Researcher

Yansong Liu

My research focuses on digital health, machine learning, and intervention research at University College London.

Yansong Liu
01. Research

Featured Research

Developing AI-powered remote patient monitoring systems for cancer care, combining wearable technology with advanced machine learning to improve clinical outcomes.

Research Overview

My research focuses on developing AI-powered remote patient monitoring systems for cancer patients undergoing systemic therapy. I work on multi-modal time-series deep learning models to overcome wearable data compliance challenges, predictive algorithms for post-surgical survival, and comprehensive data infrastructure integrating hospital EHR systems with wearable devices. My work addresses critical post-discharge care gaps where 30% of patients are readmitted within 30 days.

AI-Powered Remote Patient Monitoring System for Cancer Systemic Therapy

PhD Research Project (March 2022 - Present) Digital Health Machine Learning Wearable Devices

Developed one of the UK's most advanced wearable monitoring platforms for cancer patients. Led algorithm development implementing multi-modal time-series deep learning models. Secured pre-seed funding from GE Healthcare.

Post-surgical Survival Prediction for Urological Cancer Patients

Multi-center UK Study (January 2022 - June 2024) Machine Learning Clinical Research Predictive Modeling

Conducted retrospective analysis of multi-center clinical dataset from 9 UK hospitals. Developed interpretable XGBoost models improving survival prediction accuracy from 0.67-0.68 to 0.77 AUC.

Digital remote monitoring and machine learning modelling to predict survival following radical cystectomy

European Urology Association Conference 2024 Machine Learning Clinical Research

Secondary outcome analysis of the iROC trial, extended to Journal of Urology

More publications available on Google Scholar

02. Education

Academic Background

From computer science fundamentals to pioneering research in AI-powered healthcare solutions.

PhD in Computer Science • University College London

Artificial Intelligence Remote Patient Monitoring

PhD in Computer Science • September 2021 - May 2026

Thesis: Artificial Intelligence Remote Patient Monitoring: Design, Development, and Clinical Insights. Supervised by Prof. Ivana Drobnjak, Dr. Yukun Zhou, and Prof. John Kelly.

Bachelor in Computer Science • University College London

Computer Science

Bachelor in Computer Science • September 2018 - July 2021

Thesis: Computational modelling in remote monitoring of post-operative patients

03. Experience

Professional Journey

Translating academic research into commercial healthcare solutions, from algorithm development to deployment at scale.

Technical Product Manager - Wearable Medical Devices • Ethera Health UK

Technical Product Manager - Wearable Medical Devices

April 2021 - April 2022

Led commercial deployment of AI-powered remote patient monitoring platform. Conducted comprehensive market analysis of 12+ wearable solutions and scaled deployment across 3 clinical trials covering 1,000 patients. Managed OEM partnerships, international procurement, and regulatory compliance.

Natural Language Processing Algorithm Engineer, Data Analyst • Ling Xi Technology

Natural Language Processing Algorithm Engineer, Data Analyst

June 2020 - September 2020

Contributed to NLP and dialogue generation technology platform. Developed AI models for customer identification achieving 66% accuracy and implemented K-means clustering for 10M user data annotations. Designed sales algorithms generating additional £150K annual revenue (23% increase).

Current Focus

Currently pursuing PhD research in AI-powered remote patient monitoring for cancer care, building on my experience in commercial product management and NLP algorithm development. My work bridges the gap between cutting-edge machine learning research and real-world clinical applications, focusing on improving patient outcomes through data-driven healthcare solutions.

04. Recognition

Awards & Achievements

Recognition for research innovation and contributions to healthcare technology advancement.

Patent: Intelligent Lane Device

CN206591377U • 2017

Patent: Automobile Dustproof Window

CN202325144U • 2011

05. Connect

Get in Touch

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