科研团队
沈思淇
长聘副教授, 博士生导师
siqishen@xmu.edu.cn

现为厦门大学信息学院计算机系长聘副教授,博士生导师,人工智能研究院双聘导师。2007年、2009年于国防科学技术大学计算机学院计算机科学与技术学科(教育部评估A+)获得学士和硕士学位。2015年博士毕业于荷兰代尔夫特理工大学,2015年至2020年担任国防科学技术大学计算机学院(教育部评估A+)助理研究员,原天河超级计算机团队成员,参与多项国家重大科研任务研发。在NeurIPS, CVPR, AAAI, MM, INFOCOM, CIKM, WWW, TOMM, ToN, TKDD, Computer Networks, ICASSP, NOSSDAV, CCGrid, EuroPar, NetGames, MMVE等国际知名会议、期刊上公开发表了多篇学术论文,担任NeurIPS 24 Area Chair及多个期刊、会议组委会委员及审稿人。目前主要从事多智能体感知与计算(多智能体强化学习,AI Agents, 人体动作与场景捕捉及生成,视觉定位,具身智能等)相关领域的研究。



新闻

  • [NeurIPS 24] 受邀成为Area Chair (领域主席)

  • [NeurIPS 22] ResQ 被选为亮点论文,为信息学院首篇

  • [AAAI 23] FedGS 被选为Oral

  • [NeurIPS 23] RiskQ及E2PNet两个工作录用

  • [NeurIPS 23 Melting Pot] 挑战赛亚军

  • [跨越险阻挑战赛] 第四名

  • [AAAI 24] CoherenceFuse被选为Oral

  • [CVPR 24] RELI11D/LEIR被录用(得分5,5,4,4)

 


教育经历

  • 2007年 国防科学技术大学计算机科学与技术(985,教育部评估A+),学士  

  • 2009年 国防科学技术大学计算机科学与技术(教育部评估A+)

  • 2015年 国防科学技术大学计算机科学与技术(教育部评估A+)  

  • 2015年 荷兰代尔夫特理工大学 (2023年QS世界大学排名47) 


工作经历

  • 2015年-2020年 国防科学技术大学计算机学院并行与分布处理国家重点实验室

  • 2020年至今,厦门大学


部分主持/主要负责的科研项目

  • 多智能体协同

  • 国家体育总局奥运夺冠科技项目1项:xxx人体动作捕捉技术研究 

  • 国家自然科学基金青年基金:xxx网络虚拟xx关键技术研究

  • 国家重点实验室基金4项:基于强化学习的xx研究,高效强化学习技术研究,推理框架优化技术,人员识别技术

  • 厦大校长基金2项:多智能体强化学习等




部分参与的科研项目

  • 天河超级计算机 (曾连续5次世界上最快计算机)

  • 银河超级计算机

  • 国家973项目2项

  • 国家自然科学基金重点研发项目2项

  • 国家自然科学基金面上项目4项


教学

算法设计与分析 (2022春,2023春,2024春), 操作系统(2021春)



学术服务

NeurIPS 2024 Area Chair

NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, IJCAI, TSC, TOMM, TON, MMVE, NetGames等会议、期刊PC或审稿人。

CCF 高级会员

IEEE 高级会员

CCF AI多智能体系统学组执行委员

中国图象图形学会三维视觉专委会委员

China3DV 2021 宣传主席

China3DV 2023 宣传主席

ChinaSLAM 2023 宣传主席

ChinaSLAM 2024 Poster主席

APPT 2017出版主席




学生培养

指导毕业的硕士生均在一线IT企业/国企(阿里、百度等)工作或继续攻读博士学位。


2024年指导的本科毕设去向:2位保研厦大,1位保研清华,1位直博北大,1位考研北大,1位直博南大,1位直博中大,1位中国电信。


2024年硕士生实习情况:阿里,快手,科大讯飞


推免生及博士生

本实验室硕士生及博士生的培养方向为科技公司的算法岗、大学及研究院的研究岗。


招收夏令营及九推的推免研究生及博士生,也欢迎对科研感兴趣的本科生来本实验室实习,请对本人研究领域有兴趣的同学通过电子邮件(siqishen@xmu.edu.cn)联系我。希望你是一位较为自律,有较强内驱力,有ICPC/CCPC/蓝桥杯获奖的同学优先。


欢迎志向远大、思想上进、意志坚强,不怕吃苦、身体健康、品行端正、学业优秀的同学加入团队一起攀登科技高峰!

近期实验室要招收2025年入学的博士生,感兴趣的同学请和我写信,并请填写以下链接。

https://jsj.top/f/mz5C8H







研究方向 Research
发表的数据集 Datasets 部分论文列表 Selected Publications
2024
KeZheng Xiong, Haoen Xiang, Qingshan Xu, Chenglu Wen, Siqi Shen, Jonathan Li, Cheng Wang
Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
NeurIPS 2024, CCF A
todo
Haoyuan Qin, Chennan Ma, Mian Deng, Zhengzhu Liu, Songzhu Mei, Xinwang Liu, Cheng Wang, Siqi Shen
The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization
NeurIPS 2024, CCF A
todo
Yudi Dai, Zhiyong Wang, Xiping Lin, Chenglu Wen, Lan Xu, Siqi Shen, Yuexin Ma, Cheng Wang
HiSC4D: Human-centered interaction and 4D Scene Capture in Large-scale Space Using Wearable IMUs and LiDAR
PAMI, CCF A, 2024
to appear
Yitai Lin, Zhijie Wei, Wanfa Zhang, Xiping Lin, Yudi Dai, Chenglu Wen, Siqi Shen, Lan Xu, Cheng Wang
HmPEAR: A Dataset for Human Pose Estimation and Action Recognition
MM 2024, CCF A
...
Shaoyang Chen, Bochun Yang, Yan Xia, Ming Cheng, Siqi Shen, Cheng Wang*
Bridging LiDAR Gaps: A Multi-LiDARs Domain Adaptation Dataset for 3D Semantic Segmentation
IJCAI 2024, CCF A
xx
Weiquan Liu, Minghao Liu, Shijun Zheng, Siqi Shen, Xuesheng Bian, Yu Zang, Ping Zhong, Cheng Wang
Interpreting Hidden Semantics in the Intermediate Layers of 3D Point Cloud Classification Neural Network
TMM 2024, CCF B
tmp
Ming Yan, Yan Zhang, Shuqiang Cai, Shuqi Fan, Xincheng Lin, Yudi Dai, Siqi Shen*, Chenglu Wen, Lan Xu, Yuexin Ma, Cheng Wang
RELI11D: A Comprehensive Multimodal Human Motion Dataset and Method
CVPR 2024, CCF A
https://openaccess.thecvf.com/content/CVPR2024/html/Yan_RELI11D_A_Comprehensive_Multimodal_Human_Motion_Dataset_and_Method_CVPR_2024_paper.html
Jinyi Zhang, Qihong Mao, Siqi Shen, Guosheng Hu, Cheng Wang
Neighborhood-enhanced 3D Human Pose Estimation with Monocular LiDAR in Long-range Outdoor Scenes
AAAI 2024, Oral, CCF A
todo
Kezheng Xiong, Maoji Zheng, Qingshan Xu, Chenglu Wen*, Siqi Shen*, Cheng Wang
SPEAL: Skeletal-Prior Embedded Attention Learning for Cross-Source Point Cloud Registration
AAAI 2024, CCF A
todo
2023
Xiuhong Lin, Changjie Qiu, Zhipeng Cai, Siqi Shen*, Yu Zang, Weiquan Liu, Xuesheng Bian, Matthias Müller, Cheng Wang
E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning
NeurIPS 2023, CCF A
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Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu*, Songzhu Mei, Xinwang Liu, Cheng Wang
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
NeurIPS 2023, CCF A
{}
Liwen Peng, Songlei Jian, Dongsheng Li, Siqi Shen
MRML: Multimodal Rumor Detection by Deep Metric Learning
ICASSP 2023, CCF B
xx
Bo Pang, Yongquan Fu, Siyuan Ren, Siqi Shen, Ye Wang, Qing Liao, Yan Jia
A Multi-modal Approach for Context-aware Network Traffic Classification
ICASSP 2023, CCF B
xx
Ming Yan, Xin Wang, Yudi Dai, Siqi Shen*, Chenglu Wen, Lan Xu, Yuexin Ma, Cheng Wang
CIMI4D: A Large Multimodal Climbing Motion Dataset under Human-scene Interactions
CVPR 2023, CCF A
xx
Yudi Dai, YiTai Lin, XiPing Lin, Chenglu Wen*, Lan Xu, Hongwei Yi, Siqi Shen, Yuexin Ma, Cheng Wang
SLOPER4D: A Scene-Aware Dataset For Global 4D Human Pose Estimation In Urban Environments
CVPR 2023, CCF A
xx
Wen Li, Shangshu Yu, Cheng Wang, Guosheng Hu, Siqi Shen, Chenglu Wen
SGLoc: Scene Geometry Encoding for Outdoor LiDAR Localization
CVPR 2023, CCF A
xx
Yongquan Fu, Lun An, Siqi Shen*, Kai Chen, Pere Barlet-Ros
A One-pass Clustering based Sketch Method for Network Monitoring
IEEE/ACM Transactions on Networking (ToN), CCF A, 2023
xx
Zheng Wang, Xiaoliang Fan*, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability
AAAI 2023, CCF A,Oral
abc
2022
Siqi Shen, Mengwei Qiu, Jun Liu, Weiquan Liu, Yongquan Fu*, Xinwang Liu, Cheng Wang
ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization
NeurIPS 2022, Spotlight, CCF A, top 5%
@inproceedings{ResQ, author = {Siqi Shen and Mengwei Qiu and Jun Liu and Weiquan Liu and Yongquan Fu and Xinwang Liu and Cheng Wang}, title = {ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization}, booktitle = {{NeurIPS}}, year = {2022} }
Yudi Dai, YiTai Lin, Chenglu Wen, Siqi Shen, Lan Xu, Jingyi Yu, Yuexin Ma, Cheng Wang
HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR
CVPR 2022, CCF A
N/A
Jialian Li Jingyi Zhang, Zhiyong Wang, Siqi Shen, Chenglu Wen, Yuexin Ma, Lan Xu, Jingyi Yu, Cheng Wang
LiDARCap: Long-range Marker-less 3D Human Motion Capture with LiDAR Point Clouds
CVPR 2022, CCF A
N/A
Siqi Shen, Jun Liu, Mengwei Qiu, Weiquan Liu, Cheng Wang*, Yongquan Fu*, Qinglin Wang, Peng Qiao
QRelation: An Agent Relation-Based Approach for Multi-Agent Reinforcement Learning Value Function Factorization
ICASSP 2022, CCF B
@inproceedings{QRelation, author = {Siqi Shen and Jun Liu and Mengwei Qiu and Weiquan Liu and Cheng Wang and Yongquan Fu and Qinglin Wang and Peng Qiao}, title = {QRelation: An Agent Relation-Based Approach for Multi-Agent Reinforcement Learning Value Function Factorization}, booktitle = {{IEEE} International Conference on Acoustics, Speech and Signal Processing, {ICASSP} 2021, Toronto, ON, Canada, June 6-11, 2021}, pages = {3510--3514}, publisher = {{IEEE}}, year = {2021}, url = {https://doi.org/10.1109/ICASSP39728.2021.9413716}, doi = {10.1109/ICASSP39728.2021.9413716}, timestamp = {Thu, 07 Oct 2021 14:54:19 +0200}, biburl = {https://dblp.org/rec/conf/icassp/ShenFSPQDW21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2021
Yongquan Fu, Lun An, Kai Chen, Pere Barlet-Ros, Siqi Shen*
Jellyfish: Locality-sensitive Subflow Sketching
INFOCOM, 2021, CCF A
@article{Fu2021JellyfishLS, title={Jellyfish: Locality-Sensitive Subflow Sketching}, author={Yongquan Fu and Lun An and Siqi Shen and Kai Chen and Pere Barlet-Ros}, journal={IEEE INFOCOM 2021 - IEEE Conference on Computer Communications}, year={2021}, pages={1-10} }
Siqi Shen, Yongquan Fu*, Huayou Su, Hengyue Pan, Peng Qiao, Yong Dou, Cheng Wang*
GRAPHCOMM: A GRAPH NEURAL NETWORK BASED METHOD FOR MULTI-AGENT REINFORCEMENT LEARNING
ICASSP 2021, CCF B
@inproceedings{GraphComm, author = {Siqi Shen and Yongquan Fu and Huayou Su and Hengyue Pan and Peng Qiao and Yong Dou and Cheng Wang}, title = {Graphcomm: {A} Graph Neural Network Based Method for Multi-Agent Reinforcement Learning}, booktitle = {{ICASSP}}, pages = {3510--3514}, year = {2021}, bibsource = {dblp computer science bibliography, https://dblp.org} }
2020
Adele Lu Jia, Yuanxing Rao, Hongru Li, Ran Tian, Siqi Shen*
Revealing Donation Dynamics in Social Live Video Streaming
WWW 2020, CCF A
@inbook{10.1145/3366424.3382682, author = {Lu Jia, Adele and Rao, Yuanxing and Li, Hongru and Tian, Ran and Shen, Siqi}, title = {Revealing Donation Dynamics in Social Live Video Streaming}, year = {2020}, isbn = {9781450370240}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3366424.3382682}, abstract = {Social live video streaming has become a global economic and social phenomenon with the rise of platforms like Facebook-Live, Youtube-Live, and Twitch. The phenomenon of user donation in these communities is rapidly emerging, towards which however we have very limited understandings. In this preliminary work, we reveal the dynamics of user donations based on a publicly available (anonymized) dataset with detailed information on over 2 million users and worth in total over 200 million US dollars. Among other results, we find that (i) both the donations received and the donations made are highly skewed, (ii) user donation is strongly correlated with the atmosphere (the volume and the sentiment of real-time user chats) and in the long run, the loss of broadcasters, and (iii) donors are loyal and very generous to their favorite broadcasters while in the mean time they also support others moderately. Our findings represent a first step towards understanding user donations which will shed lights on the donor retention problem and the design of social live video streaming services. }, booktitle = {Companion Proceedings of the Web Conference 2020}, pages = {30–31}, numpages = {2} }
Siqi Shen*, Yongquan Fu, Adele Lu Jia, Huayou Su, Qinglin Wang, Chengsong Wang, Yong Dou
Learning Network Representation Through Reinforcement Learning
ICASSP 2020, CCF B
@INPROCEEDINGS{9053879, author={Shen, Siqi and Fu, Yongquan and Jia, Adele Lu and Su, Huayou and Wang, Qinglin and Wang, Chengsong and Dou, Yong}, booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, title={Learning Network Representation Through Reinforcement Learning}, year={2020}, volume={}, number={}, pages={3537-3541}, doi={10.1109/ICASSP40776.2020.9053879}}
Yongquan Fu, Dongsheng Li, Siqi Shen*, Yiming Zhang, Kai Chen
Clustering-preserving Network Flow Sketching
INFOCOM 2020, CCF A
@INPROCEEDINGS{9155388, author={Fu, Yongquan and Li, Dongsheng and Shen, Siqi and Zhang, Yiming and Chen, Kai}, booktitle={IEEE INFOCOM 2020 - IEEE Conference on Computer Communications}, title={Clustering-preserving Network Flow Sketching}, year={2020}, volume={}, number={}, pages={1309-1318}, doi={10.1109/INFOCOM41043.2020.9155388}}
Xiaoxue Shen, Adele Lu Jia, Siqi Shen*, Yong Dou, Helping the ineloquent farmers: Finding experts for questions with limited text in agricultural Q&A Communities
Helping the ineloquent farmers: Finding experts for questions with limited text in agricultural Q&A Communities
IEEE ACCESS 2020, JCR 2
@ARTICLE{9050735, author={Shen, Xiaoxue and Jia, Adele Lu and Shen, Siqi and Dou, Yong}, journal={IEEE Access}, title={Helping the Ineloquent Farmers: Finding Experts for Questions With Limited Text in Agricultural Q amp;A Communities}, year={2020}, volume={8}, number={}, pages={62238-62247}, doi={10.1109/ACCESS.2020.2984342}}
2019
Liwen Peng, Siqi Shen*, Jun Xu, Yongquan Fu, Dongsheng Li, Adele lu Jia. Diting: An Author Disambiguation method based on Network Representation Learning
Diting: An Author Disambiguation method based on Network Representation Learning
IEEE ACCESS 2019, JCR 2
@ARTICLE{8844683, author={Peng, Liwen and Shen, Siqi and Xu, Jun and Fu, Yongquan and Li, Dongsheng and Jia, Adele Lu}, journal={IEEE Access}, title={Diting: An Author Disambiguation Method Based on Network Representation Learning}, year={2019}, volume={7}, number={}, pages={135539-135555}, doi={10.1109/ACCESS.2019.2942477}}
Yongquan Fu, Dongsheng Li, Pere Barlet-Ros, Chun Huang, Zhen Huang, Siqi Shen, Huayou Su
A Skewness-aware Matrix Factorization Approach for Mesh-structured Cloud Services
IEEE/ACM Transactions on Networking 2019, CCF A
@article{10.1109/TNET.2019.2923815, author = {Fu, Yongquan and Li, Dongsheng and Barlet-Ros, Pere and Huang, Chun and Huang, Zhen and Shen, Siqi and Su, Huayou}, title = {A Skewness-Aware Matrix Factorization Approach for Mesh-Structured Cloud Services}, year = {2019}, issue_date = {August 2019}, publisher = {IEEE Press}, volume = {27}, number = {4}, issn = {1063-6692}, url = {https://doi.org/10.1109/TNET.2019.2923815}, doi = {10.1109/TNET.2019.2923815}, abstract = {Online cloud services need to fulfill clients’ requests scalably and fast. State-of-the-art cloud services are increasingly deployed as a distributed service mesh. Service to service communication is frequent in the mesh. Unfortunately, problematic events may occur between any pair of nodes in the mesh, therefore, it is vital to maximize the network visibility. A state-of-the-art approach is to model pairwise RTTs based on a latent factor model represented as a low-rank matrix factorization. A latent factor corresponds to a rank-1 component in the factorization model, and is shared by all node pairs. However, different node pairs usually experience a skewed set of hidden factors, which should be fully considered in the model. In this paper, we propose a skewness-aware matrix factorization method named SMF. We decompose the matrix factorization into basic units of rank-one latent factors, and progressively combine rank-one factors for different node pairs. We present a unifying framework to automatically and adaptively select the rank-one factors for each node pair, which not only preserves the low rankness of the matrix model, but also adapts to skewed network latency distributions. Over real-world RTT data sets, SMF significantly improves the relative error by a factor of 0.2 $times$ to 10 $times$ , converges fast and stably, and compactly captures fine-grained local and global network latency structures.}, journal = {IEEE/ACM Trans. Netw.}, month = {aug}, pages = {1598–1611}, numpages = {14} }
Liwen Peng, Siqi Shen*, Dongsheng Li, Jun Xu, Yongquan Fu, Huayou Su
Author Disambiguation through Adversarial Network Representation Learning
IJCNN 2019, CCF C
2018
Jun Xu, Siqi Shen*, Dongsheng Li, Yongquan Fu
A Network-embedding Based Method for Author Disambiguation
CIKM 2018, CCF B
Adele Lu Jia, Siqi Shen*, Dongsheng Li, and Shengling Chen
Predicting the Implicit and the Explicit Video Popularity in a User Generated Content Site with Enhanced Social Features
Computer Networks 2018, CCF B
2017
Dongsheng Li, Wangxing Zhang, Siqi Shen, Yiming Zhang
SES-LSH: Shuffle-Efficient Locality Sensitive Hashing for Distributed Similarity Search
ICWS 2017, CCF B
2016
Adele Lu Jia, Siqi Shen*, Dick Epema, and Alexandru Iosup
When game becomes life: The creators and the spectators of online game replays and live streaming
TOMM 2016, CCF B
2015
Adele Lu Jia, Siqi Shen*, Ruud van de Bovenkamp, Alexandru Iosup, Fernando Kuipers, and Dick Epema
Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games
TKDD 2015, CCF B
Siqi Shen, Shunyun Hu, Alexandru Iosup, and Dick Epema
The Area of Simulation Mechanism and Architecture for Multi-Avatar Virtual Environments
TOMM 2015, CCF B
Marcus Martens, Siqi Shen, Alexandru Iosup, and Fernando Kuipers
Toxicity Detection in Multiplayer Online Games
NetGames 2015, BEST Paper
Siqi Shen, Alexandru Iosup, Assaf Israel, Walfredo Cirne, Danny Raz, and Dick Epema
An Availability-on-Demand Mechanism for Datacenters
CCGrid 2015, CCF C
Siqi Shen, Vincent van Beek, and Alexandru Iosup
Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters
CCGrid 2015, CCF C
2014
Siqi Shen, Niels Brouwers, Alexandru Iosup, and Dick Epema
Characterization of Human Mobility in Networked Virtual Environments
NOSSDAV 2014, CCF B
Yunhua Deng, Siqi Shen, Zhe Huang, Alexandru Iosup, and Rynson Lau
Dynamic Resource Management in Cloud-based Distributed Virtual Environment
ACM Multimedia 2014, CCF A
Siqi Shen and Alexandru Iosup
Modeling Avatar Mobility of Networked Virtual Environments
MMVE 2014
2013
Siqi Shen, Kefeng Deng, Alexandru Iosup, and Dick Epema
Scheduling Jobs in the Cloud Using On-demand and Reserved Instances
EuroPar 2013, CCF B
Siqi Shen, Alexandru Iosup, and Dick Epema
Massivizing Multi-Player Online Games on Clouds
CCGrid 2013, CCF C
2011
Siqi Shen, Otto Visser, and Alexandru Iosup
RTSenv: An Experimental Environment for Real-Time Strategy Games
NetGames 2011
Siqi Shen and Alexandru Iosup
The XFire Online Meta-Gaming Network: Observation and High-Level Analysis
MMVE, 2011