Smart Health Seminar 22-23: Machine learning applied to home-based healthcare monitoring

VinUni-Illinois Smart Health Center (VISHC) is honored to welcome Professor Huy Phan from Queen Mary University of London & Amazon R&D to be the speaker in our upcoming Smart Health Seminar Series.  

1. Short Bio: Professor Huy Phan is Assistant Professor in AI at School of Electronic Engineering and Computer Science, Queen Mary University of London and Turing Fellow at the Alan Turing Institute, UK. Before that, he was a postdoctoral researcher at the University of Oxford and Lecturer in Computing at the University of Kent. His PhD thesis was awarded the Bernd Fischer award for the best PhD thesis by the University of Lübeck in 2018.  In 2021, he was awarded IEEE Engineering in Medicine and Biology Society (IEEE-EMBS) Best Paper Award 2019-2020. 

2. Research Interest

Deep learning/machine learning: Representation learning and algorithms for temporal signal analysis (e.g. audio, speech, EEG, sEMG, fMRI, etc.).

Healthcare Application

  • Brain monitoring
  • Building fMRI biomarkers for brain diseases
  • Pathological voice/speech/language analysis
  • Digital biomarkers for mental health monitoring

Topics: Machine learning applied to home-based healthcare monitoring | Date: Thursday, November 24, 2022 | Time: 4:00 PM  

Location: VISHC Office (3rd Floor, Building G, VinUni Campus) & Zoom Meeting 

Zoom Link: 

Registration Link: 


The ongoing demographic change has posed serious public health issues in many countries around the world, for example, overwhelming health services. With the aim of providing better care for patients, cutting the number of unplanned bed days in hospitals and reducing net costs, strategic changes have been made to deliver more healthcare health services out of acute hospitals and closer to home. Consequently, it raises an urgent need for efficient, accessible, cost-effective, and scalable healthcare solutions that can serve a large population. There is a great opportunity to explore state-of-the-art computational modelling techniques combined with non-invasive, and wearable sensors, actuators and modern communication technologies aimed at transitioning healthcare solutions to home-based environments. The goal is to develop user-friendly wearable devices, new signal processing techniques, and novel machine learning algorithms targeted at home-based health and medical care monitoring applications. This talk will showcase two applications: acoustic monitoring for sound event detection and sleep monitoring with mobile EEG wearable devices. 

This seminar opens for all VinUni students, faculty, staff and partners. We are looking forward to your attendance!