罗昕，博士，山东大学软件学院副教授，硕士生导师。入选山东省青年科技人才托举工程、山东大学青年学者未来计划。2010年进入国家基础学科拔尖学生培养试验计划(珠峰计划)山东大学“泰山学堂”，2014年获得学士学位；于2019年3月申请提前答辩并顺利通过，在山东大学计算机科学与技术学院获得博士学位；毕业后留校任教。

    主要研究领域为机器学习、机器视觉、数据挖掘、信息检索和图像/视频内容分析与检索等。在国际学术期刊和会议上发表论文50余篇，如WWW、AAAI、MM、IJCAI、SIGIR、TIP等。已获得国家授权的发明专利10余项。曾获山东省人工智能优秀青年奖（1/1）、ACM新星奖(济南分会 1/1）、山东省人工智能科技进步一等奖（3/6）、山东大学校长奖、山东大学优秀博士论文等荣誉。教育教学方面获山东省高校青年教师教学比赛二等奖（1/1）、山东省青教赛三等奖（1/1）、山东省人工智能学会教学成果一等奖（1/3）、山东大学青年教学能手称号、山东大学优秀班主任、山东大学青年教师教学比赛一等奖、山东大学课程思政教学名师、山东大学优秀本科毕业论文（设计）指导奖，担任山东大学校级教学咨询员。

    现任中国计算机学会高级会员，中国计算机学会人工智能与模式识别专业委员会执行委员，中国计算机学会多媒体技术专业委员会通讯委员，中国人工智能学会机器学习专业委员会通讯委员，山东省人工智能学会理事，山东省神经科学学会理事。担任ACM MM、AAAI、IJCAI等国际学术会议的程序委员会委员，并担任IEEE TIP、IEEE TCYB、IEEE TMM、IEEE TKDE等国际学术期刊审稿人。

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招生信息

**2025年9月入学的招生名额情况（动态更新中）：

专项计划的同学仍可以与我联系。专项计划外的学硕、专硕（不区分专业）已无空余名额。

山东大学机器学习与媒体分析实验室(MIMA)成立于2012年，隶属于山东大学软件学院，其负责人是许信顺教授。实验室每年招收博士后1－2人，博士生1－2人，硕士生6-12人，欢迎软件、计算机、人工智能、数学和信息等相关专业的同学加入。

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Education:

◼ Shandong University, Jinan, China (Sep 2014 - Mar 2019)

   - Doctor of Philosophy (Ph.D.), Computer Science and Technology

   - Advisor: Prof. Xin-Shun Xu  (许信顺教授) and Prof. Liqiang Nie (聂礼强教授)

◼ Shandong University, Jinan, China (Sep 2010 - Jun 2014)

   - Bachelor of Science (B.S.), Computer Science and Technology

   - In particular, I was a member of Taishan College. (泰山学堂)

◼ National University of Singapore, NUS, Singapore (Jan 2018 - Feb 2019)  

   - Visiting student, in NEXT++, School of Computing

   - Advised by Prof. Tat-Seng Chua.   

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Academic Service:

Journal Reviewer

-IEEE Transactions on Circuits and Systems for Video Technology 

-IEEE Transactions on Cybernetics

-IEEE Transactions on Knowledge and Data Engineering

-IEEE Transactions on Multimedia

-IEEE Transactions on Neural Networks and Learning System

-IEEE Transactions on Big Data

-IEEE Access

-IEEE Transactions on Artificial Intelligence

-IEEE Transactions on Image Processing

-IEEE Transactions on Systems, Man, and Cybernetics: Systems

-ACM Transactions on Information Systems

-ACM Transactions on Multimedia Computing, Communications, and Applications

-Information Processing and Management

-Information Sciences

-Pattern Recognition

-Journal of Software

-SCIENCE CHINA Information Sciences

-Knowledge-Based Systems

-Neurocomputing

-Wireless Communications and Mobile Computing

-Signal Processing Journal

-Multimedia System

-EURASIP Journal on Image and Video Processing

-Neural Processing Letters

-Frontiers of Computer Science

-DISPLAYS

-Applied Intelligence

-Expert Systems With Applications

-Big Data Research

Conference Reviewer

-International Joint Conference on Artificial Intelligence 2021/2022/2023/2024/2025 - PC member

-AAAI Conference on Artificial Intelligence 2021/2022/2023/2024/2025 - PC member 

-ACM International Conference on Multimedia 2019/2020/2021/2022/2023/2024 - PC member 

-ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2022/2023 - PC member

-IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 - PC member

-IEEE International Conference on Acoustics, Speech, & Signal Processing 2023/2024/2025 - PC member

-IEEE International Conference on Multimedia and Expo 2023 - PC member

-European Conference on Machine Learning and Principles and Practice of KnowledgeDiscovery in Databases 2023 - PC member

-Pacific-Asia Conference on Knowledge Discovery and Data Mining 2022/2023/2024/2025 -  PC member

-International Joint Conference on Neural Networks 2025 -  PC member

-CCF Conference on Artificial Intelligence (CCFAI)  2021/2023 - PC member 

-ACM Multimedia Asia 2020/2021/2022/2023/2024 - PC member

-International Conference on Web Search and Data Mining 2022 - PC member

-China Conference on Machine Learning (CCML) 2023

-China Conference on Data Mining (CCDM) 2020/2022/2024

-ChinaMM 2020

-Annual Meeting of the Association for Computational Linguistics

-Pacific-Rim Conference on Multimedia

-International Conference on Machine Learning and Machine Intelligence (MLMI) 2023 - PC member

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主持的科研、教研项目

2024，山东省青年科技人才托举工程，山东省科协项目

2024，多模态数据存储与索引关键技术研究与应用，横向

2023，机器学习课程线上线下混合教学模式探索与实践，校级教改一般项目

2023，面向类增量场景的在线哈希学习方法研究，省级重点实验室开放基金项目

2023，面向大规模流式多媒体数据的快速跨模态检索相关问题研究，国家自然科学基金青年项目

2022，基于联邦学习的5G基站能耗及切片优化模型研究，横向

2022，山东大学青年学者未来计划项目，山东大学人才计划

2021，深度学习轻量化模型研究与应用，横向

2021，面向复杂场景下的多媒体数据的快速检索研究，山东省自然科学基金青年项目

2021，2021年度课程思政示范项目，校级

2021，AI课程思政教学设计与实践研究，以“机器学习”课程为例，校级教改一般项目

2020，研究生国际化课程-深度学习与应用，校级

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Full Publication List: （Google Scholar：https://scholar.google.com/citations?user=ZaCsoy0AAAAJ）

In the year of 2024:

ØYu-Wei Zhan, Xin Luo*, Zhen-Duo Chen, Yongxin Wang, Yinwei Wei, Xin-Shun Xu. POLISH: Adaptive Online Cross-Modal Hashing for Class Incremental Data. The Web Conference (WWW), 2024. (Full, CCF A)  [code will be available soon]

ØTing Fu, Yu-Wei Zhan, Chong-Yu Zhang, Xin Luo*, Zhen-Duo Chen, Yongxin Wang, Xun Yang, Xin-Shun Xu. FedCAFE: Federated Cross-Modal Hashing with Adaptive Feature Enhancement. The ACM International Conference on Multimedia (MM). 2024. (Full, CCF A)  [code will be available soon]

ØZhen-Duo Chen, Li-Jun Zhao, Zi-Chao Zhang, Xin Luo, Xin-Shun Xu. Characteristics Matching Based Hash Codes Generation for Efficient Fine-grained Image Retrieval. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (Full, CCF A) 

ØXiao-Qian Liu, Peng-Fei Zhang, Xin Luo, Zi Huang, Xin-Shun Xu. TextAdapter: Self-supervised Domain Adaptation for Cross-domain Text Recognition. IEEE Transactions on Multimedia, 2024.  (SCI CCF B)

ØLi-Jun Zhao, Zhen-Duo Chen, Zhen-Xiang Ma, Xin Luo, Xin-Shun Xu. Angular Isotonic Loss Guided Multi-Layer Integration for Few-shot Fine-grained Image Classification. IEEE Transactions on Image Processing, 2024. (SCI CCF A)

ØZhen-Xiang Ma, Zhen-Duo Chen, Li-Jun Zhao, Zi-Chao Zhang, Tai Zheng, Xin Luo, Xin-Shun Xu. Bi-directional Task-Guided Network for Few-Shot Fine-Grained Image Classification. The ACM International Conference on Multimedia (MM). 2024. (Full, CCF A) 

ØXiaoqian Liu, Ming-Hui Liu, Zhen-Duo Chen, Xin Luo, Xin-Shun Xu. Hierachical Multi-label Learning for Incremental Multilingual Text Recognition. The ACM International Conference on Multimedia (MM). 2024. (Full, CCF A) 

In the year of 2023:

ØChong-Yu Zhang, Xin Luo*, Yu-Wei Zhan, Peng-Fei Zhang, Zhen-Duo Chen, Yongxin Wang, Xun Yang, and Xin-Shun Xu. Self-Distillation Dual-Memory Online Hashing with Hash Centers for Streaming Data Retrieval. In proceedings of the ACM International Conference on Multimedia (MM). 2023. (Full, CCF A)   [code is available]

ØYan Wang, Xin Luo*, Zhen-Duo Chen, Peng-Fei Zhang, Meng Liu, and Xin-Shun Xu. FedVMR: A New Federated Learning Method for Video Moment Retrieval. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2023.  (Full, CCF B) [code is available]

ØJiale Liu, Yu-Wei Zhan, Xin Luo*, Zhen-Duo Chen, Yongxin Wang, and Xin-Shun Xu. Prototype-Based Layered Federated Cross-Modal Hashing. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2023. (Full, CCF B) [code is available]

Ø Tianyu Chang, Xun Yang, Xin Luo, Wei Ji, and Meng Wang. Learning Style-Invariant Robust Representation for Generalizable Visual Instance Retrieval. In proceedings of the ACM International Conference on Multimedia (MM). 2023. (Full, CCF A) 

Ø Meng Liu, Fenglei Zhang, Xin Luo, Fan Liu, Yinwei Wei, and Liqiang Nie. Advancing Video Question Answering with a Multi-modal and Multi-layer Question Enhancement Network. In proceedings of the ACM International Conference on Multimedia (MM). 2023. (Full, CCF A) 

Ø Yunxiao Wang, Meng Liu, Zhe Li, Yupeng Hu, Xin Luo, and Liqiang Nie. Unlocking the Power of Multimodal Learning for Emotion Recognition in Conversation. In proceedings of the ACM International Conference on Multimedia (MM). 2023. (Full, CCF A) 

Ø Xiao-Qian Liu, Xue-Ying Ding, Xin Luo, and Xin-Shun Xu. Unsupervised Domain Adaptation via Class Aggregation for Text Recognition. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). 2023. ( SCI, CCF B) 

Ø Tian-Zi Niu, Shan-Shan Dong, Zhen-Duo Chen, Xin Luo, Shanqing Guo, Zi Huang, and Xin-Shun Xu. Semantic Enhanced Video Captioning with Multi-feature Fusion. ACM Transactions on Multimedia Computing Communications and Applications (TOMM). 2023. (SCI, CCF B)

Ø Tian-Zi Niu, Zhen-Duo Chen, Xin Luo, Peng-Fei Zhang, Zi Huang, and Xin-Shun Xu. Video Captioning by Learning from Global Sentence and Looking Ahead. ACM Transactions on Multimedia Computing Communications and Applications (TOMM). 2023. (SCI, CCF B)

ØXue-Ying Ding, Xiao-Qian Liu, Xin Luo, and Xin-Shun Xu. DOC: Text Recognition via Dual Adaptation and Clustering. IEEE Transactions on Multimedia (TMM). 2023. (SCI, CCF B) 

ØYali Du, Yinwei Wei , Wei Ji, Fan Liu, Xin Luo, and Liqiang Nie. Multi-queue Momentum Contrast for Microvideo-Product Retrieval. ACM International Conference on Web Search and Data Mining (WSDM). 2023. (CCF B)

ØZi-Chao Zhang, Zhen-Duo Chen, Zhen-Yu Xie, Xin Luo, and Xin-Shun Xu. S3Mix: Same Category Same Semantics Mixing for Augmenting Fine-grained Images. ACM Transactions on Multimedia Computing, Communications and Applications  (TOMM). 2023. (SCI, CCF B)

Ø Jia-Nan Li, Xiao-Qian Liu, Xin Luo, Xin-Shun Xu. VOLTER: Visual Collaboration and Dual-Stream Fusion for Scene Text Recognition. IEEE Transactions on Multimedia (TMM). 2023.  (SCI, CCF B)

Ø  Xiao-Qian Liu, Xue-Ying Ding, Xin Luo, Xin-Shun Xu. ProtoUDA: Prototype-based Unsupervised Adaptation for Cross-Domain Text Recognition. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2023.  (SCI, CCF A)

Ø Yongxin Wang, Yu-Wei Zhan, Zhen-Duo Chen, Xin Luo, Xin-Shun Xu. Multiple Information Embedded Hashing for Large-Scale Cross-Modal Retrieval. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). 2023.  (SCI, CCF B)

Ø Hao-Chen Pei, Hao Fang, Xin Luo, and Xin-Shun Xu. Gradformer: A Framework for Multi-Aspect Multi-Granularity Pronunciation Assessment. IEEE/ACM Transactions on Audio, Speech and Language Processing (IEEE/ACM TASLP). 2023.  (SCI, CCF B)

Ø Zi-Chao Zhang, Zhen-Duo Chen, Yongxin Wang, Xin Luo, Xin-Shun Xu. A vision transformer for fine-grained classification by reducing noise and enhancing discriminative information. Pattern Recognition (PR). 2023.  (SCI, CCF B)

Ø Zi-Chao Zhang, Zhen-Yu Xie, Zhen-Duo Chen, Yu-Wei Zhan, Xin Luo, Xin-Shun Xu. Expansion window local alignment weighted network for fine-grained sketch-based image retrieval. Pattern Recognition (PR). 2023.  (SCI, CCF B)

In the year of 2022:

ØXiao-Ming Wu, Xin Luo*, Yu-Wei Zhan, Chen-Lu Ding, Zhen-Duo Chen, and Xin-Shun Xu. Online enhanced semantic hashing: Towards effective and efficient retrieval for streaming multi-modal data. AAAI Conference on Artificial Intelligence (AAAI). 2022. (Full, CCF A)  [code is available]

Ø Yan Wang, Yu-Wei Zhan, Xin Luo*, Meng Liu,  and Xin-Shun Xu. Survey on video moment retrieval. Journal of Software (软件学报). 2022, Accepted. (In Chinese, CCF A) 

ØChen-Lu Ding, Xin Luo*, Xiao-Ming Wu, Yu-Wei Zhan, Rui Li, Hui Zhang, and Xin-Shun Xu. Weakly-Supervised Online Hashing with Refined Pseudo Tags. ACM International Conference on Information and Knowledge Management  (CIKM). 2022.  (Full, CCF B)  [code is available]

ØYu-Wei Zhan,Xin Luo*, Yongxin Wang, Zhen-Duo Chen,  and Xin-Shun Xu. Three-stream joint network for zero-shot sketch-based image retrieval. 2022, arXiv.  [paper]

ØYan Wang, Xin Luo*, Zhen-Duo Chen, Peng-Fei Zhang, Meng Liu, Xin-Shun Xu. FedVMR: A New Federated Learning method for Video Moment Retrieval. 2022, arXiv. [paper]

ØJiale Liu, Yu-Wei Zhan, Xin Luo*, Zhen-Duo Chen, Yongxin Wang, Xin-Shun Xu. Prototype-Based Layered Federated Cross-Modal Hashing. 2022, arXiv. [paper]

ØZhen-Duo Chen, Xin Luo, Yongxin Wang, Shanqing Guo, and Xin-Shun Xu. Fine-grained hashing with double filtering. IEEE Transactions on Image Processing (TIP). 2022, 31, 1671-1683. (SCI, CCF A, IF=10.856）  [code is available]

Ø  Yongxin Wang, Zhen-Duo Chen, Xin Luo, and Xin-Shun Xu. A High-Dimensional Sparse Hashing Framework for Cross-Modal Retrieval. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT). 2022. ( SCI, CCF B,  IF=5.859)   [code is available]

Ø  Tian-Zi Niu, Shan-Shan Dong, Zhen-Duo Chen, Xin Luo, Zi Huang, Shanqing Guo, and Xin-Shun Xu. A Multi-layer Memory Sharing Network for Video Captioning. Pattern Recognition, 2022. (SCI, CCF B)

ØXinyu Liu, Xiaoqian Liu, Bin Wang,  Xin Luo, and Xin-Shun Xu. Arbitrary-shaped scene text detection with scoring mask quality. IEEE International Conference on Multimedia & Expo (ICME). 2022. (CCF B)

ØShanshan Dong, Tianzi Niu,  Xin Luo, Wu Liu, and Xin-Shun Xu. Semantic embedding  guided attention with explicit visual feature fusion for video captioning. ACM Transactions on Multimedia Computing Communications and Applications (TOMM). 2022. (CCF B)

ØJieru Tian, Yongxin Wang, Zhen-Duo Chen, Xin Luo, and Xin-Shun Xu. Weakly-Supervised Fine-Grained Classification of Breast Cancer. ACM Transactions on Intelligent Systems and Technology (TIST). 2022. (SCI)

ØPeng-Fei Zhang, Zi Huang, Xin Luo, Pengfei Zhao. Robust Learning with Adversarial Perturbations and Label Noise: A Two-Pronged Defense Approach.  ACM Multimedia Asia. 2022. (Regular)

ØZi-Chao Zhang, Zhen-Duo Chen, Yongxin Wang, Xin Luo, and Xin-Shun Xu. ViT-FOD: A vision transformer based fine-grained object discriminator. 2022, arXiv.  [paper]

In the year of 2021:

ØYongxin Wang, Zhen-Duo Chen, Xin Luo*, and Xin-Shun Xu. High-dimensional sparse cross-modal hashing with fine-grained similarity embedding. In proceedings of the Web Conference (WWW). 2021, 2900-2909. (Full,Oral, CCF A)   [code is available]

ØHui-Qiong Li, Yongxin Wang, Zhen-Duo Chen, Xin Luo*, and Xin-Shun Xu. Ranking-based supervised discrete cross-modal hashing. Chinese Journal of Computers (计算机学报). 2021, 44(8): 1620-1635. (In Chinese, CCF A) 

ØYu-Wei Zhan, Yongxin Wang, Yu Sun, Xiao-Ming Wu, Xin Luo*, and Xin-Shun Xu. Discrete online cross-modal hashing.Pattern Recognition, 2021, 108262. (SCI, CCF B, IF=7.740) [code is available]

ØYu-Wei Zhan, Xin Luo*, Yu Sun, Yongxin Wang, Zhen-Duo Chen, and Xin-Shun Xu. Weakly-supervised online hashing. IEEE International Conference on Multimedia & Expo (ICME). 2021. (Full, Oral, CCF B) [code is avaiable] 

ØHong-Lei Yao, Yu-Wei Zhan, Zhen-Duo Chen, Xin Luo*, and Xin-Shun Xu. TEACH: Attention-aware deep cross-modal hashing. ACM International Conference on Multimedia Retrieval (ICMR'21), 2021. (Full, oral, CCF B)

ØXiao-Ming Wu, Xin Luo*, Yu-Wei Zhan, Chen-Lu Ding, Zhen-Duo Chen, and Xin-Shun Xu. Online enhanced semantic hashing: Towards effective and efficient retrieval for streaming multi-modal data. 2021, arXiv. [paper]

ØYongxin Wang, Jie-Ru Tian, Zhen-Duo Chen, Xin Luo,  and Xin-Shun Xu. Label enhancement discrete cross-modal hashing method. Journal of Software (软件学报). 2021, Accepted. (In Chinese, CCF A) 

ØYongxin Wang, Zhen-Duo Chen, Xin Luo, Rui Li, and Xin-Shun Xu. Fast cross-modal hashing with global and local similarity embedding. IEEE Transactions on Cybernetics(TCYB). 2021. (SCI, CCF B) [code is avaiable]

ØPeng-Fei Zhang, Pengfei Zhao, Xin Luo, and Xin-Shun Xu. BRUSH: Label reconstructing and similarity preserving hashing for cross-modal retrieval.  ACM Multimedia Asia. 2021. (Regular)

In the year of 2020:

ØYu-Wei Zhan, Xin Luo*, Yongxin Wang, and Xin-Shun Xu. Supervised hierarchical deep hashing for cross-modal retrieval. In proceedings of the ACM International Conference on Multimedia (MM). 2020, 3386-3394. (Full, Poster, CCF A) [code is avaiable]

ØYu-Wei Zhan, Xin Luo*, Yu Sun, Yongxin Wang, Zhen-Duo Chen, Xin-Shun Xu. Weakly-supervised online hashing. 2020, arXiv.  [paper]

ØYongxin Wang, Xin Luo, Xin-Shun Xu. Label embedding online hashing for cross-modal retrieval. In proceedings of the ACM International Conference on Multimedia(MM).2020,871-879.(Full, Oral, CCF A) [code is avaiable]

ØYongxin Wang, Xin Luo, Liqiang Nie, Jingkuan Song, Wei Zhang, Xin-Shun Xu. BATCH: A scalable asymmetric discrete cross-modal hashing. IEEE Transactions on Knowledge and Data Engineering(TKDE), 2020, 33(11), 3507-3519.(SCI, CCF A, IF=3.85) [code is avaiable] 

In the year of 2019:

ØXin Luo, Peng-Fei Zhang, Zi Huang, Liqiang Nie, Xin-Shun Xu. Discrete hashing with multiple supervision. IEEE Transactions on Image Processing(TIP). 2019, 28(6): 2962-2975.(SCI, CCF A, IF=6.79)

ØZhen-Duo Chen, Yongxin Wang, Hui-Qiong Li, Xin Luo, Liqiang Nie, Xin-Shun Xu. A two-step cross-modal hashing by exploiting label correlations and preserving similarity in both steps. In proceedings of the ACM International Conference on Multimedia(MM). 2019,1694-1702.(Full, Oral, CCF A)

ØChuan-Xiang Li, Ting-Kun Yan, Xin Luo, Liqiang Nie, and Xin-Shun Xu. Supervised robust discrete multimodal hashing for cross-media retrieval. IEEE Transactions on Multimedia, 2019. (SCI, CCF B, IF=5.452)

ØZhen-Duo Chen, Chuan-Xiang Li, Xin Luo, Liqiang Nie, Wei Zhang, and Xin-Shun Xu. SCRATCH: A scalable discrete matrix factorization hashing framework for cross-modal retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 2019. ( SCI, CCF B,  IF=4.046)

ØYongxin Wang, Xin Luo, Huaxiang Zhang, and Xin-Shun Xu. Sparse manifold embedded hashing for multimedia retrieval. IEEE International Conference on Data Engineering Workshops, 2019. (ICDE Workshop)

ØWan-Jin Yu, Zhen-Duo Chen, Xin Luo, Wu Liu, and Xin-Shun Xu. DELTA:A deep dual-stream network for multi-label image classification.Pattern Recognition, 2019, 91, 322-331. (SCI, CCF B, IF=5.898) 

In the year of 2018:

ØChuan-Xiang Li, Zhen-Duo Chen, Peng-Fei Zhang, Xin Luo, Liqiang Nie, Wei Zhang, Xin-Shun Xu. SCRATCH: A scalable discrete matrix factorization hashing for cross-modal retrieval.In proceedings of the ACM International Conference on Multimedia(MM). 2018, 1-9.(Full, Poster, CCF A) [code is avaiable]

ØXin Luo, Xiao-Ya Yin, Liqiang Nie, Xuemeng Song, Yongxin Wang, Xin-Shun Xu. SDMCH: Supervised discrete manifold-embedded cross-modal hashing. In proceedings of the International Joint Conference on Artificial Intelligence(IJCAI). 2018,2518-2524.(Full, Oral, CCF A)

ØXin Luo, Liqiang Nie, Xiangnan He, Ye Wu, Zhen-Duo Chen, Xin-Shun Xu. Fast scalable supervised hashing. International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR).2018,735-744.(Full, Oral, CCF A)  [code is avaiable]

ØYe Wu, Xin Luo, Xin-Shun Xu, Shanqing Guo, and Yuliang Shi. Dictionary learning based supervised discrete hashing for cross-media retrieval. ACM International Conference on Multimedia Retrieval (ICMR'18), 2018. (Full, Spotlight, CCF B)

ØXin Luo, Peng-Fei Zhang, Ye Wu, Zhen-Duo Chen, Hua-Junjie Huang, and Xin-Shun Xu. Asymmetric discrete cross-modal hashing. ACM International Conference on Multimedia Retrieval (ICMR'18), 2018. (Full, Spotlight, CCF B)

ØXin Luo, Ye Wu, Wan-Jin Yu, and Xin-Shun Xu. Class consistent hashing for fast web data searching. World Wide Web Journal (WWWJ), 2018. (SCI, CCF B, IF=1.77)

ØXin Luo, Ye Wu, Xin-Shun Xu. Scalable supervised discrete hashing for large-scale search.In proceedings of the World Wide Web Conference (WWW). 2018,1603-1612. (Full, Oral, CCF A) 

In the year of 2017:

ØXin Luo, Zhen-Duo Chen, Gao-Yuan Du, and Xin-Shun Xu. Improving hashing by leveraging multiple layers of deep neural networks. International Conference on Neural Information Processing (ICONIP'17), 2017. (Full, Oral, CCF C)

ØKuikui Wang, Lu Yang, Gongping Yang, Xin Luo, Kun Su, and Yilong Yin. Finger vein image retrieval via coding scale-varied superpixel feature. ACM International Conference on Multimedia Retrieval (ICMR'17), 2017. (Full, Spotlight, CCF B) 

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教学技能工作坊ISW证书

山东省人工智能学会教学成果一等奖

第二届全国高校计算机课程思政教学案例设计大赛三等奖

山东省人工智能优秀青年奖

山东大学优秀本科毕业论文（设计）指导奖（丁陈璐）

山东省第十届高校青年教师教学比赛二等奖

CCF优秀大学生学术秀二等奖（本科生类别，指导学生：丁陈璐）

山东大学教师教学创新大赛二等奖（第三届）

山东省人工智能科技进步奖一等奖

山东大学优秀本科毕业论文（设计）指导奖（伍晓鸣）

山东省第九届高校青年教师教学比赛三等奖

山东大学教师教学创新大赛二等奖（第二届）

山东大学青年教学能手、山东大学青年教师教学比赛一等奖

山东大学课程思政教学名师、山东大学课程思政教学团队

山东大学软件学院青年教学能手、山东大学软件学院青年教师教学比赛一等奖

山东大学优秀班主任

ACM新星奖(济南分会)

山东省人工智能学会优秀博士论文

山东大学“同屏在线、共振育人”在线直播教学比赛三等奖

ACM优秀博士论文(济南分会)

山东大学校长奖学金

山东省优秀毕业生

山东大学研究生标兵

山东大学研究生优秀学术成果奖

国家奖学金

团队名称：山东大学机器学习与媒体分析实验室(MIMA)

团队介绍：http://mima.sdu.edu.cn/

    山东大学机器学习与媒体分析实验室(MIMA)成立于2012年，隶属于 山东大学 软件学院。目前研究组有教师5人，博士后2人，学生35人，其负责人是许信顺教授。

    MIMA的含义是 "Machine Intelligence & Media Analysis"，即“机器学习与媒体分析”。目前，MIMA的主要研究兴趣包括机器学习、信息检索、数据挖掘、机器视觉、模式识别、智能计算等领域。其中，具体的研究内容包括：集成学习、半监督学习、多示例学习，多标记学习、多示例与多标记学习、哈希学习、深度学习、降维与特征选择、神经网络、文本的分类和聚类、web的分类和聚类、图像与视频的内容分析与理解、基于内容的图像检索、 基于内容的视频检索、大数据分析等。

    实验室学术氛围浓厚，就业面广，毕业学生多人赴国外大学继续深造或者在知名企业、机关事业等单位就职。实验室每年招收博士后1－2人，博士生1－2人，硕士生6－12人，欢迎软件、计算机、人工智能、数学和信息等相关专业的同学加入。