1.自然语言处理中的信息提取和生成技术

2.面向大数据的逻辑推理技术研究

3.基于知识图谱和图网络的决策推断研究

4.基于嵌入式系统的算法优化

1.重点研发计划“全流程管控的精细化执行技术及装备研究”（2018-2021）：借助深度神经网络，对海量拍卖物品的多种数据源进行整合，分析拍卖物品的实际价值，实现拍卖物品的成交价格预测。

2.工信部创新项目“面向医疗健康的大数据共享及人工智能训练平台”（2018），参与医疗数据融合及训练平台的前期建设。

3.上海科委项目“儿童青少年脑智发育数据平台研发”（2019-2022），完成对儿童脑海量数据的收集、存储和管理，实现多种数据在不同学科间的共享和关联，并通过人工智能分析工具辅助科研人员进行数据搜索、数据挖掘以及可视化等应用

<span font-size:14pt;"="">4.上海脑科学与类脑研究中心“脑科学大数据协作研究平台”（2019-2021）

1. W. Chen, J. Tian, L. Xiao, H. He*, and Y. Jin*, “Exploring Logically Dependent Multi-task Learning with Causal Inference,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, Nov. 2020, pp. 2213–2225, Accessed: Nov. 15, 2020. [Online]. Available: https://www.aclweb.org/anthology/2020.emnlp-main.173.

2. W. Chen, J. Tian, L. Xiao, H. He*, and Y. Jin*, “A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation,” in Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, Spain (Online), Dec. 2020, pp. 1186–1198, Accessed: Dec. 17, 2020. [Online]. Available: https://www.aclweb.org/anthology/2020.coling-main.102.

3. L. Xiao, L. Wang, H. He*, and Y. Jin*, “Modeling Content Importance for Summarization with Pre-trained Language Models,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, Nov. 2020, pp. 3606–3611, Accessed: Nov. 27, 2020. [Online]. Available: https://www.aclweb.org/anthology/2020.emnlp-main.293.

4. Xiao, L., Wang, L., He, H., Jin, Y., 2020. Copy or Rewrite: Hybrid Summarization with Hierarchical Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence 34, 9306–9313. https://doi.org/10.1609/aaai.v34i05.6470

5. Yang, S., Tian, J., Zhang, H., Yan, J., He, H., Jin, Y., 2019. TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics 1935–1942.

6. Xiong, Z., Li, L., Yan, J., Wang, H., He, H., Jin, Y., 2019. Differential Privacy with Variant-Noise for Gaussian Processes Classification, in: Nayak, A.C., Sharma, A. (Eds.), PRICAI 2019: Trends in Artificial Intelligence, Lecture Notes in Computer Science. Springer International Publishing, Cham, pp. 107–119. https://doi.org/10.1007/978-3-030-29894-4_9

7. Zhang, K., He, H.*, Xin, H., Hu, W., Liang, S., Lu, D., Zhao, L., 2018. Chirp-aided power fading mitigation for upstream 100 km full-range long reach PON with DBR DML. Optics Communications 407, 63–68. https://doi.org/10.1016/j.optcom.2017.09.011

8. Hu, W., He, H., Zhang, K., Xin, H., Li, L., Mikaeil, A.M., 2019. A comprehensive optical mobile fronthaul network toward high-fidelity, flexible and low-latency transport. Photon Netw Commun 37, 322–334. https://doi.org/10.1007/s11107-019-00829-z

9. Chen, K., Ye, T., He, H., Guo, Z., 2019. Modular Optical Cross-Connects (OXCs) for Large-Scale Optical Networks. IEEE Photonics Technology Letters 31, 763–766. https://doi.org/10.1109/LPT.2019.2907001