Academic Title: Associate Professor, Master’s Supervisor

Affiliated Institution: Institute of Computer Application Technology

Office Address: Room 312, Feiyun Building

Educational Background

2012.09-2016.06 Bachelor of Engineering in Computer Science and Technology, School of Information Science and Engineering, Lanzhou University

2016.09-2019.06 Master of Engineering in Computer Software and Theory, School of Computer Science and Technology, Huazhong University of Science and Technology

2019.08-2023.12 Doctor of Philosophy in Computer Science, King Abdullah University of Science and Technology (KAUST) Professional Experience

2024.07-Present Associate Professor, School of Information Science and Engineering, Lanzhou University

Research Interests

1. Affective Computing
2. Machine Learning, Data Mining, Generative Artificial Intelligence
3. Large Model-based Medical Assistance Systems

Publications (Papers and Books)

More than 10 SCI/EI-indexed papers published. Selected publications in the past five years are as follows:

[1] Ma, C., Guo, T., Yang, Q., Chen, X., Gao, X., Liang, S., Chawla, N. and Zhang, X., 2024, April. A Property-Guided Diffusion Model For Generating Molecular Graphs. In 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 2365-2369).

[2] Ma, C., Yang, Q., Liang, S. and Gao, X., 2023, December. A Distribution Preserving Model for Molecular Graph Generation. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (pp. 379-386).

[3] Ma, C., Yang, Q., Gao, X. and Zhang, X., 2022, October. Disentangled molecular graph generation via an invertible flow model. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 1420-1429).

[4] Ma, C. and Zhang, X., 2021, October. GF-VAE: a flow-based variational autoencoder for molecule generation. In Proceedings of the 30th ACM international conference on information & knowledge management (pp. 1181-1190).

[5] Ma, C., Li, J., Pan, P., Li, G., Du, J., 2019, August. BDMF: a biased deep matrix factorization model for recommendation. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing.

[6] Yang, Q., Ma, C., Zhang, Q., Gao, X., Zhang, C. and Zhang, X., 2023, August. Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2988-2998).

[7] Yang, Q., Ma, C., Zhang, Q., Gao, X., Zhang, C. and Zhang, X., 2023, February. Interpretable research interest shift detection with temporal heterogeneous graphs. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (pp. 321-329).

[8] Li, M., Chen, X., Xiang, J., Zhang, Q., Ma, C., Dai, C., Chang, J., Liu, Z. and Zhang, G., 2024, March. Multi-Intent Attribute-Aware Text Matching in Searching. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (pp. 360-368).

Email: macs@lzu.edu.cn