Dr Tianhong Dai
Locations
Dr Tianhong Dai
BEng, MSc, PhD
Lecturer
- About
-
Biography
I'm now a Lecturer in the Department of Computing Science. My research interests are focused on deep reinforcement learning (DRL) and its applications to robotics, video games and medical/microscopy images (e.g., axon tracking). In addition, I’m also interested in the research of computational photography, such as high dynamic range (HDR) imaging.
Before I joined the University of Aberdeen, I finished my PhD degree and worked as a Research Associate at Imperial College London. Prior to that, I also had two research internships in Tencent AI Lab/Robotics X and Huawei Noah’s Ark Lab (London), respectively. Currently, I'm also the reviewer of several conferences and journals, such as AAAI, TNNLS, ToG, Cognitive Computation, etc.
Qualifications
- PhD Machine Learning2022 - Imperial College London
- MSc Communication and Signal Processing2016 - Imperial College London
- BEng Electronic and Communication Engineering2015 - University of Liverpool
Latest Publications
Deep Reinforcement Learning for Real-Time Assembly Planning in Robot-Based Prefabricated Construction
IEEE Transactions on Automation Science and Engineering, pp. 1-12Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TASE.2023.3236805
Machine Learning to Support Visual Auditing of Home-based Lateral Flow Immunoassay Self-Test Results for SARS-CoV-2 Antibodies
Communications MedicineContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1038/s43856-022-00146-z
- [ONLINE] http://dx.doi.org/10.1038/s43856-022-00146-z
Progressive Multi-Scale Fusion Network for RGB-D Salient Object Detection
Computer Vision and Image UnderstandingContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.cviu.2022.103529
- [ONLINE] http://dx.doi.org/10.1016/j.cviu.2022.103529
LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/cog51982.2022.9893707
- [ONLINE] http://dx.doi.org/10.1109/cog51982.2022.9893707
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
Neurocomputing, vol. 493, pp. 143-165Contributions to Journals: Articles
- Research
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Research Overview
Currently, I'm focusing on the following research areas:
- Reinforcement Learning
- Medical Imaging
- Computational Photography
Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
Computing Science
Accepting PhDsResearch Specialisms
- Machine Learning
- Artificial Intelligence
Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.
- Publications
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Page 1 of 2 Results 1 to 10 of 16
Deep Reinforcement Learning for Real-Time Assembly Planning in Robot-Based Prefabricated Construction
IEEE Transactions on Automation Science and Engineering, pp. 1-12Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TASE.2023.3236805
Machine Learning to Support Visual Auditing of Home-based Lateral Flow Immunoassay Self-Test Results for SARS-CoV-2 Antibodies
Communications MedicineContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1038/s43856-022-00146-z
- [ONLINE] http://dx.doi.org/10.1038/s43856-022-00146-z
Progressive Multi-Scale Fusion Network for RGB-D Salient Object Detection
Computer Vision and Image UnderstandingContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.cviu.2022.103529
- [ONLINE] http://dx.doi.org/10.1016/j.cviu.2022.103529
LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/cog51982.2022.9893707
- [ONLINE] http://dx.doi.org/10.1109/cog51982.2022.9893707
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
Neurocomputing, vol. 493, pp. 143-165Contributions to Journals: ArticlesAdaptive Intra-Group Aggregation for Co-Saliency Detection
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsDiversity-Augmented Intrinsic Motivation for Deep Reinforcement Learning
NeurocomputingContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.neucom.2021.10.040
- [ONLINE] http://dx.doi.org/10.1016/j.neucom.2021.10.040
Coupled Network for Robust Pedestrian Detection With Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling
IEEE Transactions on Image ProcessingContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/tip.2020.3038371
- [ONLINE] http://dx.doi.org/10.1109/tip.2020.3038371
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1007/978-3-030-89370-5_3
- [ONLINE] http://dx.doi.org/10.1007/978-3-030-89370-5_3
Episodic Self-Imitation Learning with Hindsight
Electronics (Switzerland)Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.3390/electronics9101742
- [ONLINE] http://dx.doi.org/10.3390/electronics9101742
