The SINGAPORE DATA SCIENCE CONSORTIUM (SDSC) DISSERTATION RESEARCH FELLOWSHIP aims to promote and recognise innovative and impactful data science thesis work of PhD students. This annual programme will provide up to ten (10) cash awards of S$10,000 for doctoral students at Singapore universities. The cash awards can be used to support research initiatives that are related to data science and involve the use of real-world data sets.
Click on the links below to view the research done by the 2022 awardees:
Chen Jielin – Conceptual Space-Oriented Architectural Creative Design Assistant with Cognitive and Computational Footings
Kong Weijia – Novel Tools for Missing Protein Identification and Quantification
Leong Yong Xiang – Strengthening Surface-Enhanced Raman Scattering (SERS)-based Nanosensors with Machine Learning
Liu Xu – Efficient Forecasting on Spatio-Temporal Graphs
Mathieu Ravaut – Improving Neural Abstractive Summarization with Sequence-level Models
Teo Hoong Chen – Quantifying the Benefits, Risks and Uncertainties of Nature-based Climate Solutions to Develop High-quality Carbon Projects
Tran Nhu Thuat – Interpretability in Recommender Systems
Wang Yufei – Deep Learning on Image Restoration
Wu Zhaoxuan – Collaborative Machine Learning
Zhang Fengzhuo – Problems in Statistical Learning Theory: From Graphical Models to Reinforcement Learning
Click on the links below to view the research and video presentations done by the 2021 awardees:
Gregory Ang Tai Xiang – Application of Big Data Analytics in a National Mobile Health Program
Jiang Liming – Image and Video Generation via Deep Learning
Nguyen Xuan Phi – Towards Robust Neural Machine Translation
Sun Yinxiaohe – Modelling of the COVID-19 Pandemic
Yang Siyuan – Deep Learning on Skeleton Action Recognition
Zhang Ce – Document Graph Representation Learning
Click on the links below to view the research and video presentations done by the 2020 awardees:
Berend David Christopher – Enhancing Trustworthiness of AI Systems with Out-of-Distribution Detection & Generalization
Hasnain Ali – Data-Driven and Learning-Based Airport Traffic Control
Le Trung Hoang – Mining Product Textual Data for Recommendation Explanations
Liang Yuxuan – Learning Human Mobility with Deep Spatio-Temporal Neural Networks
Lim Xiang Hui Nicholas – User Preference Modelling for Recommendation
Low Ching Nam Raymond – Data Issues in Urban Freight Studies
Wang Yiwei – Towards Effective Neural Networks on Graph Data
Zhang Huaizheng – Towards Efficient Model Deployment and Serving of Deep Neural Network
Zhou Daquan – Efficient Architecture Design for Deep Neural Networks