王
王萌 (Meng Wang)
H指数:104
被引数:4.2万
个人简介
"王萌Assistant Professor, SEU Zhishan Young Scholar Please visit My homepage (请访问我的个人主页) Learn more about my research in Webcast: Bilibili (我的直播间) Greeting! I am working as an assistant professor in the Knowledge Graph & AI Research Group, School of Computer Science and Engineering, Southeast University, China. I am also an SEU Zhishan Young Scholar (东南大学至善青年学者,awarded in 2019). I obtained the doctoral degree from the Department of Computer Science and Technology, Xi’an Jiaotong University in 2018. I was a visiting scholar, working with Prof. Xue Li and Prof. Xiaofang Zhou, in the DKE lab at the University of Queensland, Australia in 2016. I have published 30+ papers in top international conferences including ISWC, AAAI, WWW, CIKM, IJCAI, ICSE.... My research area is in the knowledge graph (KG), semantic search, NLP, and cross-modal data. My research goal is to solve real problems with KG in real life, such as healthcare, education, and legal areas. I take supervision very seriously and enjoy healthy collaborations with my students. For highly motivated students(面向计算机、人工智能、软件、网络安全均可), please email me with your CV. Knowledge Graph & AI Research Group, School of Computer Science and Engineering, Southeast University, Nanjing, China, Assistant Professor, SEU Zhishan Young Scholar Github: wangmengsd Learn more about my research in Webcast: Bilibili (我的直播间) Tenure countdown: 209 weeks 4 days 13 hours 11 minutes 40 seconds Education and Experience | Publications | Awards | Academic Services | Joining Our Lab (实验室招生) | Resource (ppt) Greeting! I am working as an assistant professor in the Knowledge Graph & AI Research Group, School of Computer Science and Engineering, Southeast University, China. I am also a SEU Zhishan Young Scholar (awarded in 2019). I obtained the doctoral degree from the Department of Computer Science and Technology, Xi’an Jiaotong University in 2018, under the supervision of Prof. Jun Liu. I was a visiting scholar, working with Prof. Xue Li and Prof. Xiaofang Zhou, in the DKE lab at University of Queensland, Australia in 2016. My research area is in the knowledge graph (KG), semantic search, NLP, and cross-modal data. My research goal is to solve real problems with KG in real life, such as healthcare, education, and legal areas. News [Aug. 2020] We have one paper accepted at the ISWC 2020 ! [Jul. 2020] We have one paper accepted at the MM 2020 ! [Jul. 2020] We have one paper accepted at the CIKM 2020 ! [Feb. 2020] We have one paper accepted at the IJCAI 2020 ! [Jan. 2020] We have one paper accepted at the ECAI 2020 ! [Nov. 2019] We have one paper accepted at the AAAI 2020 ! [Aug. 2019] I was invited to do a report at CCKS 2019 (ppt). [Nov. 2018] Our IEEE International Conference on Big Knowledge 2018 paper got the best paper award ! [Oct. 2018] Our International Semantic Web Conference (ISWC) 2018 paper got the best student paper candidate ! Education and Experience Jan. 2019 - present. Zhishan Young Scholar (东南大学至善青年学者), Southeast University, Nanjing, China. Oct. 2018 - present. Assistant professor, in School of Computer Science and Engineering, Southeast University, Nanjing, China. Working with: Prof. Guilin Qi Sep. 2013 - Sep 2018. Ph.D., in Dept. of Computer Science and Technology, Xi’an Jiaotong University, Xi'an, China. Supervisor: Prof. Jun Liu Oct. 2017 - Mar. 2018. Researcher, in Healthcare Big Data Lab, Tencent, Shenzhen, China. Supervisor: Dr. Zhigang Chen Mar. 2016 - Mar. 2017. Visiting Scholar, in DKE lab, University of Queensland, Brisbane, Australia. Supervisor: Prof. Xue Li & Prof. Xiaofang Zhou Sep. 2012 - Jul. 2013. M.S., in Dept. of Computer Science and Technology, Xi’an Jiaotong University, Xi'an, China. Supervisor: Prof. Jun Liu Sep. 2008 - Jul. 2012. B.S., in School of Computer Science, Sichuan University, Chengdu, China. Sep. 2005 - Jul. 2008. Kangjie High School, Yuncheng, Shanxi, China. Patents RDF Approximating Querying with RDF Embedding, Chinese Inventive Patent (201810641543.X) RDF Keyword Querying based on Entity Communities, Chinese Inventive Patent (201410389984.7) Awards Nov. 2018. Best Paper Award, ICBK 2018 Nov. 2018. Best Student Paper Candidate, ISWC 2018 Jul. 2018. Excellent Graduate, Xi'an China Jun. 2015, 15/121, Excellent Student of Xi’an Jiaotong University, Xian, China Dec. 2013, 1/135, Guorui Scholarship, Xian, China Sep. 2012, 3/435, Excellent Graduate of Sichuan University, Chengdu, China Sep. 2011, 5/435, Excellent Student of Sichuan University, Chengdu, China Sep. 2010, 6/435, Excellent Student of Sichuan University, Chengdu, China 2009~2012. First Class Scholarship, Sichuan University, Chengdu, China Academic Services ICBK 2017 Workshop chair. JIST 2019 Publicity Chair. PC member: IJCAI 2020, ISWC 2020, ECAI 2020, APWeb-WAIM 2020, ICONIP 2020, CCKS 2020, ICKG 2020, ADMA 2018 2019, JIST 2019 2020. Invited talks: 2019 CCKS; 2018 Australia-China Innovation Forum on Advanced Technology; The 1st Chinese Artificial Intelligence Competition Training Camp Journal Reviewer: TKDE, TNNLS, Semantic Web Journal, Information Fusion, Neurocomputing, TALLIP, 《中国科学:信息科学》, 《计算机研究与发展》. Joining Our Lab (实验室招生) I particularly enjoy healthy collaborations with my students. So, I consider supervision very seriously. For highly motivated students, please email me with your CV. Ongoing: Xinyu Ma, Kefei Chen, Yu Yang (Master students since 2020) Xu Qin (Master student since 2019) Chaoyu Bai, Qiushuo Zheng (Master students since 2019, Co-supervise with Prof. Guilin Qi) Weitao Wang (Masters student since 2019, Co-supervise with Prof. Yang Chen) Resource (ppt) Data Structure (Autumn 2020, AI class) Multi-modal Knowledge Graph invited report CCKS 2019 invited report 遇见AI"
教育背景
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工作经历
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荣誉奖项
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$\bf {B^{3}}$:基于随机过程建模的文本-视频检索中通过布朗桥连接时间间隙
AI-T2I: 聚合与隔离跨注意力机制用于文本到图像合成的扩散模型
基于熵引导的自适应奖励最大化提升半监督学习
HDG-CLIP:面向开放词汇多标签图像分类的层次化双粒度视觉-语义对齐
通过信息瓶颈建模实现可信的动态面部表情识别
基于Mamba状态空间模型的分子基态构象预测
没有万能的神经元:面向任务的人工神经网络神经元
IAMAgent: 旨在构建一个用于图像修复的交互式和自适应的多智能体系统
计算病理学中具有差异化序列对比学习的扫描不变Mamba
元学习中的尾任务风险最小化:从理论进展到实践策略
面向小样本学习的混合粒度分布估计:从类别和实例进行统计转移
通过模仿学习结合因果世界建模进行长期情感支持建模
解耦兴趣网络用于OOD CTR预测
多RIS辅助UWOC系统的性能分析:全接收方案和选择接收方案
Pattern Recognition
IF7.6
AttriPrompt:面向视觉-语言模型的类属性感知提示微调
<monospace>Momentor++</monospace>:通过细粒度长视频推理推进视频大型语言模型
MT-RoadNet: 一种具有局部-全局联合增强的道路表面和中心线提取的异构网络

