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

Hi there! My name is Tong Xia, and I am a finishing PhD student about to start as a postdoctoral research associate in the Department of Computer Science and Technology at the University of Cambridge, UK, supervised by Prof. Cecilia Mascolo. I received my master’s 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’s degree in Electronic and Information Engineering from Wuhan University, China, in 2017.

I am on the 2024 academic job market.

Research directions

Deep learning for modelling behavioural and physiological data:

• Deep learning for audio signals to predict respiratory and cardiovascular diseases, from early screening [KDD’20,NPJ Digital Medicine’22, NeurIPS’21] to longitudinal minitoring [JMIR’22, KDD’23]
• Deep learning for electrocardiogram (ECG) data, particularly those collected by mobile devices, for detecting heart abnormalities [JBHI’24].
• Data mining and machine learning algorithms to model complex human behaviours like individual [UbiComp’18] and collective [UbiComp’19, TKDD’21, TKDE’21] mobility patterns.
• Sequantial deep learning and graph neural networks for app usage behaiour modelling and prediction [UbiComp’20, TIST’2020].

Big data and AI for public health:

• Big data techniques to understand the impact of urban environmental factors on public health [Scientific data’23].
• Mobility intervention strategies for pandemic control and devising state-of-the-art intelligent interventions [BigData’21, KDD’22].

Trustworthy AI for human-centric applications:

• Data-efficient transformer neural network for humman mobility data generation [AAAI’21].
• Uncertainty quantification for safty-critial health applications [INTERSPEECH’21, CinC’22,TKDD’23, JBHI’24].
• Decentrialized and privacy-preserving machine learning models for real-world applications [ICASSP’21, KDD’24].

To date, I have published over 50 peer-reviewed papers, including 9 in top-tier journals and 13 at CCF A-level conferences. My Google Scholar citations exceed 1500, and my h-index is 18. Through these projects, I have fostered close collaborations and connections in the industry with companies like Nokia Bell Labs, Tencent, and Huawei Cambridge.

News

• July 2024: I gave a seminar at City University of Hong Kong link.
• May 2024: Our paper FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation was accepted by KDD 2024.
• May 2024: I recived my PhD degree.
• March 2024: I passed my PhD viva!
• Feb. 2024: I gave a guest lecture on Generative AI for mobiel health, check from here pdf
• Jan. 2024: I have submitted my PhD Thesis!
• Oct. 2023: Our workshop FairComp at UbiComp2023 was completed with great success!
• Sep. 2023: I start a new role - postdocal research assitant in Cambridge!
• July 2023: Congrats to Evelyn - the first MPhil I co-supervised, graduated from Cambridge with distinction. Also, she has been awarded a commended dissertation award by the department - one of the 4 prizes awarded for dissertations in computer science.
• March 2023: My paper Cross-device Federated Learning for Mobile Health Diagnostics: A First Study on COVID-19 Detection was accepted by IEEE ICASSP, check out the pre-print.
• December 2022: Welcome to our poster - Hybrid-EDL at Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022.
• Nov. 2022: We are delighted that my teammate and I got Third Place in the Intelligent Medical Track in the 2022 World Privacy-Preserving Computing Competition (WPPCC 2022)!
• 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.

Awards

• 2023, Chinese Government Award for Outstanding Self-financed Students Abroad, UK
• 2022, 2nd POSTER AWARD in Precision Health Initiative Launch Symposium, Cambridge
• 2022, Third Place of lntelligent Medical Track in 2022 World Privacy-Preserving Computing Competition (WPPCC 2022)
• 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, Overseas PhD Full Scholarship for 2020-2023
• 2020, Distinguished Master Thesis Award by the Chinese Institute of Electronics
• 2020, Outstanding Research Intern, Tencent, 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, TMC
• EPJ data science
and I also serve as an SPC for
• AAAI 2020,2021
• UbiComp 2019, 2020, 2021
• WWW 2020
• KDD 2019, 2021
• IJCAI 2021,2022, 2023
• ICASSP 2022, 2023

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)