50% of my research is on machine learning and the other 50% lies in its applications in health. Currently, my primary work is focused around semi-supervised learning for wearables. My doctoral research is supervised by Prof. Aiden Doherty and Prof. Simon Kyle. My research has also been generously sponsored by the Li Kai Shing foundation.
Back at Jacobs, I first worked with Prof. Michael Kohlhase and then my real ML research started with Prof. Herbert Jaeger and Prof. Benn Godde. I also spent time at MPI with Prof. Grosse-Wentrup and at EPFL with Prof. Courtine on brain-computer-interface research which was super interesting. My master thesis supervisors are Dr. François Fleuret and Dr. Mathieu Salzmann.
PC Member for ML4Health Neurips 2020
|2019 Jun: A Primer on the Delayed Adversarial Attack in Using Recurrent Neural Networks for Reinforcement Learning
An introduction of a series of work on delayed adversarial attack in deep learning. We will make the code available soon.
|Repo PDF||2017 Jun: Motor Learning Skill Classification Using Echo State Networks
ESNs are a type of Recurrent Neural Networks (RNNs) that are easy to train but still maintain the power of capturing the temporal information that do. In my bachelor thesis, I constructed ESNs for motor learning skill classification on EEG data. Additionally, I also developed new methods on how to increase the interpabiltiy of ESNs.
Mathematical Knowledge Management (MKM)
|2016 Jun: Mixing Surface Languages for OMDoc
The formalism of mathmatics: MathML, OpenMath and OMDoc are machine-friendly formats for math so that the machines can do search, automated proving and cross-referencing easily. TeX is the main driving horse for high quality mathematics documents authoring. A variant of TeX that allows for structural formats, enables us to transform those documents into OMDoc with the help of LaTeXML sTeX plugin to let machines operate on the documents.
|2020 Dec: Training Ethically Responsible AI Researchers: a Case Study
NBAIR Workshop, Neurips, 2020
Relfection on ethics training for AI researchers.
- Tutor for Artificial Intelligence, Oxford, 2021 Spring
- Tutor for Centre for Doctoral Training Health Data Science, CDT for HDS, wearable modules and data challenge, Oxford, 2021 Spring
- Teaching assistant for Computation and Complexity, Jacobs University, 2017
- Chap 1 and Chap 2 in Deep Reinforcement Learning: Fundamentals, Research and Applications , Springer 2020 ISBN 978-981-15-4094-3
- Deep Learning using TensorLayer 深度学习：一起玩转TensorLayer, Publishing House of Electronics Industry 2018 ISBN: 9787121326226.