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J
Jet L.

Jet L.

Research Associate – Algoverse Research

USA flagBozeman, Usa

Key Skills

Software

AWS SageMakerAWS SageMaker
CVATCVAT
Deep SystemsDeep Systems
Google Cloud Vertex AIGoogle Cloud Vertex AI
RoboflowRoboflow

Top Subject Matter

Clinical Prediction
Fairness in Machine Learning

Top Data Types

TextText
Computer Code ProgrammingComputer Code Programming
ImageImage

Top Task Types

PolygonPolygon
PolylinePolyline
SegmentationSegmentation
Text SummarizationText Summarization
Evaluation/RatingEvaluation/Rating
Data CollectionData Collection
Function CallingFunction Calling
Computer Programming/CodingComputer Programming/Coding

Freelancer Overview

Research Associate – Algoverse Research. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes High School Diploma, Bozeman High School (2027). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

RAPTOR

ImageImageSegmentationSegmentation

An AI-powered waste system that uses computer vision to identify items in real time and automatically route them to the correct bin (recycling, compost, or landfill). By combining a camera, a trained vision model, and simple mechanical sorting.

2026 - Present

Research Associate – Algoverse Research

TextText

I led a research team developing AI models focused on clinical prediction tasks, which involved training, evaluating, and optimizing transformer-based architectures. I implemented and executed bias mitigation methods for model fairness, performing subgroup reweighting, threshold optimization, and calibration of prediction models. I analyzed model outputs using various metrics, including AUROC/AUPRC and subgroup analysis, to ensure reliable evaluation across demographic groups. • Developed model evaluation pipelines for medical and demographic text datasets • Applied fairness-aware evaluation strategies to AI model outputs • Contributed to the research as primary author, validating results for publication • Utilized Python-based deep learning libraries for model performance assessment.

2025 - Present

ICEMAN

ImageImagePolygonPolygon

The Intelligent Condition & Environmental Monitoring Aerial Network (ICEMAN) is a project designed to detect and report hazardous road conditions that can endanger drivers. It works through three components: an autonomously flying drone, a YOLOv8 model running on a Raspberry Pi, and client-side software that displays real-time detection results.

2026 - 2026

Education

B

Bozeman High School

High School Diploma, General Studies

High School Diploma
2024 - 2027

Work History

S

Self-Employed

Private Tutor

Bozeman
2025 - Present
B

Bozeman High School Coding Club

Club Founder and President

Bozeman
2025 - Present