Fanhao Z.

Key Skills

Software

Other

Top Subject Matter

Medical imaging for Alzheimer’s disease diagnosis

Natural language processing for reading assistance (aphasia)

Retail analytics and predictive modeling (inventory, pricing, forecasting)

Top Data Types

Text

Image

Computer Code Programming

Top Task Types

Diagnosis

Fine-tuning

Data Collection

Freelancer Overview

Diagnosis of Alzheimer's disease — main contributor (twin neural network model training). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include PyTorch, Other, and Spark. Education includes Bachelor of Computer Science, The University of Queensland (2023) and Master of Computer Science, The University of Queensland (2024). AI-training focus includes data types such as Medical, DICOM, and Text and labeling workflows including Diagnosis, Fine-tuning, and Data Collection.

Labeling Experience

元数科技 Meta era — Big Data R&D Intern (dataset prep & ML training support)

Data Collection

Worked on big data R&D involving machine learning model development for retail inventory management and pricing optimization. Collected, preprocessed, and analyzed large-scale retail datasets to prepare high-quality inputs for training and evaluation. Conducted feature engineering and model validation to refine algorithm performance for demand forecasting and inventory allocation. • Performed data collection and preprocessing for retail datasets • Built and validated ML features for improved forecasting • Designed intelligent pricing strategies using predictive modeling • Collaborated to ensure data quality for training and evaluation

2025 - 2025

Hikvision — Product Market Team Intern (test-case data collection & feedback)

Data Collection

Assisted product and testing activities that included developing test cases and performing functional and compatibility testing for product delivery quality. Participated in product life cycle management and supported sales and demonstrations, while contributing to product testing feedback loops. Although not explicit AI labeling work, the role supported structured data collection for testing outcomes. • Developed test cases and conducted functional/compatibility testing • Recorded and provided feedback to support product quality • Supported product demonstrations and customer inquiry responses • Assisted with product life cycle follow-ups from initiation to launch

2024 - 2025

Reading aids for people with aphasia — Team Leader (LLM fine-tuning & evaluation)

OtherTextFine-tuning

Led a team to fine-tune a Facebook BART language model to improve reading support for people with aphasia. Focused on adapting the model to users’ reading needs through program development, task assignment, and evaluation of model effects. Conducted iterative assessment to measure improvements in reading comprehension outcomes. • Fine-tuned an LLM (BART) for aphasia reading needs • Developed project program and assigned team tasks • Evaluated model effectiveness based on reading comprehension • Coordinated iterative improvements for better NLP performance

2023 - 2023

Diagnosis of Alzheimer's disease — main contributor (twin neural network model training)

Diagnosis

Contributed to a deep learning project for automated diagnosis of Alzheimer’s disease using brain CT images, focusing on end-to-end model training rather than manual annotation. Led data preprocessing, feature extraction, and model training to improve diagnostic accuracy. Worked with medical image inputs and supervised learning workflows to validate model performance. • Preprocessed brain CT image data for training • Performed feature extraction to support diagnosis • Trained twin neural network models for automated diagnosis • Improved diagnosis accuracy through modeling iterations

2023 - 2023

Education

Work History