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I am Ian, a third-year PhD student in the Department of Computer Science and Technology at the University of Cambridge, where I am supervised by Professor Cecilia Mascolo. I am a member of Hughes Hall, Cambridge and a Cambridge Trust Scholar. My research is supported by the Doris Zimmern Charitable Foundation, Cambrdige Trust and Nokia Corporation.
-I am interested in deep learning applications, especially on mobile systems. I am currently working on building scalable human activity recognition systems using semi-supervised learning techniques, which include contrastive learning, self-supervised learning and self-training.
- During my masters studies, I worked on collaborative activity recognition systems which leverage signals from multiple devices for better recognition efficiency and performance, under the supervision of Dr Robert Harle. In the summer of 2018, I worked at the Bioinformatics Algorithms and Core Technology Research Laboratory of the University of Hong Kong, on the development of an accurate germline small variant calling system powered by deep neural networks. I received my bachelor degree in Computer Science from the University of Hong Kong in 2018. + I am a Research Scientist in AI/ML in Mobile Systems at Nokia Bell Labs Cambridge and a former PhD student at the Mobile Systems Research Lab, University of Cambridge. + + My work focuses on developing data-efficient and scalable machine learning algorithms, particularly for mobile systems. I specialize in developing robust AI models that can handle complex, real-world scenarios by leveraging data-efficient approaches, including semi-supervised and self-supervised learning. +
++ My key research areas include: +
++ I am passionate about leveraging AI to advance human-centric applications, from healthcare to mobile systems. By developing robust and scalable solutions, I aim to contribute to the future of ubiquitous computing, creating technologies that seamlessly integrate into and enhance our daily lives.
- +- June 2022 - I am starting a research internship at Nokia Bell Labs (Cambridge), conducting research in machine learning on heterogenous edge devices. + September 2024 - I will be running the second version of the UbiComp SOAR Tutorial on solving the activity recognition problem from 1:00 PM to 5:00 PM on October 6 at Melbourne Australia. Come and join us for an exciting discussion!
-- May 2022 - Source code for "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering" has been released on GitHub. -
-- May 2022 - Paper "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering" has been accepted for presentation in ICML 2022 and is now available on arXiv. -
-- May 2022 - Presented "Improving Feature Generalizability with Multitask Learning in Class Incremental Learning" at ICASSP 2022. Recorded talk available here. -
-- March 2022 - Paper "ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition" has been published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). + +
+ June 2022 - I am starting a research internship at Nokia Bell Labs (Cambridge), conducting research in machine learning on heterogenous edge devices. +
++ May 2022 - Source code for "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering" has been released on GitHub. +
++ May 2022 - Paper "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering" has been accepted for presentation in ICML 2022 and is now available on arXiv. +
++ May 2022 - Presented "Improving Feature Generalizability with Multitask Learning in Class Incremental Learning" at ICASSP 2022. Recorded talk available here. +
++ March 2022 - Paper "ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition" has been published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). +
++ March 2022 - A set of notes on Lambda calculus "How to Use the Y Combinator" has been uploaded to this website, as complementary materials for the course Computation Theory (2021-2022). +
++ June 2021 - Source code for "SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data" has been released on GitHub. +
++ April 2021 - Paper "SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data" has been published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). +
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- March 2022 - A set of notes on Lambda calculus "How to Use the Y Combinator" has been uploaded to this website, as complementary materials for the course Computation Theory (2021-2022).
+ Balancing Continual Learning and Fine-tuning for Human Activity Recognition
+ Chi Ian Tang, Lorena Qendro, Dimitris Spathis, Fahim Kawsar, Akhil Mathur, Cecilia Mascolo
+ In AAAI 2024 Workshop: Human-Centric Representation Learning (HCRL)
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- June 2021 - Source code for "SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data" has been released on GitHub.
+ Kaizen: Practical Self-Supervised Continual Learning With Continual Fine-Tuning
+ Chi Ian Tang, Lorena Qendro, Dimitris Spathis, Fahim Kawsar, Cecilia Mascolo, Akhil Mathur
+ In WACV 2024 (IEEE/CVF Winter Conference on Applications of Computer Vision)
- April 2021 - Paper "SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data" has been published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT).
+ Self-supervised learning for data-efficient human activity recognition
+ Chi Ian Tang
+ PhD Thesis
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+ Solving the sensor-based activity recognition problem (SOAR): self-supervised, multi-modal recognition of activities from wearable sensors
+ Harish Haresamudram, Chi Ian Tang, Sungho Suh, Paul Lukowicz, Thomas Ploetz
+ In UbiComp/ISWC 2023 Adjunct
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Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering
Ekdeep Singh Lubana, Chi Ian Tang, Fahim Kawsar, Robert P. Dick, Akhil Mathur
In ICML 2022 (International Conference on Machine Learning)
Exploring Contrastive Learning in Human Activity Recognition for Healthcare
Chi Ian Tang, Dimitris Spathis, Ignacio Perez Pozuelo, Cecilia Mascolo.
- In ML for Mobile Health Workshop at NeurIPS. 2020.
+ In ML for Mobile Health Workshop at NeurIPS. 2020.
+ I have taking up organizing roles for the following: +
© 2020-2022 Chi Ian Tang. All rights reserved. +
© 2020-2024 Chi Ian Tang. All rights reserved.