李楠

 

研究领域：神经架构搜索、性能预测器、演化计算，特征选择

电子邮箱：lnnner@163.com

个人简介

        入选首届中国科协青年人才托举工程博士生专项计划。目前已在ACM CSUR (IF: 28.06)，IJCAI，IEEE TEVC, IEEE TFS, IEEE TCYB等知名期刊及会议上发表论文20篇（含ESI高被引3篇，热点论文1篇，研究前沿3篇），Google引用400余次。担任30多个SCI/EI审稿人，其中包括20本中科院一区期刊以及3个国际会议的PC/TPC reviewer。此外，作为Session/Workshop Chair在多个国际会议上组织与演化架构搜索相关的专题。

科学研究

主要研究方向：

        序感知性能预测器关键技术研究

        面训练准测关键技术研究

主要科研项目情况：

        中国科协青年人才托举工程博士生专项计划（主持）

发表论文：

[1] Li N, Ma L, Yu G, Xue B, et al. Survey on evolutionary deep learning: Principles, algorithms, applications, and open issues[J]. ACM Computing Surveys, 2024, 56(2): 1-34. (IF: 28.06, 中科院一区Top, ESI高被引/研究前沿)

[2] Li N, Xue B, Ma L, et al. Transferable Relativistic Predictor: Mitigating Cross-Task Cold-Start Issue in NAS [C]. International Joint Conference on Artificial Intelligence, 2025, Accepted. (CCF-A类会议).

[3] Li N, Xue B, Ma L, et al. Automatic Fuzzy Architecture Design for Defect Detection via Classifier-assisted Multiobjective Optimization Approach [J]. IEEE Transactions on Evolutionary Computation, 2024. (CAAI-A, 中科院一区Top)

[4] Li N, Ma L, Xue B, Zhang M, et al. Listwise Ranking Predictor for Evolutionary Neural Architecture Search [J]. Swarm and Evolutionary Computation, 2025. (中科院一区)

[5] Li N, Ma L, Xing T, et al. Automatic design of machine learning via evolutionary computation: A survey[J]. Applied Soft Computing, 2023: 110412. (中科院一区Top)

[6] Ma L, Li N*, et al. A Novel Fuzzy Neural Network Architecture Search Framework for Defect Recognition with Uncertainties [J] IEEE Transactions on Fuzzy Systems, 2024, doi: 10.1109/TFUZZ.2024.3373792. (中科院一区Top)

[7] 李楠,贺美蕊,马连博.进化深度学习的研究现状与进展[J].信息与控制,2024,53(02):129-153. (EI期刊，入选科技期刊双语传播工程)

[8] Li N, Ma L, Zhang T, et al. Multi-objective Evolutionary Ensemble Learning for Disease Classification[C]//International Conference on Swarm Intelligence. Cham: Springer International Publishing, 2022: 491-500. (EI会议)

[9] Ma L, Li N, Yu G, et al. Pareto-Wise Ranking Classifier for Multi-Objective Evolutionary Neural Architecture Search[J]. IEEE Transactions on Evolutionary Computation, 2023. (中科院一区Top, ESI高被引/热点/研究前沿)

[10] Ma L, Li N, Guo Y, et al. Learning to Optimize: Reference Vector Reinforcement Learning Adaption to Constrained Many-Objective Optimization of Industrial Copper Burdening System[J]. IEEE Transactions on Cybernetics, 2022, 52(12): 12698-12711. (中科院一区Top, ESI高被引/研究前沿)

[11] 马连博,李楠,程适.进化神经网络原理、模型及方法综述[J].陕西师范大学学报(自然科学版),2021,49(05):30-38+133.DOI:10.15983/j.cnki.jsnu.2021.01.022. (中文核心，获卓越论文奖)

[12] Tian Zhang, Lianbo Ma, Shi Cheng, Yikai Liu, Nan Li Automatic Prompt Design via Particle Swarm Optimization Driven LLM for Efficient Medical Information Extraction [J]. Swarm and Evolutionary Computation. (中科院一区Top)

[13] Guo L, Li N, Zhang T. EEG-based emotion recognition via improved evolutionary convolutional neural network[J]. International Journal of Bio-Inspired Computation, 2024, 23(4): 203-213. (CAA-A期刊)

[14] Zhang T, Li N, Zhou Y, et al. Information extraction of Chinese medical electronic records via evolutionary neural architecture search[C]//2023 IEEE International Conference on Data Mining. IEEE, 2023: 396-405. (CCF-B会议)

[15] Zhang T, Li N, et al. Neural Architecture Search Based on Brain Storm Optimization Algorithm for Face Detection [C]// International Joint Conference on Neural Networks 2024 (CCF-C会议)

[16] Mei A., Li N, et al. Evolutionary Graph Fusion Architecture Search [C]// IEEE Congress on Evolutionary Computation 2025 (CAAI-C会议)

[17] Zhang T, Ma L, Liu Q, Li N, et al. Genetic programming for ensemble learning in face recognition[C]// International Conference on Swarm Intelligence. Cham: Springer International Publishing, 2022: 209-218. (EI会议)

[18] Liu Y, Xing T, Li N, et al. A Large-Scale Multi-objective Brain Storm Optimization Algorithm Based on Direction Vectors and Variance Analysis[C]//International Conference on Swarm Intelligence. Cham: Springer Nature Switzerland, 2023: 413-424. (EI会议)

[19] An X, Ma L, Li N, et al. Neural Architecture Search Based on Improved Brain Storm Optimization Algorithm[C]//International Conference on Swarm Intelligence. Cham: Springer Nature Switzerland, 2023: 334-344. (EI会议)

[20] Kang H, Li N, et al. When NAS Meets Anomaly Detection: In Search of Resource-Efficient Architectures in Surveillance Video [C]// International Joint Conference on Neural Networks 2024 (CCF-C会议)

授权专利：

[1] 基于粒子群优化的大模型提示设计的病历信息抽取方法（授权）

[2] 一种基于进化的神经架构搜索方法（授权）

学术服务/社会兼职：

担任TEVC、TFS、TNNLS、TCYB、IOT、TAI、TITS、TCE、INF、PR、ASCO、CIM、INS、CAIS、CAIE、ICML、NeurIPS、ICLR、ICDM、IJCNN、ICIC、GECCO、CEC等30余个SCI期刊及国际会议审稿人。在ICDM、IJCNN、CEC等国际会议担任TPC/PC reviewer。

IJCNN-2025 “Neural Architecture Search's Theory, Algorithm and Application” Special Chair

CEC-2025 “Neural Architecture Search: A Deep Evolutionary Optimization Perspective” Special Chair

DOCS-2025 “Evolutionary Deep Learning: From Theory to Application” Special Chair

ICCVIT-2024 “Advanced Architectural Design for Vision Task” Workshop Chair