machine-learning methods in Python, creating ML-ready representations of population movement patterns. Built predictive models of transmission trends by transforming large mobility datasets into structured inputs suitable for supervised learning. Performed data preprocessing using standard scientific Python tooling to support modeling and evaluation. • Geospatial data preparation and feature construction • Machine-learning predictive modeling for transmission trends • Large-scale preprocessing with Pandas/NumPy • Data workflow for downstream ML evaluation

2023 - 2024

Education

Work History