Yucheng M.

Key Skills

Software

No software listed

Top Subject Matter

Engineering data validation and technical documentation review

Control system modeling validation and performance evaluation

Legal Services & Contract Review

Top Data Types

Document

Text

Top Task Types

Classification

Entity (NER) Classification

Question Answering

Text Summarization

Evaluation/Rating

RLHF

Prompt + Response Writing (SFT)

Data Collection

Text Generation

Function Calling

Fine-tuning

Freelancer Overview

R&D Intern Engineer — Amphenol Mobile Connector Systems (Changzhou) Co., Ltd.. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and MATLAB. Education includes Master of Science, University of Leeds (2025) and Bachelor of Engineering, Changzhou University (2024). AI-training focus includes data types such as Document and labeling workflows including Evaluation and Rating.

Labeling Experience

ControlSystemDesign Course Project — MATLAB/Simulink

Document

Conducted evidence-based evaluation of simulation-generated system performance using quantitative metrics and comparative testing results. Validated simulation models through iterative testing, performance evaluation, and stability assessment to ensure correctness of outcomes. Produced structured technical reports and visualizations to communicate analysis findings and model verification results. • Performed quantitative evaluation and comparisons • Validated model performance through iterative testing • Used root locus and step response testing for assessment • Authored structured reports and presented results

2024 - 2024

R&D Intern Engineer — Amphenol Mobile Connector Systems (Changzhou) Co., Ltd.

Document

Reviewed complex technical documentation and verified information consistency across multiple sources for engineering validation needs. Analyzed technical datasets to identify anomalies and produced structured findings that supported quality improvement decisions. Evaluated validation results and offered evidence-based recommendations to enhance data quality and downstream decision-making processes. • Verified cross-source consistency • Identified anomalies in technical datasets • Produced structured technical analysis reports • Recommended improvements based on validation evidence

2023 - 2023

Education

Work History