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

Liu Siqi – Applying Machine Learning Models as Clinical Decision Support (CDS) Tools to Assist Clinician’s Decision Making in Critical Care

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