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朱光辉 |
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Short Biography
I am currently a Tenure-track Assistant Professor of the School of Computer Science at Nanjing University. I received my Ph.D. degree from Nanjing University in 2020, supervised by Prof. Yihua Huang. I worked in the 28th Research Institute of CETC from 2012 to 2015. He has been selected as an outstanding doctor of Jiangsu Computer Society, Jiangsu Province "Innovation and Entrepreneurship Doctor" program, Huawei "Spark Award", and Ministry of Education-Huawei "Intelligent Center" Pioneer Teacher, Executive Member of CCF Expert Committee on Big Data, Executive Member of CCF Technical Committee on Artificial Intelligence & Pattern Recognition, Secretary-General of the Jiangsu Computer Society Big Data Committee, CCF YOCSEF Nanjing Vice-Chairman,《BDMA》Youth Editorial Board. His research interests include big data and intelligent computing, automated machine learning, and graph machine learning. He has published more than 30 papers in leading conferences/journals, such as NeurIPS, ICML, ICLR, ACM SIGKDD, IEEE ICDE, ACM SIGIR, ICDM, CIKM, IEEE TKDE, IEEE TNNLS, IEEE TPDS, Machine Learning Journal, JPDC, and Chinese Journal of Computers. He has served as a reviewer for many conferences/journals such as NeurIPS, KDD, SIGIR, AAAI, TPDS, TKDE, TNNLS, etc. He has presided over many projects including the National Natural Science Foundation of China, the Natural Science Foundation of Jiangsu Province, Sub-project of the Key Research and Development Program of Jiangsu Province, Open Research Projects of Zhejiang Lab, CAAI Academic Foundation, University-Industry Cooperation and Collaborative Education Project, and the Cooperation Projects of Enterprises. He has published one core book "Introduction to Computer Systems" under the "101 Program". He has won 9 international awards in AutoML competitions organized by top international AI conferences such as NeurIPS and KDD, and won the gold award of 5th China International College Students' "Internet+" Innovation and Entrepreneurship Competition. The related technology has been applied in Huawei, Qihoo 360, CETC, and other IT enterprises.
Bio in Chinese (中文简介): 博士，Betway必威西汉姆联特聘研究员、准聘助理教授，江苏省计算机学会优博，江苏省“双创博士”，华为“难题揭榜火花奖”获得者，英特尔中国学术英才计划荣誉学者，教育部-华为“智能基座”先锋教师，教育部-华为“智能基座”产教融合协同育人基地优秀课件奖励计划获得者，担任CCF大数据专家委员会执行委员，CCF人工智能与模式识别专委会执行委员，中国指控学会大模型与决策智能专委会委员，江苏省计算机学会大数据专委会秘书长，CCF YOCSEF南京副主席，《大数据挖掘与分析（英文）》BDMA青年编委，曾在中电科28所工作3年，研究方向为大数据与智能计算，包括大数据自动化机器学习、图机器学习、大模型微调与推理系统优化等，已在NeurIPS、ICLR、ACM SIGKDD、IEEE ICDE、ACM SIGIR、ICDM、CIKM、IEEE TKDE、IEEE TNNLS、IEEE TPDS、Machine Learning Journal、JPDC及计算机学报、软件学报等国内外一流会议/期刊发表论文30余篇，多次担任NeurIPS、ICML、ICLR、KDD、SIGIR、AAAI、TPDS、TKDE、TNNLS等国内外会议/期刊审稿人，主持国家自然科学基金青年项目、江苏省自然科学基金项目、江苏省科技厅重点研发计划课题、之江实验室开放课题、人工智能学会学术基金、教育部产学合作协同育人项目以及企业横向合作项目多项，作为核心成员参与多项国家自然科学基金重点项目、科技创新2030-“新一代人工智能”重大项目、江苏省科技厅重点研发计划等，出版“101计划”核心教材《计算机系统:基于x86+Linux平台》1本。AutoML自动化机器学习领域的研究成果已在NeurIPS、KDD等国际顶级学术会议组织的AutoML大赛中，9次荣获国际大奖，6次获得前三名，并荣获第五届中国“互联网+”大学生创新创业大赛全国金奖，入选bw必威西汉姆联官网120周年校庆重点成果展，相关技术已落地应用于华为、奇虎360、中电科等IT企业。
News
[4/2022]: 课题组招收博士、硕士以及bw必威西汉姆联官网本科生，对大数据智能计算，特别是自动化机器学习、图机器学习、大模型微调与高效推理等方向感兴趣的同学，欢迎随时邮件联系! 另外，课题组还有少量2025级研究生名额，欢迎同学们与我联系！
[6/2022]: 恭喜本组在第五届中国“互联网+”双创大赛获得全国金奖的“PASA-AutoML人工智能自动化建模工具平台”项目入选bw必威西汉姆联官网120周年校庆重点成果展，并在我校“强国有我征程路”专栏展出!
[12/2024]: One paper on "Temporal Graph Learning" was accepted to IEEE Transactions on Neural Networks and Learning Systems (TNNLS, CAAI A & CCF-B类期刊).
[12/2024]: Honored to receive Huawei's invitation to present at the Computer Education Conference of China (CECC 2024)!
[12/2024]: One paper on "Graph Machine Learning" was accepted to IEEE Transactions on Neural Networks and Learning Systems (TNNLS, CAAI A & CCF-B类期刊).
[11/2024]:I will serve as a reviewer in ICML 2025!
[10/2024]: Our research on large model fine-tuning and efficient inference was funded by the Frontier Technology R&D Program of Jiangsu Province（江苏省前沿技术研究计划项目）.
[8/2024]: One paper on "Temporal Knowledge Graph Reasoning" was accepted to the 27th International Conference on Pattern Recognition (ICPR 2024, CAAI B & CCF-C类会议).
[8/2024]: Honored to be selected for Intel China Academic Excellence Program (2024年度英特尔中国学术英才计划荣誉学者)!
[8/2024]:I will serve as a reviewer in ICLR 2025!
[8/2024]: Honored to be selected as Executive Member of CCF Expert Committee on Big Data (CCF大数据专家委员会执行委员).
[7/2024]:I will serve as a PC Member in AAAI 2025!
[7/2024]:I will serve as a reviewer in KDD 2025!
[7/2024]: Honored to be selected as Executive Member of CCF Technical Committee on Artificial Intelligence & Pattern Recognition (CCF人工智能与模式识别专委会执行委员).
[6/2024]:Congratulations on the official publication of the core textbook "Introduction to Computer Systems" co-authored with Prof. Yuan Chunfeng under the "101 Program"（教育部“101计划”计算机领域核心教材）!
[6/2024]:Honored to be Ministry of Education-Huawei "Intelligent Center" Pillar Teacher(教育部-华为“智能基座”栋梁之师)!
[5/2024]:I will serve as a reviewer in NeurIPS 2024!
[5/2024]: One paper on "MOE Architecture Search for Multi-task Learning" was accepted to SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024, CCF-A, acceptance rate 20%).
[4/2024]:I will serve as a reviewer in CIKM 2024!
[3/2024]: One full paper on "LLM-Enhanced Temporal Heterogeneous Graphs" was accepted to ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024, CCF-A).
[02/2024]:One paper on "Graph Adversarial Attack" was accepted to IEEE Transactions on Knowledge and Data Engineering (TKDE, CCF-A)!
[02/2024]:Congratulations on the successful completion of our Open Research Project of Zhejiang Lab on Graph Neural Architecture Search, which was rated as excellent! （祝贺之江实验室开放课题项目（高效的图神经网络架构搜索）顺利结题，被评为优秀）！
[01/2024]:One paper on "Graph Anomaly Detection" was accepted to the 12th International Conference on Learning Representations (ICLR 2024, CAAI-A)!
[01/2024]:I will serve as a reviewer in KDD 2024!
[12/2023]: Received an Fund from Chinese Association for Artificial Intelligence (CAAI) and MindSpore Academic Foundation to support our research on Parallel Inference Optimization for Large Models（高效的大模型并行推理技术研究）！
[12/2023]:I will serve as a reviewer in ICML 2024!
[12/2023]:I will serve as a reviewer in SIGIR 2024!
[12/2023]:I will serve as a reviewer in DASFAA 2024!
[9/2023]: One paper on "Differentiable Neural Architecure Search" was accepted to the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023, CCF-A).
[9/2023]: One paper on "Spatial-Temporal Graph Learning in Traffic Forecasting" was accepted to IEEE International Conference on Data Mining (ICDM 2023, CCF-B).
[9/2023]:I will serve as a reviewer in ICLR 2024!
[8/2023]: Honored to be selected as Corresponding Member of CCF Expert Committee on Big Data (CCF大数据专委会通讯委员).
[4/2023]: One full paper on "Adaptive Fusion Multi-View Contrastive Learning Framework for Graph Collaborative Filtering" was accepted to ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023, CCF-A).
[3/2023]: I received Spark Award from Huawei due to the contribution to the distributed training of big models (华为“难题揭榜”火花奖，揭榜题目：大模型多维度混合训练策略的自动搜索)!
[4/2023]: One paper "Research on Progressive Deep Ensemble Architecture Search Algorithm" was accepted to Chinese Journal of Computers (计算机学报，中文CCF-A类期刊)
[2/2023]:I will serve as the PC member in SIGKDD 2023!
[2/2023]: I will serve as the PC member in SIGIR 2023!
[2/2023]: One paper "Federated Query Join Order Optimization based on Deep Reinforcement Learning" was accepted to World Wide Web Journal (WWWJ, CCF-B).
[2/2023]: One paper "Automated Attribute Completion for Heterogeneous Graph Neural Network" was accepted to IEEE International Conference on Data Engineering (IEEE ICDE 2023, CCF-A).
[1/2023]: I received Outstanding Doctorial Dissertation Award from CCF, Jiangsu Province !（江苏省计算机学会优博）
[1/2023]: One paper "Efficient Automatic Data Augmentation Algorithm Based on Self-Guided Evolutionary Strategy" was accepted to Journal of Software (软件学报，中文CCF-A类期刊)
[9/2022]: One paper on "Automated Adversarial Training" was accepted to the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022, CCF-A, Spotlight Paper!).
[8/2022]: One full paper on "Self-supervised Learning on Graphs" was accepted to the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022, CCF-B).
[8/2022]: One paper on "Evolutionary Automated Feature Engineering" was accepted to the 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2022, CCF-C).
[6/2022]: Our master student Jingfan Chen (co-advised with Prof. Yihua Huang) won the "2022 Excellent Master Thesis in Compuster Science Department of Nanjing University (bw必威西汉姆联官网计算机系优秀硕士论文)" for his thesis "Research on Graph Neural Network Algorithms and its Application on Recommender Systems". Congratulations!
[5/2022]: One paper on "Automated Black-box Attacks for Recommendations" was accepted to SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022, CCF-A, acceptance rate 14.9%).
[5/2022]: One paper on "Automated Feature Engineering" was accepted to AutoML-Conf 2022 Conference (the 1st International Conference on Automated Machine Learning, acceptance rate 19.2%).
[4/2022]: Two full papers on "Automated Recommendation System" were accepted to ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022, CCF-A).
[1/2022]: One paper on "Graph Neural Architecture Search" was accepted to IEEE International Conference on Data Engineering (IEEE ICDE 2022, CCF-A).
[1/2022]: Received an Open Fund from Zhejiang Lab to support our research on automated graph learning. Thanks Zhejiang Lab!
[10/2021]: One paper on “Architecture Search for Tree Models" was accepted to Machine Learning Journal (MLJ,CCF B).
[8/2021]: Granted by the National Natural Science Foundation of China （国家自然科学基金青年基金）on AutoML！
[6/2021]: Granted by the Natural Science Foundation of Jiangsu Province（江苏省自然科学基金青年基金）on Graph Neural Network！
[2/2021]: One paper on "AutoSpeech (Automatic Speech Classification)" was accepted to PAKDD 2021.
[8/2020]: Our team won the 2nd place in the AutoML Track (AutoGraph) of KDD Cup 2020.
[5/2020]: Our team won the 2nd place in the AutoSpeech Challenge held in InterSpeech 2020.
[4/2020]: Our team won the 3rd place in the AutoDL Challenge held in NeurIPS 2019.
[10/2019]: Our team won the 1nd place in the AutoSpeech/AutoDL Challenge held in NeurIPS 2019.
Research Interests
My research interests include Big Data Processing, Automated Machine Learning, Graph Machine Learning, and Intelligent Computing System Optimization. Especially in,
Distributed and parallel data mining and machine leraning in the big data scenario
Automated machine learning for various data types (e.g., Table, Image, Speech, Graph) and various application scenarios (e.g., NAS, Recommendation, System Optimization)
Graph neural network algorithm, application, and system
Large Model Fine-tuning and Efficient Inference
Teaching
AI Computing Systems [Spring 2022, Fall 2022, Fall 2023, Fall 2024]
Synthesis Experiments of Big Data Processing [Spring 2022, Spring 2023, Spring 2024, Spring 2025]
Introduction to Computer Systems [Fall 2021, Fall 2023, Fall 2024]
Publications
Selected Papers(* Corresponding Author)
Fengyi Wang, Guanghui Zhu*, Hongqing Ding, Pengfei Zhang, Chunfeng Yuan, and Yihua Huang. Boosting Temporal Graph Learning From Perspectives of Global and Local Structures. IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2025, CAAI A & CCF B), accepted (Regular Paper), 2025.
Guanghui Zhu*, Zhennan Zhu, Hongyang Chen, Chunfeng Yuan, and Yihua Huang. HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks. IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2025, CAAI A & CCF B), accepted (Regular Paper), 2025.
Fengyi Wang, Guanghui Zhu*, Haojun Hou, Chunfeng Yuan, and Yihua Huang. Mining Long Short-Term Evolution Patterns for Temporal Knowledge Graph Reasoning. Proc. of the 27th International Conference on Pattern Recognition (ICPR 2024, CAAI B & CCF C), accepted (Research Track), 2024.
Shen Jiang, Guanghui Zhu*, Yue Wang, Chunfeng Yuan, and Yihua Huang. Automatic Multi-Task Learning Framework with Neural Architecture Search in Recommendations (SIGKDD 2024,CCF A), accepted (Research Track), 2024.
Fengyi Wang, Guanghui Zhu*, Chunfeng Yuan, and Yihua Huang. LLM-enhanced Cascaded Multi-level Learning on Temporal Heterogeneous Graphs. Proc. of the ACM 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024,CCF A), pp. 512-521, 2024.
Guanghui Zhu, Mengyu Chen, Chunfeng Yuan, and Yihua Huang. Simple and Efficient Partial Graph Adversarial Attack: A New Perspective. IEEE Transactions on Knowledge and Data Engineering (TKDE 2024, CCF-A), 36(8): 4245-4259 , 2024.
JingYan Chen, Guanghui Zhu*, Chunfeng Yuan, and Yihua Huang. Boosting Graph Anomaly Detection with Adaptive Message Passing. Proc. of the 12th International Conference on Learning Representations (ICLR 2024), 2024.
袁春风 余子濠 朱光辉等. 计算机系统导论课程教学思路及课程资源建设. 《计算机教育》（“101计划”课程建设专题），2023年11期 No.347
Shen Jiang, Zipeng Ji, Guanghui Zhu*, Chunfeng Yuan, and Yihua Huang. Operation-Level Early Stopping for Robustifying Differentiable NAS. Proc. of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023, CCF-A), pp. 70983-71007, 2023.
Guanghui Zhu, Haojun Hou, Peiliang Wang, Chunfeng Yuan, and Yihua Huang. STSD: Modeling Spatial Temporal Staticity and Dynamicity in Traffic Forecasting. Proc. of the 23rd IEEE International Conference on Data Mining (ICDM 2023,CCF B), pp. 1565-1570, 2023.
Guanghui Zhu, Wang Lu, Chunfeng Yuan, and Yihua Huang. AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering. Proc. of the ACM 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023,CCF A), pp. 1076-1085, 2023.
朱光辉，祁加豪，朱振南，袁春风，黄宜华. 渐进式深度集成架构搜索算法研究. 计算机学报，Vol. 46 (10): 2041-2065，2023.
Rong Gu, Yi Zhang, Liangliang Yin, Lingyi Song, Wenjie Huang, Chunfeng Yuan, Zhaokang Wang, Guanghui Zhu*, Yihua Huang*. Coral: Federated Query Join Order Optimization based on Deep Reinforcement Learning. World Wide Web Journal (WWWJ, CCF-B). 26: 3093-3118, 2023.
Guanghui Zhu, Zhennan Zhu, Wenjie Wang, Zhuoer Xu, Chunfeng Yuan, and Yihua Huang. AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network. Proc. of the IEEE 39th International Conference on Data Engineering (ICDE 2023,CCF A), pp. 2808-2821, 2023.
朱光辉，陈文忠，朱振南，袁春风，黄宜华. 基于自引导进化策略的高效自动化数据增强算法研究. 软件学报，35(6): 3013-3035, 2024.
Zhuoer Xu, Guanghui Zhu*, Changhua Meng, Shiwen cui, Zhenzhe Ying, Weiqiang Wang, Ming GU, and Yihua Huang. A2: Efficient Automated Attacker for Boosting Adversarial Training . Proc. of the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022, CCF-A, Spotlight Paper!), pp. 22844-22855, 2022.
Jingfan Chen, Guanghui Zhu*, Yifan Qi, Chunfeng Yuan, and Yihua Huang. Towards Self-supervised Learning on Graphs with Heterophily. Proc. of the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022,CCF B), pp. 201-211, 2022.
Guanghui Zhu, Shen Jiang, Xu Guo, Chunfeng Yuan, and Yihua Huang. Evolutionary Automated Feature Engineering. Proc. of the 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2022, CCF C), pp.574-586, 2022.
Guanghui Zhu, Zhuoer Xu, Chunfeng Yuan, and Yihua Huang. DIFER: Differentiable Automated Feature Engineering. Proc. of the 1st International Conference on Automated Machine Learning (AutoML-Conf 2022), PMLR 188:17/1-17, 2022.
Jingfan Chen, Wenqi Fan, Guanghui Zhu*, Xiangyu Zhao, Chunfeng Yuan, Qing Li, and Yihua Huang. Knowledge-enhanced Black-box Attacks for Recommendations. Proc. of the 28rd SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2022,CCF A), pp. 108-117, 2022.
Guanghui Zhu, Feng Cheng, Defu Lian, Chunfeng Yuan, and Yihua Huang. NAS-CTR: Efficient Neural Architecture Search for Click-Through Rate Prediction. Proc. of the ACM 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022,CCF A), pp. 332-342, 2022.
Jingfan Chen, Guanghui Zhu*, Haojun Hou, Chunfeng Yuan, and Yihua Huang. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation. Proc. of the ACM 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022,CCF A), pp. 1694-1704, 2022.
Guanghui Zhu, Wenjie Wang, Zhuoer Xu, Feng Cheng, Mengchuan Qiu, Chunfeng Yuan, and Yihua Huang. PSP: Progressive Space Pruning for Efficient Graph Neural Architecture Search. Proc. of the IEEE 38th International Conference on Data Engineering (ICDE 2022,CCF A), pp. 2168-2181, 2022.
Zhuoer Xu, Guanghui Zhu*, Chunfeng Yuan, and Yihua Huang. One-Stage Tree: End-to-End Tree Builder and Pruner. Machine Learning Journal (MLJ, CCF B), 111: 1959–1985, 2022.
Zhaokang Wang, Junhong Li, Yifan Qi, Guanghui Zhu*, Chunfeng Yuan, and Yihua Huang*. UniGPS: A Unified Programming Framework for Distributed Graph Processing. Proc. of the 27th International Conference on Parallel and Distributed Systems (ICPADS,CCF C), accepted, 2021.
Guanghui Zhu, Feng Cheng, Mengchuan Qiu, Zhuoer Xu, Wenjie Wang, Chunfeng Yuan, and Yihua Huang. Progressive AutoSpeech: An Efficient and General Framework for Automatic Speech Classification. Proc. of the 25th Pacific-Asia Conference on Knowledge Discovery andData Mining (PAKDD,CCF C), pp. 168-180, India, 2021.
Guanghui Zhu and Ruancheng Zhu. Accelerating Hyperparameter Optimization of Deep Neural Network via Progressive Multi-Fidelity Evaluation. Proc. of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD,CCF C), pp. 752-763, Singapore, 2020.
Guanghui Zhu, Qian Wang, Qiwei Tang, Rong Gu, Chunfeng Yuan, and Yihua Huang. Efficient and Scalable Functional Dependency Discovery on Distributed Data-Parallel Platforms. IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS,CCF A), 2019, 30(12): 2663-2676.
Guanghui Zhu, Xiaoqi Wu, Liangliang Yin, Haogang Wang, Rong Gu, Chunfeng Yuan, and Yihua Huang. HyMJ: A Hybrid Structure-Aware Approach to Distributed Multi-Way Join Query. Proc. of the IEEE 35th International Conference on Data Engineering (IEEE ICDE, CCF A), pp. 1726-1729, Macao, China, 2019.
Guanghui Zhu, Qiu Hu, Rong Gu, Chunfeng Yuan, and Yihua Huang. ForestLayer: Efficient Training of Deep Forests on Distributed Task-Parallel Platforms. Journal of Parallel and Distributed Computing (JPDC,CCF B), 2019, 132: 113-126.
Guanghui Zhu, Chen Guo, Le Lu, Zhi Huang, Chunfeng Yuan, Rong Gu, and Yihua Huang. DGST: Efficient and Scalable Suffix Tree Construction on Distributed Data-Parallel Platforms. Parallel Computing (PARCO, CCF B), 2019, 87: 87-102.
Guanghui Zhu, Xiaoqi Wu, Rong Gu, Chunfeng Yuan, and Yihua Huang. AutoMJ: Towards Efficient Multi-Way Join Query on Distributed Data-Parallel Platform. Proc. of the 23rd International Conference on Parallel and Distributed Systems (IEEE ICPADS), pp. 161-169, Shenzhen, China, 2017.
朱光辉，黄圣彬，袁春风，黄宜华. SCoS: 基于Spark 的并行谱聚类算法设计与实现.计算机学报，2018, Vol. 41 (4): 868-885.
Selected Honours & Awards
2024年度英特尔中国学术英才计划（Intel China Academic Excellence Program）
2024年度中国人工智能学会-华为MindSpore学术奖励基金
第五届中国“互联网+”大学生创新创业大赛全国金奖（项目负责人）
华为“难题揭榜”火花奖
海军首届“金海豚”杯算法挑战赛优秀成果奖
2022年度江苏省计算机学会优秀博士论文奖
2022年度江苏省“双创博士”人才计划
《人工智能计算系统》课件荣获教育部-华为 “智能基座”产教融合协同育人基地优秀课件奖励计划
bw必威西汉姆联官网“师德先进”团队（计算机系统能力培养教学研究与建设团队）
2024年度bw必威西汉姆联官网本科教学“刘厚俊教奖金”
教育部-华为 “智能基座” 先锋教师
教育部-华为 “智能基座” 栋梁之师
第八届全国计算机类课程实验教学案例设计竞赛二等奖
昇腾AI创新大赛2023江苏赛区区域决赛开发者创新赛道银奖（第二名）
华为昇腾众智项目“金质量奖“
Win the Second Place in the AutoML Track:AutoGraph Challenge, KDD 2020 (Rank: 2/149).
Win the Second Place in the AutoSpeech Challenge, InterSpeech 2020 (Rank: 2/24).
Win the Third Place in the AutoDL Challenge, NeurIPS 2019 (Rank: 3/54).
Win the First Place in the AutoSpeech/AutoDL Challenge, NeurIPS 2019 (Rank: 1/33).
Win the Eighth Place in the AutoML Challenge (AutoML for Temporal Relational Data), KDD 2019 (Rank: 8/860).
Win the Fourth Place in the AutoWSL Challenge (AutoML for Weakly Supervised Learning), ACML 2019 (Rank: 4/27).
Win the Seventh Place in the AutoNLP Challenge (AutoML for Natural Language Processing), WAIC 2019 (Rank: 7/66).
Win the Third Place in the Feedback Phase of the AutoML Challenge (AutoML for Lifelong Learaning), NeurIPS 2018 (Rank:3/360).
Win the Third Place in the Automl Challenge, PAKDD 2018 (Rank:3/250).
Academic Service
PC Member & Reviewer:
- NeurIPS 2023/2024
- ICML 2024
- ICLR 2024/2005
- KDD 2023/2024/2025
- AAAI 2001/2025
- SIGIR 2023/2024
- CIKM 2024
- SDM 2024
- DASFAA 2024
- IEEE Transactions on Knowledge and Data Engineering (TKDE) (Reviewer)
- IEEE Transactions on Parallel and Distributed System (TPDS) (Reviewer)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (Reviewer)
- Neural Networks (Reviewer)
- 计算机学报 (Reviewer)
Services:
- Executive Member of CCF Expert Committee on Big Data (CCF大数据专家专委会执行委员)
- Executive Member of CCF Technical Committee on Artificial Intelligence & Pattern Recognition (CCF人工智能与模式识别专委会执行委员)
- Member of CICC Technical Committee on Large Foundation Model and Decision Intelligence (中国指控学会大模型与决策智能专委会委员)
- Secretary-General of the Jiangsu Computer Society Big Data Committee (江苏省计算机学会大数据专委会秘书长)
- CCF YOCSEF Nanjing Vice-Chairman (CCF YOCSEF南京副主席)
- 《大数据挖掘与分析（英文）》BDMA期刊（CCF高质量科技期刊T2）青年编委
- Member of CCF Technical Committee on Distributed Computing and Systems (CCF分布式计算与系统专业委员会委员)
- Member of the Jiangsu Computer Society System Architecture Committee (江苏省计算机学会系统结构专委会委员)
Students
Current Members (co-adviced with Prof. Yihua Huang)
- 2023: Yue Wang, Shen Jiang
- 2022: Jingyan Chen, Zipeng Ji, Fengyi Wang, Lang Guo
- 2021: Zhennan Zhu, Wang Lu, Mengyu Chen, Peiliang Wang
Alumni (co-adviced with Prof. Yihua Huang)
- 2020: Shen Jiang (Ph.D. Nanjing University) HaoJun Hou (Alibaba), Yifan Qi (Baidu), Xiao Sun (NARI Group)
- 2019: Feng Cheng (Huawei FX Program), Jingfan Chen (Ph.D. The Hong Kong Polytechnic University), Zhuoer Xu (Ant Group), Wenjie Wang (ByteDance)