一、个人基本信息

郭小丁，女，博士，2015年7月在西安电子科技大学获得学士学位，2021年3月在哈尔滨工业大学获得博士学位，2021年5月入职河南大学计算机与信息工程学院。长期从事人工智能、智慧司法、人工智能安全等领域相关研究。针对基于张量分解的咨询意图理解、基于优化门控神经网络的罪名预测、基于多任务学习的刑期研判、基于强化学习的资源调度、面向分布式物联网的边缘计算等多个国际热点课题具有多年的研究经验。主持或参与多项河南省科技攻关、国家重点研发专项、国家自然科学面上基金项目的研究。在国际知名期刊和会议上发表论文13篇，其中SCI论文8篇，EI论文5篇。

二、主讲课程和研究方向

本科生课程：《基本电路与电子学》、《云计算及安全》

研究生课程：《算法设计与分析》

三、论文、著作

[1]Xiaoding Guo, Lei Zhang and Zhihong Tian, "Judgment Prediction Based on Tensor Decomposition With Optimized Neural Networks," in IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2023.3248275.

[2] Xiaoding Guo, Feifei Zao, Lei Zhang, Legal judgment prediction via optimized multi-task learning fusing similarity correlation. Applied Intelligence, 2023, https://doi.org/10.1007/s10489-023-04904-x.

[3]Xiaoding Guo, Feifei Zao, Zhuo Shen, Lei Zhang, FCA-LJP: A Method Based on Formal Concept Analysis for Case Judgment Prediction. Neural Processing Letters, 2023, https://doi.org/10.1007/s11063-023-11238-9.

[4]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, "Ten La: An Approach based on Controllable Tensor Decomposition and Optimized Lasso Regression for judgement Prediction of Legal Cases," Applied intelligence, 18 pages, 2020.

[5]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, “TdBrnn: An Approach to Learning Users' Intention to Legal Consultation with Normalized Tensor Decomposition and Bi-LSTM,” CMC: Computers, Materials & Continua, 22 pages, 2019.

[6]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, “RnRTD: Intelligent Approach Based on the Relationship-Driven Neural Network and Restricted Tensor Decomposition for Multiple Accusation Judgment in Legal Cases,” Computational Intelligence and Neuroscience, vol. 2019, 18 pages, 2019.

[7]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, “Learning Users’ Intention of Legal Consultation through Pattern-Oriented Tensor Decomposition with Bi-LSTM,” Wireless Communications and Mobile Computing, vol. 2019, 16 pages, 2019.

[8]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, “TenRR: An Approach Based on Innovative Tensor Decomposition and Optimized Ridge Regression for Judgment Prediction of Legal Cases,” IEEE Access, 2020, PP(99):1-1.DOI:10.1109/ACCESS.2020.2999522.

[9]Shang Li, Hongli Zhang, Lin Ye; Shen Su, Xiaoding Guo, Haining Yu, Binxing Fang. Prison “Term Prediction on Criminal Case Description with Deep Learning.” Computers, Materials & Continua, 2020, 62(3): 1217-1231.

[10]Xiaoding Guo, Hongli Zhang, Lin Ye, Shang Li, "RnnTd: An Approach Based on LSTM and Tensor Decomposition for Classification of Crimes in Legal Cases," 2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC), Hangzhou, China, 2019, pp. 16-22, doi: 10.1109/DSC.2019.00012.

[11]Hongli Zhang, Xiaoding Guo, Lin Ye, Shang Li, "Marrying K-means with Evidence Accumulation in Clustering Analysis," 2018 IEEE 4th International Conference on Computer and Communications (ICCC), Chengdu, China, 2018, pp. 2050-2056, doi: 10.1109/CompComm.2018.8780791.

[12]Shang Li, Hongli Zhang, Lin Ye, Xiaoding Guo, Binxing Fang, "Evaluating the Rationality of Judicial Decision with LSTM-Based Case Modeling," 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC), Guangzhou, China, 2018, pp. 392-397, doi: 10.1109/DSC.2018.00063.

[13]Xiaoding Guo, Yadi Wang, Zhijun Miao et al., "ER-MRL: Emotion Recognition based on Multimodal Representation Learning," 2022 12th International Conference on Information Science and Technology (ICIST), Kaifeng, China, 2022, pp. 421-428, doi: 10.1109/ICIST55546.2022.9926848.

[14]Yadi Wang, Xiaoding Guo, Yibo Zhang et al., "An Adaptive Framework of Multimodal Emotion Recognition Based on Collaborative Discriminative Learning," 2023 15th International Conference on Advanced Computational Intelligence (ICACI), Seoul, Korea, Republic of, 2023, pp. 1-8, doi: 10.1109/ICACI58115.2023.10146184.

四、科研项目

[1]基于高阶互联张量分解的情景感知智能判案方法研究及应用，河南省重点研发与推广专项（232102210032），2023.01至2024.12，主持。

[2]基于规范化层次张量分解的智能研判方法研究，河南省高等学校重点科研项目计划（23A520026），2023.01至2024.12，主持。

[3]基于虚拟机自省的云安全防护关键技术研究, 国家自然科学基金面上项目（61872111），2019-01至2022-12，主要成员。

[4]高维自适应结构稀疏特征选择模型及其应用研究，河南省科技发展计划项目(222102210151), 2022-01至2023-12，主要成员。

[5]基于人工智能+区块链的5G网络行为监管关键技术研究，河南省重点研发与推广专项（222102210040），2022-01至2023-12，主要成员。

[6]基于知识图谱的案例特征匹配检索及法律法规推荐、基于深度网络与知识本体库的法律咨询语义识别与智能交互技术、基于语义分析的法律服务案例库建设与搜索技术等多项国家重点研发计划课题（2018YFC0830602，2018YFC0830903，2018YFC0830900），2018-01至2022-12，参与。

五、专利

[1]郭小丁,张磊,皂菲菲. 基于回归概念格的案件刑期预测方法及系统[P]. 河南省：CN114153950A,2022-03-08.

[2]郭小丁,张磊,皂菲菲. 一种基于形式概念分析的罪名预测方法和系统[P]. 河南省：CN114138939A,2022-03-04.

[3]王雅娣,郭小丁,任意缘等. 基于判别学习的多模态情绪识别方法和系统[P]. 河南省：CN116226635A,2023-06-06.

[4]张磊,郭小丁,皂菲菲. 一种基于形势概念分析的案件分流方法和系统[P]. 河南省：CN114138938A,2022-03-04.

[5]叶麟,张宏莉,郭小丁等. 一种基于输出型相似门的案件分类方法、装置及存储介质[P]. 黑龙江省：CN113033174B,2022-06-10.

六、联系方式

E-mail：gxd@henu.edu.cn