Publications

Legends: 

J-Journal paper, C-Conference paper, BC-Book chapter, P-presentation 

2024:

1. X. Wu, D. Wang, H. Chen, L. Yan, Y. Xiao, C. Miao, H. Ge, D. Xu,  Y. Liang, K. Wang, C. Wu and Y. Zhou, "Neural architecture search for text classification with limited computing resources using efficient Cartesian Genetic Programming", IEEE Transactions on Evolutionary Computation, in press. 

2. Y. Zhang, H. Liu, D. Wang, D. Zhang, T. Lou, Q. Zheng and C. Quek, "Cross-modal credibility modelling for EEG-based multimodal emotion recognition", Journal of Neural Engineering, to appear.

3. M. Hassana, Y. Wang, D. Wang, P. Wei, D. Li, Y. Zhou, D. Xu, S.-ur-Rahman, A.-ur-Rahman, A. A. Fateh and P. Qin, "Deep Learning Model for Human-Intuitive Shoeprint Reconstruction", Expert Systems with Applications, in press.

4. Z. Su, D. Wang, C. Miao and L. Cui, "Anchoring path for inductive relation prediction in knowledge graphs", in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 19.36%), Vancouver, Canada, February 2024, to appear.

5. Y. Xiao, D. Wang, B. Li, M. Wang, X. Wu, C. Zhou and Y. Zhou, "Distilling autoregressive models to obtain high-performance non-autoregressive solvers for vehicle routing problems with faster inference speed", in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 19.36%), Vancouver, Canada, February 2024, to appear.

6. D. K. X. Fung*, D. Wang*,  H. Wang, Y. Wang, P. Wu, Y. Y. Ha, C. C. Yip, W. J. Heng, T. H. Lim, C. Leung and C. Miao, "Accurate and explainable cataract screening using eye images taken by slit-lamp cameras", in Proceedings of IEEE Conference on Artificial Intelligence (CAI), Singapore, June 2024, to appear. *equal contribution.

7. Y. Qiu, P. Chen, H. Zhang, B. Huang, D. Wang and Z. Shen, "Engaging the elderly in exercise with agents: A gamified stationary bike system for sarcopenia management", in Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Auckland, New Zealand, May 2024, to appear [Demo paper]. 

2023:

1. [J24] Y. Wang, D. Wang, Y. Zhou, X. Zhang and C. Quek, "VDPC: Variational Density Peak Clustering algorithm", Information Sciences, vol. 621, pp. 627-651, 2023.

2. [J23] X. Song, D. Wang, C. Quek, A,-H. Tan and Y. Wang, "Spatial-temporal episodic memory modeling for ADLs: Encoding, retrieval, and prediction", Complex & Intelligent Systems, in press.

3. [J22] X. Wu, J. Han, D. Wang, P. Gao, Q. Cui, L. Chen, Y. Liang, H. Huang, H. P. Lee, C. Miao, Y. Zhou and C. Wu, "Incorporating surprisingly popular algorithm and Euclidean distance-based adaptive topology into PSO", Swarm and Evolutionary Computation, vol. 76, article no. 101222, 2023.

8. [J21] Y. Zheng, X. Zhang, S. Chen, X. Zhang, X. Yang and D. Wang, "When convolutional network meets temporal heterogeneous graphs: An effective community detection method", IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 2, pp. 2173-2178, 2023.

9. [C32] Z. Su, D. Wang, C. Miao and L. Cui, "Multi-aspect explainable inductive relation prediction by Sentence Transformer" (selected for oral presentation), in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 19.6%), Washington DC, USA, February 2023, pp. 6533-6540.

2022:

1. [J20] W.-C. L. Lew, D. Wang, K. K. Ang, J.-H. Lim, C. Quek and A.-H. Tan, "EEG-video emotion-based summarization: Learning with EEG auxiliary signals", IEEE Transactions on Affective Computing, vol. 13, no. 4, pp. 1827-1839, 2022.

2. [J19] P. Zhong, D. Wang and C. Miao, "EEG-based emotion recognition using regularized graph neural networks", IEEE Transactions on Affective Computing, vol. 13, no. 3, pp. 1290-1301, 2022 [Best Paper Award].

3. [J18] R. S. Tan, E. F. Goh, D. Wang, R. C. L. Chan, Z. Zeng, A. Yeo, K. Pek, J. Kua, W. C. Wong, Z. Shen and W. S. Lim, "Effectiveness and usability of the System for Assessment and Intervention of Frailty (SAIF) for community-dwelling pre-frail older adults: A pilot study", Frontiers in Medicine, vol. 9, article no. 955785, 2022.

4. [J17] M. Hassan, Y. Wang, D. Wang, W. Pang, K, Wang, D. Li, Y, Zhou and D. Xu, "Restorable-inpainting: A novel deep learning approach for shoeprint restoration", Information Sciences, vol. 600, pp. 22-42, 2022.

5. [J16] M. Hassan, Y. Wang, W. Pang, D. Wang, D. Li, Y. Zhou and D. Xu, "GUV-Net for high fidelity shoeprint generation", Complex & Intelligent Systems, vol. 8, pp. 933-947, 2022.

6. [J15] M. Hassan, Y. Wang, W. Pang, D. Wang, D. Li, Y. Zhou and D. Xu, "IPAS-Net: A deep-learning model for generating high-fidelity shoeprints from low-quality images with no natural references", Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 6, Part A, pp. 2743-2757, 2022.

7. [C32] Z. Su, D. Wang, L. Cui, X. Zhang and C. Miao, "Efficient reachability query with Extreme Labeling Filter", in Proceedings of ACM International Conference on Web Search and Data Mining (WSDM) (acceptance rate 20.2%, virtual conference), pp. 966-975, Feburary 2022.

8. [C31] F. Luo, H. Qian, D. Wang, X. Guo, Y. Sun, E. S. Lee, H. H. Teong, R. T. R. Lai and C. Miao, "Missing value imputation for diabetes prediction", in Proceedings of IEEE International Joint Conference on Neural Networks (IJCNN), pp. 1-8, Padua, Italy, July 2022.

2021:

1. [J14] H. Zhang, D. Wang, Y, Wang, Y. Chi and C. Miao, "Development and validation of a practical instrument for evaluating players’ familiarity with exergames", International Journal of Human-Computer Studies, vol. 145, article no. 102521, 2021.

2. [J13] M. Hassan, Y. Wang, D. Wang, D. Li, Y. Liang, Y. Zhou and D. Xu. "Deep learning analysis and age prediction from shoeprints", Forensic Science International, vol. 327, article no. 110987, 2021.

3. [C30] P. Zhong, D. Wang, P. Li, C. Zhang, H. Wang and C. Miao. “CARE: Commonsense-aware emotional response generation with latent concepts", in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 21.4%, virtual conference), pp. 14577-14585, February 2021.

2020:

1. [J12] Y. Wang, D. Wang, X. Zhang, W. Pang, C. Miao, A.-H. Tan and Y. Zhou, "McDPC: Multi-center density peak clustering", Neural Computing and Applications, vol. 32, pp. 13465-13478, 2020.

2. [J11] Y. Wang, D. Wang, W. Pang, C. Miao, A.-H. Tan and Y. Zhou, "A systematic density-based clustering method using anchor points", Neurocomputing, vol. 400, pp. 352-370, 2020.

3. [J10] X. Zhang, H. Liu, X. Chen, J. Zhong and D. Wang, "A novel hybrid deep recommendation system to differentiate user’s preference and item’s attractiveness", Information Sciences, vol. 519, pp. 306-316, 2020.

4. [J9] W. Yang, D. Wang, W. Pang, A.-H. Tan and Y. Zhou, "Goods consumed during transit in split delivery vehicle routing problems: Modeling and solution", IEEE Access, vol. 8, pp. 110336-110350, 2020.

5. [C29] T. Zhang, D. Wang, H. Chen, Z. Zeng, W. Guo, C. Miao and L. Cui, "BDANN: BERT-based domain adaptation neural network for multi-modal fake news detection", in Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 1-8, Glasgow, UK, July 2020.

6. [C28] W.-C. L. Lew, D. Wang, K. Shylouskaya, Z. Zhang, J.-H. Lim, K.-K. Ang and A.-H. Tan, "EEG-based emotion recognition using spatial-temporal representation via Bi-GRU", in Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 116-119, Montreal, Canada, July 2020.

2019:

1. [J8] M. Parmar*, D. Wang*, X. Zhang, A.-H. Tan, C. Miao, J. Jiang and Y. Zhou, "REDPC: A residual error-based density peak clustering algorithm", Neurocomputing, vol. 348, pp. 82-96, 2019. *equal contribution.

2. [J7] A.-H. Tan, B. Subagdja, D. Wang and L. Meng, "Self-organizing neural networks for universal learning and multimodal memory encoding", Neural Networks, vol. 120, pp. 58-73, 2019.

3. [J6] Z. Zeng, Z. Shen, D. Wang, W. S. Lim, S. K. Pek, Y. Qiu, J. Ji, R. Chan, H. Zhang, Y. Yuan, B. Huang, W. Wang, Y. Liu and J. J. Chin, "SAIF: A system for long-term assessment and intervention of frailty with gamification", International Journal of Information Technology, vol. 25, no. 1, pp. 1–26, 2019.

4. [BC1] D. Wang, A. A. Moustafa, A.-H. Tan and C. Miao, "Using a neurocomputational autobiographical memory model to study memory loss", in V. Curtsuridis (Ed.), Multiscale Models of Brain Disorders, pp. 157-163, Springer.

5. [C27] D. Wang, A.-H. Tan, C. Miao and A. A. Moustafa, "Modelling autobiographical memory loss across life span", in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 16.2%), pp. 1368-1375, Hawaii, USA, January 2019.

6. [C26] P. Zhong, D. Wang and C. Miao, "An affect-rich neural conversational model with biased attention and weighted cross-entropy loss", in Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (acceptance rate 16.2%), pp. 7492-7500, Hawaii, USA, January 2019.

7. [C25] P. Zhong, D. Wang and C. Miao, "Knowledge-enriched transformer for emotion detection in textual conversations", in Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP) (acceptance rate 23.8%), pp. 165-176, Hong Kong, China, November 2019.

8. [C24] T. Luo, B. Subagdja, D. Wang and A.-H. Tan, "Multi-agent collaborative exploration through graph-based deep reinforcement learning", in Proceedings of IEEE International Conference on Agents (ICA) (acceptance rate 38.46%), pp. 2-7, Jinan, China, October 2019 [Best Paper Award].

2018:

1. [J5] D. Wang, X. Qian, C. Quek. A.-H. Tan, C. Miao, X. Zhang, G. S. Ng and Y. Zhou, "An interpretable neural fuzzy inference system for predictions of underpricing in initial public offering", Neurocomputing, vol. 319, pp. 102-117, 2018.

2. [C23] Z. Wei, D. Wang, M. Zhang, A.-H. Tan, C. Miao and Y. Zhou, "Autonomous agents in snake game via deep reinforcement learning", in Proceedings of IEEE International Conference on Agents (ICA), pp. 20-25, Singapore, July 2018.

3. [C22] P. Wang, W. J. Zhou, D. Wang and A.-H. Tan, "Probabilistic guided exploration for reinforcement learning in self-organizing neural networks", in Proceedings of IEEE International Conference on Agents (ICA), pp. 109-112, Singapore, July 2018.

4. [C21] D. Wang, E. Wu and A.-H. Tan, "Analysis of public transportation patterns in a densely populated city with station-based shared bikes", in Proceedings of International Conference on Crowd Science and Engineering (ICCSE), Article No. 8, Singapore, July 2018.

5. [C20] Z. Zeng, S. Fauvel, B. T. H. Tan, D. Wang, P. O. K. Chew. C. Leung, Z. Shen and J. J. Chin, "Towards long-term tracking and detection of early dementia: A computerized cognitive test battery with gamification", in Proceedings of International Conference on Crowd Science and Engineering (ICCSE), Article No. 30, Singapore, July 2018.

2017:

1. [C19] D. Wang, X. Yu, S. Fauvel, A.-H. Tan and C. Miao, “Elderly friendliness evaluation of mobile assistants”, in Proceedings of International Conference on Agents (ICA), pp. 115-120, Beijing, China, July 2017.

2. [C18] D. Wang and A.-H. Tan, "eHealthPortal: A social support hub for the active living of the elderly", in Proceedings of International Conference on Crowd Science and Engineering (ICCSE), pp. 19-25, Beijing, China, July 2017.

3. [P3] D. Wang, A.-H. Tan, C. Miao and A. Moustafa, "Neurocomputational modeling of memory loss", presented at International Conference on Ageless Aging (ICAA), Beijing, China, July 2017.

4. [P2] M. Parmar, D. Wang, J. Jiang and Y. Zhou, "A novel path-following density peak clustering algorithm based on squared residual error", presented at International Conference on Management of e-Commerce and e-Government (ICMECG), Changchun, China, September 2017.

5. [C17] C. Tang, D. Wang, A.-H. Tan and C. Miao, "EEG-based emotion recognition via fast and robust feature smoothing", in  Proceedings of International Conference on Brain Informatics (BI), pp. 83-92, Beijing, China, November 2017.

6. [C16] M. Parmar, D. Wang, A.-H. Tan, C. Miao, J. Jiang and Y. Zhou, "A novel density peak clustering algorithm based on squared residual error", in Proceedings of IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), pp. 43-48, Shenzhen, China, December 2017.

7. [C15] D. Wang, C. Quek, A.-H. Tan, C. Miao, G. S. Ng and Y. Zhou, "Leveraging the trade-off between accuracy and interpretability in a hybrid intelligent system", in Proceedings of IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), pp.55-60, Shenzhen, China, December 2017.

8. [C14] D. Wang, E. Candinegara, J. Hou, A.-H. Tan and C. Miao, "Robust human activity recognition using lesser number of wearable sensors", in Proceedings of IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), pp. 290-295, Shenzhen, China, December 2017.

2016:

1. [J4] D. Wang, C. Quek and G. S. Ng, “Bank failure prediction using an accurate and interpretable neural fuzzy inference system”, AI Communications, vol. 29, no. 4, pp. 477-495, 2016.

2. [C13] D. Wang, A.-H. Tan and C. Miao, “Modelling autobiographical memory in human-like autonomous agents”, in Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS) (acceptance rate 24.9%), pp. 845-853, Singapore, May 2016.

3. [C12] D. Wang and A.-H. Tan, “Self-regulated incremental clustering with focused preferences”, in Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 1297-1304, Vancouver, Canada, July 2016.

4. [P1] H. Zhang, C. Miao and D. Wang, "Familiarity design in exergames for the elderly", Presented at International Conference on Crowd Science and Engineering (ICCSE), Vancouver, Canada, July 2016. 

5. [C11] Z. Zeng, D. Wang, A. Borjigin, C. Miao, A.-H. Tan and C. Leung, "Human-centred design for silver assistants", in Proceedings of International Conference on Agents (ICA), pp. 112-113, Matsue, Japan, September, 2016 [Short Paper].

2015:

1. [J3] D. Wang and A.-H. Tan, “Creating autonomous adaptive agents in a real-time first-person shooter computer game”, IEEE Transactions on Computational Intelligence and AI in Games, vol. 7, no. 2, pp. 123-138, 2015.

2. [C10] D. Wang, A.-H. Tan and D. Zhang, “Non-intrusive robust human activity recognition for diverse age groups”, in Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp. 368-375, Singapore, December 2015.

3. [C9] S. Gao, D. Wang, A.-H. Tan and C. Miao, “Progressive sequence matching for ADL plan recommendation”, in Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp. 360-367, Singapore, December 2015.

4. [C8] D. Wang, B. Subagdja, Y. Kang and A.-H. Tan, “Silver assistants for aging-in-place”, in Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp. 241-242, Singapore, December 2015 [Demo paper].

5. [C7] D. Wang and A.-H. Tan, “MyLife: An online personal memory album”, in Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp. 243-244, Singapore, December 2015 [Demo paper].

2014:

1. [J2] D. Wang, C. Quek and G. S. Ng, “Ovarian cancer diagnosis using a hybrid intelligent system with simple yet convincing rules”, Applied Soft Computing, vol. 20, pp. 25-39, 2014.

2. [C6] D. Wang and A.-H. Tan, “Mobile humanoid agent with mood awareness for elderly care”, in Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 1549-1556, Beijing, China, July 2014.

3. [C5] D. Wang, B. Subagdja, Y. Kang, A.-H. Tan and D. Zhang, “Towards intelligent caring agents for Aging-In-Place: Issues and challenges”, in Proceedings of IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI), pp. 1-8, Orlando, Florida, USA, December 2014.

Prior to 2014:

1. [C4] D. Wang, B. Subagdja, A.-H. Tan and G.-W. Ng, “Creating human-like autonomous players in real-time first person shooter computer games”, in Proceedings of Conference on Innovative Applications of Artificial Intelligence (IAAI), pp. 173-178, Pasadena, California, USA, July 2009.

2. [C3] D. Wang, G. S. Ng and C. Quek. “A novel hybrid intelligent system: Genetic algorithm and rough set incorporated neural fuzzy inference system”, in Proceedings of IEEE Congress on Evolutionary Computation (CEC), pp. 2749-2755, Hong Kong, China, June 2008.

3. [C2] D. Wang, G. S. Ng and C. Quek, “Ovarian cancer diagnosis using fuzzy neural networks empowered by evolutionary clustering technique”. In Proceedings of IEEE Congress on Evolutionary Computation (CEC), pp. 9314-9320, Vancouver, Canada, July 2006.

4. [J1] D. Wang, C. Quek and G. S. Ng, “Novel self-organizing Takagi-Sugeno-Kang fuzzy neural networks based on ART-like clustering”, Neural Processing Letters, vol. 20, no. 1, pp. 39-51, 2004.

5. [C1] D. Wang, C. Quek and G. S. Ng, “MS-TSKfnn: Novel Takagi-Sugeno-Kang fuzzy neural network using ART like clustering”, in Proceedings of IEEE International Joint Conference on Neural Networks (IJCNN), pp. 2361-2366, Budapest, Hungary, July 2004.