Wei

Key Skills

Software

No software listed

Top Subject Matter

AI intelligent detection data governance and dataset labeling quality

Network security traffic data labeling and dataset optimization

Top Data Types

Text

Computer Code Programming

Image

Top Task Types

Classification

Bounding Box

Text Generation

Freelancer Overview

AI Data Algorithm Intern — AI Data Algorithm Intern (NSFOCUS Group Co., Ltd.). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering in Network Engineering, Southwest Minzu University (2026). AI-training focus includes data types such as Text and labeling workflows including Classification.

Labeling Experience

AI Data Algorithm Intern — AI Data Algorithm Intern (NSFOCUS Group Co., Ltd.)

TextClassification

Conducted full-process processing of training samples for AI intelligent detection models, including screening, deduplication, cleaning, and standardized classification labeling. Applied SOP-aligned rules to ensure consistent feature labeling and boundary judgment, and reduced labeling deviations through multi-level self and re-inspection. Performed sample traceability analysis from model feedback to iteratively refine labeling rules and improve recognition accuracy and generalization. • Cleaned and normalized training datasets for AI detection • Implemented standardized labeling and quality inspection workflows • Analyzed mislabeled/missed cases and optimized labeling logic • Built dataset automation for batch sorting, statistics, format conversion, and duplicate removal

2025 - 2025

Data and Algorithm Optimization Member — SDN-based Intelligent DDoS Detection and Defense System (Algorithm Data Optimization Project)

TextClassification

Supported data governance for an SDN-based intelligent DDoS detection system by collecting, cleaning, anomaly screening, and producing labeled training samples for algorithm training. Assisted in establishing an SOP process covering AI data processing, sample labeling, and iteration to improve dataset reliability and downstream model performance. Contributed to optimizing labeling and data selection logic through controlled experiments targeting reductions in false positives and false negatives. • Constructed and optimized structured traffic sample libraries • Performed anomaly screening and feature labeling for training data • Helped tune dataset and thresholds based on recognition feedback • Participated in SOP definition for AI data processing and labeling

2023 - 2024

Education

Work History