Genuis only means hard-working all one’s life.
–Mendeleyev

Hi there! My name is Tong Xia, and I am a second-year PhD student in the Department of Computer Science and Technology, University of Cambridge, Cambridge, UK, supervised by Prof. Cecilia Mascolo. I received my master degree from the Department of Electronics and Engineering, Tsinghua University, China, in 2020, supervised by Prof. Yong Li. Prior to that, I received my bachelor degree in Electronic and Information Engineering from Wuhan University, China, in 2017.

Research Interests

I am interested in data mining, machine learning, deep learning and all kinds of artificial intelligence technologies which can help improve public health and benefit human well-being.

During the coronavirus pandemic era, I have been working on a mobile health project. Specifically, we collect human sounds to set up machine learning models, as a non-invasive and low-cost pre-screening tool, to help screen COVID-19. Visit our website to know more about our findings.

The main objective of my PhD study is the exploration and development of data-efficient, high-performance, and risk-aware automatic diagnosis systems through physiological signals like heart rate and sounds, in order to achieve ubiquitous, affordable, and portable daily illness screening, and diagnosis, monitoring from home. By harnessing the power of small data learning and probabilistic machine learning, I aim to propose novel solutions for the data imbalance and uncertainty estimation obstacles when applying machine learning to reliable health diagnosis. I am also investigating decentralised model training techniques to allow privacy-preserving mobile health applications.

News

• July 2022: I am going to introduce our recent work in MobiUK, 2022, at UCL.
• May 2022: I presented my work at Oxbridge Women in CS conference and I was awarded a Best Postgraduate Poster Prize Poster.
• April 2022: Our COVID-19 Sounds team was awarded a “Better Future Award” in Hall of Fame Awards 2021!
• Jan. 2022: Our paper Sounds of COVID-19: exploring realistic performance of audio-based digital testing was accepted by npj Digital Medicine! (IF2021=15.357).
• Oct. 2021: A paper with a large-scale dataset and competitive benchmarks published in NeurIPS 2021 Datasets and Benchmark Track paper.
• Sep. 2021: I have passed my first-year viva and became a PhD candidate at the University of Cambridge! See my report.
• May 2021: A paper accepted by INTERSPEECH2021.

Awards

• 2022, Best Postgraduate Poster in Oxbridge Women in Computer Science Conference
• 2022, COVID-19 Sounds project awarded as Better Future Award in Hall of Fame Awards, Cambridge
• 2021, ISCA INTERSPEECH Student Travel Grant
• 2020, Oversea PhD Full Scholarship for 2020-2023
• 2020, Distinguished Master Thesis Award by the Chinese Institute of Electronics
• 2020, Outstanding Research Intern, Tencet, Beijing
• 2019, National Graduate Student Scholarship of China
• 2016, Intel Cup Embedded System Invitational Contest, National Third Prize
• 2014, National Undergraduate Student Scholarship of China

Academic Service

I am a reviewer of
• IEEE TNSM
• EPJ data science
and I also serve as a SPC for
• AAAI 2020,2021
• UbiComp 2019, 2020, 2021
• WWW 2020
• KDD 2019, 2021
• IJCAI 2021,2022
• ICASSP 2021

I am serving as UbiComp 2022 Posters&Demos session chair this year.

Teaching

I am also passionate about supervising and I have been a teaching assistant for the following undergraduate courses:

• Artificial Intelligence 2022(Part IB, University of Cambridge)
• Machine Learning & Real-World Data 2022(Part IA, University of Cambridge)
• Foundation of Data Science 2021 (Part IA, University of Cambridge)
• AI Research Project 2021, 2022 (China UK Development Centre, Cambridge Centre for the Integration of Science, Technology and Culture)
• AI in medicine Project 2021 (China UK Development Centre, Cambridge Centre for the Integration of Science, Technology and Culture)