Hello, I am Jiale Zhang, an Applied Scientist with experience in healthcare-focused AI. Currently, I work at Dami and Xiaomi in Shenzhen, where I develop AI tools to support autism intervention. Previously, I worked at Mindray Bio-Medical Electronics, where I applied machine learning to improve blood testing for early sepsis detection. I hold an M.S. in Computer Science from the University of Leeds (2020) and a B.S. in Information and Computing Sciences from Shenzhen University (2019).
I am passionate about advancing research in AI Agents, Large Language Models, Medical Image Analysis and Human-Computer Interaction and am eager to contribute to impactful innovations in these fields through a Ph.D.
MSc in Advanced Computer Science (Artificial Intelligence), GPA 3.55/4.0, Dissertation with Distinction
University of Leeds, 2020
BSc in Information and Computing Sciences
Shenzhen University, 2019
AI for autism intervention: Developing an integrated AI system for childhood autism that generate evaluation reports, personalized intervention strategies and post-intervention plans based on patient data analysis.
Project 1:LLM-based Clinical Decision Support System (LLM-CDSS) for Autism Spectrum Disorder
Project 2:AI-Powered Interactive Story Generation Platform for Children with Autism
AI for hematology analyzer: Leveraging machine learning to enhance hematology analyzers, enabling cost-effective and rapid early diagnosis of sepsis through advanced blood cell counting and classification techniques.
Project 1: Advancements in AI-Based Hematological Analysis
Project 2: Innovative Sepsis Diagnosis Research
AI in Surgical Enhancement: Enhancing laparoscopic surgery by mitigating visibility issues due to smoke, and enabling precise tissue targeting in dynamic environments for ultrasound-guided HIFU therapy through advanced predictive modeling.
Project 1: Efficient Model for Medical Image Enhancement
Project 2: Spatiotemporal Model for Soft Tissue Motion Prediction
Data Mining in Social Media: Utilizing machine learning and feature engineering to extract valuable information from social media data, enabling more effective ad targeting by identifying user preferences and trending topics.
Project: Innovative Advertisement Video Recognition Method
Machine Translation: Addressing the complexity of translating concise and allusion-rich ancient Chinese into understandable modern language through advanced neural network technology.
Project: Neural Network for Machine Translation