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I'm an engineer who wants to see things work in real-world settings. I dream far but not sparsely. My research follows the SOP of generating an idea, representing the ideas in mathematical forms, and acting on the ideas / models / products based on a philosophy and inference learning oriented loops of "what, why and how". 

 

My last research fellowship project focused on developing machine learning methods to predictively monitor and manage the health of gestational diabetic women during pregnancy. This health condition affects one in six pregnant women worldwide. Among these women, 50% will become chronic type 2 diabetics within five years. So, it is highly important to identify the high-risk group; therefore, we can delay the progression through earlier interventions.

My current research interests are twofold. One is to develop a health foundation model for time-series data and explore the feasibility of using meta-learning with large language models for explainable AI for health monitoring and disease discovery, thereby reducing digital health disparities, especially for LMICs. The other fold is to exercise the federated learning on Edge for the next generation of mobile health and hospital-at-home.

Current Projects:

  1. SmartEdge, EU project, University of Oxford. (2024 — Current)

  2. Large Language Model (LLM) to Build Frontline Healthcare Worker Capacity in Rural India, Grand Challenge Project funded by the Bills & Melinda Gates Foundation and the George Institute for Global Health. (2023 — Current)

  3. MItigating the Risk of developing type 2 diabetes Associated with GEstational diabetes (MIRAGE), Diabetes UK PhD Studentship, funded by Diabetes UK, UK. (2023-2026)

  4. Clinical study: “Gestational Diabetes Predictive Monitoring and Management“, University of Oxford, UK, in kind support by the NIHR CRN on NHS data and staff costs. (2021 — Current)

  5. Blood Glucose Monitoring for Gestational Diabetes Health and Care: from reactive treatment to preventative medicine, Fellowship project funded by the Royal Academy of Engineering and University of Oxford. (2019 — Current)

 

Completed Projects:

  1. Enterprise and Innovation Research Fellowship, the MPLS Division, University of Oxford, UK. (2022 — 2023)

  2. Oxford Saïd Business School Idea2Impact Fellowship, University of Oxford, UK. (2023)

  3. Development and validation of a non-invasive device for measuring oxygen saturation with automatic adjustment according to altitude and skin color using machine learning algorithms, Enterprise Fellowship project lead by collaborators at Peru, funded by the Royal Academy of Engineering, UK. (2021 — 2023)

  4. Gestational Predictive Monitoring and Management, Oxford John Fell COVID Support Fund, University of Oxford, UK. (2021 — 2022).

  5. Wearable Vital Signs Monitoring for Patients with Asthma, Dr Stephanie Dalley Fund for student internship, Somerville College, University of Oxford, UK. (2021).

Education

University of Liverpool, UK

2015 - 2018

PGCert in Professional Studies in Learning and Teaching in Higher Education,  FHEA accreditation for the UK Higher Education Academy.

University of Sussex, UK

2004 - 2008

D.Phil at the Industrial Informatics and Manufacturing Systems Research Centre, Department of Engineering and Design. Thesis: Recognition Algorithms for Biometrics on Portable Computing Devices It was a commercial project sponsored by xVista Ltd; one patent was filed with my assistance.

Jilin University, China

2000 - 2004

Bachelor of Engineering at the Department of Computer Science and Technology. My dissertation is "Soccer Robot Cart: Hardware and Software Implementations".

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