● Graph Mining and Machine Learning on Graphs ● Big Data and Social Network Analytics ● Data Mining ● Spatial Database
Education
National Taiwan University (NTU), Taipei, Taiwan
● Ph.D. in Electrical Engineering, Jun. 2013
National Chiao Tung University (NCTU), Hsinchu, Taiwan
● M.S. in Computer Science and Information Engineering
● B.S. in Computer Science and Information Engineering
● 有庠科技論文獎, 2024
● 傑出人才基金會 年輕學者創新獎, 2022
● 財團法人潘文淵文教基金會研究考察獎, 2021
● 國立清華大學電資院傑出教學獎, 2020
● 中國電機工程學會 優秀青年電機工程師獎, 2019
● 國立清華大學新進人員研究獎, 2019
● 國立清華大學電資院新進人員研究獎, 2019
● K. T. Li Distinguished Young Scholar Award (李國鼎青年研究獎), ACM Taipei/Taiwan Chapter, Taiwan, 2018
● MOST Young Scholar Fellowship (科技部哥倫布計畫), Ministry of Science and Technology, 2018
● 國立清華大學電資院國外短期研究獎助 - University of California, Santa Barbara, 2017
● Postdoc Academic Publication Award (科技部博士後研究人員學術著作獎), Ministry of Science and Technology, 2016
● PAKDD Best Runner-Up Paper Award, Ho Chi Minh City, Vietnam, 2015
● Postdoctoral Research Abroad Program Award (博士後千里馬), Ministry of Science and Technology, 2015
● Graduate Students Study Abroad Program Award (博士生千里馬), National Science Council, Taiwan, 2012
Social network mental disorders (e.g., cyber-relationship addiction, net compulsion, information overload) have been noticed recently due to the emergence of online social networks. However, there is currently no system to detect such disorders using only the social network data. Therefore, we propose the first machine learning framework to identify potential patients using only the online social network data. We achieve 90% of accuracy, while the baseline which employs only the online duration achieves only 35%. Moreover, we also study and formulate the first therapy group formation problem to help these patients form therapy groups efficiently for receiving proper attention in time. We propose an approximation algorithm for the therapy group formation problem. These works appears in CIKM, WWW, IEEE Transactions on Knowledge and Data Enginerring (TKDE).
In these works, we propose and study the graph mining and ML approaches about how to find groups in large social and spatial databases for different scenarios. The application scenarios span a wide spectrum, including 1) impromptu social activities, 2) selection of attendees along with the most suitable activity location, 3) forming quick response teams for disasters, and 4) selection of attendees to maximize friend-making likelihood. These works have been published in SIGKDD, VLDB, AAAI, IEEE TKDE, ACM TKDD, EDBT and PAKDD. They also received MOST Young Scholar Fellowship, MOST, Taiwan, and PAKDD Best Runner-Up Paper Award.
These works include graph-based recommendation systems, federated learning with blockchain, graph adversariay attacks and countermeasures, network compression, neural network watermarking.
In addition to group managements, we also propose the first graph generator that is able to preserve graph patterns and other important graph properties such as clustering coefficient and degree distribution. This generator is able to generate a billion-node graph within several minutes. This generator is published as free download. In addition, we also consider the problem of sampling multiple overlapped social networks with a statistical quality guarantee. The graph generator has appeared in ICDM, CIKM, ECML PKDD, TKDE, TBD.
[31] B.-Y. Hsu, C.-Y. Shen, H. Yuan, W.-C. Lee, and D.-N. Yang. ``Social-Aware Group Display Configuration in VR Conference,'' Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024. (Research Track Full Paper. Acceptance Rate = 2342/9862 = 23.75%)
[30] C.-C. Chang, D.-R. Tzeng, C.-H. Lu, M.-Y. Chang, and C.-Y. Shen. ``Improving Graph-based Recommendation with Unraveled Graph Learning,'' European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2024 (Journal Track)
[29] T.-Y. Chien and C.-Y. Shen, ``Customized and Robust Deep Neural Network Watermarking,'' ACM International Conference on Web Search and Data Mining (WSDM), 2024. (Research Track Full Paper, Acceptance Rate = 18%)
[28] B.-W. Yang, M.-Y. Chang, C.-H. Lu, and C.-Y. Shen. ``Two Heads are Better than One: Teaching MLPs with Multiple Graph Neural Networks via Knowledge Distillation and Contrastive Learning,'' International Conference on Database Systems for Advanced Applications (DASFAA), 2024. (Research Track Short Paper)
[27] C.-Y. Shen, S.-H. Ko, D.-N. Yang, G.-S. Lee, and W.-C. Lee.``Density Personalized Group Query,'' International Conference on Very Large Data Bases (VLDB), 2023. (Research Track Full Paper)
[26] H.-W. Yang, M.-Y. Chang, and C.-Y. Shen. ``Enhancing Link Prediction with Self-discriminating Augmentation for Structure-aware Contrastive Learning,'' European Conference on Artificial Intelligence (ECAI), 2023. (Research Track Full Paper, Acceptance Rate = 24%)
[25] C. Fotsing, G.-S. Lee, Y.-W. Teng, C.-Y. Shen, Y.-S. Chen, and D.-N. Yang. ``On Spatial Crowdsourcing Query under Pandemics,'' IEEE International Conference on Mobile Data Management (MDM), 2023. (Research Track Full Paper, Acceptance Rate = 29%)
[24] J.-H. Yang, C.-Y. Shen, M.-Y. Chang, Y.-C. Ho, and C.-H. Lu. ``Similarity-aware Sampling for Machine Learning-based Goal-oriented Subgraph Extraction,'' IEEE International Conference on Communications (ICC), 2023.
[23] C.-H. Yang and C.-Y. Shen. ``Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation,'' ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (Research Track Full Paper, Acceptance Rate = 254/1695 = 15%)
[22] C. Fotsing, Y.-W Teng, G.-S. Lee, C.-Y. Shen, Y.-S Chen, and D.-N. Yang. ``On Epidemic-aware Socio Spatial POI Recommendation,'' IEEE International Conference on Mobile Data Management (MDM), 2022. (Research Track Full Paper, Acceptance Rate = 26%)
[21] Yu-Lin Chang, Hao-Ping (Hank) Lee, Yung-Ju Chang, Chih-Ya Shen, ``Inviting Participants' Peers in a Mobile Assessment Study: An Empirical Investigation,'' ACM International Conference on Mobile Human-Computer Interaction (MobileHCI), 2021 (Research Track Full Paper)
[20] B.-Y. Hsu, C.-Y. Shen, and M.-Y. Chang. ``WMEgo: Willingness Maximization for Ego Network Data Extraction in Online Social Networks,'' ACM International Conference on Information and Knowledge Management (CIKM), 2020. (Research Track Full Paper, Acceptance Rate = 21%, 920 Submissions)
[19] F. Ghaffar, G. Kibirige, C.-Y. Shen, and M.-C. Chen. ``LOST: A Location Estimator Scheme for PM2.5 Pollution Sources in Sparse Sensors Network.'' IEEE Global Communication Conference (Globecom), 2020.
[18] L.-Y. Yeh, W.-H. Hsu, J.-L. Huang, C.-Y. Shen, and L.-C. Wu. ``Integrating Cellphone-based Hardware Wallet with Visional Certificate Verification System,'' IEEE Global Communication Conference (Globecom), 2020.
[17] B.-Y. Hsu, C.-L. Tu, M.-Y. Chang, and C.-Y. Shen. ``CrawlSN: Community-aware Data Acquisition with Maximum Willingness in Online Social Networks, '' The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2020. (Journal Track)
[16] H.-J. Hung, W.-C. Lee, D.-N. Yang, C.-Y. Shen, Z. Lei, and S.-M. Chow, ``Efficient Algorithms towards Network Intervention,'' International World Wide Web Conference (WWW), 2020. (Research Track Full Paper, Acceptance Rate = 19%, 1129 Submissions)
[15] Y.-J. Hsu, Y.-T. Chang, C.-Y. Shen, H.-H. Shuai and W.-L. Tseng, ``On Minimizing Diagonal Block-wise Differences for Neural Network Compression, '' European Conference on Artificial Intelligence (ECAI), 2020. (Research Track Full Paper, Acceptance Rate = 26.8%, 1443 Submissions)
[14] B.-Y. Hsu, C.-Y. Shen, G.-S. Lee, Y.-J. Hsu, C.-H. Yang, C.-W. Lu, M.-Y. Chang, and K.-P. Lin, ``Optimizing k-Collector Routing for Big Data Collection in Road Networks,'' IEEE Global Commuication Conference (Globecom), 2019. (Research Track Full Paper, Acceptance Rate=38%, 2560 Submissions)
[13] B.-Y. Hsu, C.-L. Tu, M. Chang, and C.-Y. Shen, ``On Crawling Community-aware Online Social Network Data,'' ACM HyperText, (HT), 2019 (Research Track Poster)
[12] B.-Y. Hsu and C.-Y. Shen, ``On Extracting Social-Aware Diversity-Optimized Groups in Social Networks,'' IEEE Global Communication Conference (Globecom), 2018. (Research Trak Full Paper, Acceptance Rate=38%, 2562 Submissions)
[11] C.-Y. Shen, C. Fotsing, D.-N. Yang, Y.-S. Chen, and W.-C. Lee, ``On Organizing Online Soirees for Live Multi-Streaming,'' Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2018. (Research Track Full Paper with Oral Presentation, Acceptance Rate=11%)
[10] C.-Y. Shen, L.-H. Huang, D.-N. Yang, H.-H. Shuai, W.-C. Lee, and M.-S. Chen, ``On Finding Socially Teneous Groups for Online Social Networks,'' ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. (Research Track Full Paper with Oral Presentation, Acceptance Rate=64/748=8.6%)
[9] C.-Y. Shen, H.-H. Shuai, K.-F. Hsu, and M.-S. Chen. Chen, ``Task-Optimized Group Search for Social Internet of Things,'' International Conference on Extending Database Technology (EDBT), 2017. (Research Track Full Paper, Acceptance Rate=21.8%)
[8] C.-C. Chen, C.-Y. Shen, and M.-S. Chen, ``Massive Parallelism for Non-linear and Non-stationary Data Analysis with GPGPU,'' IEEE International Conference on Big Data (IEEE BigData), 2016. (Short Paper)
[7] H.-H. Shuai, C.-Y. Shen, D.-N. Yang, Y.-F. Lan, W.-C. Lee, P. S. Yu, and M.-S. Chen, ``Mining Online Social Data for Detecting Social Network Mental Disorders,'' International World Wide Web Conference (WWW), 2016. (Research Track Full Paper, Acceptance Rate=16%)
[6] C.-Y. Shen, H.-H. Shuai, D.-N. Yang, Y.-F. Lan, W.-C. Lee, P. S. Yu, and M.-S. Chen, ``Forming Online Support Groups for Internet and Behavior Related Addictions,'' ACM International Conference on Information and Knowledge Management (CIKM), 2015. (Research Track Full Paper, Acceptance Rate=21%)
[5] H.-H. Shuai, C.-Y. Shen, D.-N. Yang, H.-C. Hsu, C.-K. Chou, J.-H. Lin, and M.-S. Chen, ``Revenue Maximization for Telecommunications Company with Social Viral Marketing,'' IEEE International Conference on Big Data (IEEE BigData) 2015. (Industrial Track Regular Paper)
[4] C.-Y. Shen, D.-N. Yang, W.-C. Lee, and M.-S. Chen, ``Maximizing Friend-Making Likelihood for Social Activity Organization,'' Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015. (Best Runner-Up Paper Award, Acceptance Rate=16%)
[3] H.-H. Shuai, D.-N. Yang, P. S. Yu, C.-Y. Shen, and M.-S. Chen, ``On Pattern Preserving Graph Generation,'' IEEE International Conference on Data Mining (ICDM), 2013. (Research Track Full Paper, Acceptance Rate=11.6%)
[2] D.-N. Yang, C.-Y. Shen, W.-C. Lee, and M.-S. Chen, ``On Socio-Spatial Group Query for Location-Based Social Networks,'' ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2012. (Research Track Full Paper, Acceptance Rate=17.6%)
[1] C.-C. Yen, C.-Y. Shen, and M.-S. Chen, ``A Two-Phase Hybrid Codebook Generation Technique for Vector Quantization,'' IEEE International Conference on Image Processing (ICIP), 2010. (Short Paper)
[26] B.-Y. Hsu, C.-H. Lu, M.-Y. Chang, C.-Y. Tseng, and C.-Y. Shen. ``Budget-Constrained Ego Network Extraction with Maximized Willingness,'' to appear in IEEE Transactions on Knowledge and Data Engineering (TKDE).
[25] L.-Y. Yeh, W.-H. Hsu, and C.-Y. Shen, ``GDPR-Compliant Personal Health Record Sharing Mechanism with Redactable Blockchain and Revocable IPFS,'' to appear in IEEE Transactions on Dependable and Secure Computation (TDSC).
[24] H.-J. Hung, C.-H. Lu, Y.-Y. Huang, M.-Y. Chang, Y.-C. Ho, and C.-Y. Shen. ``Efficient Detection of k-Plex Structures in Large Graphs through Constraint Learning,'' to appear in IEEE Transactions on Computational Social Systems (TCSS).
[23] W.-Y. Lin, Y.-Z. Song, B.-K. Ruan, H.-H. Shuai, C.-Y. Shen, L.-C. Wang, and Y.-H. Li, ``Temporal Difference-Aware Graph Convolutional Reinforcement Learning for Multi-Intersection Traffic Signal Control,'' IEEE Transactions on Intelligent Transportation Systems (TITS), Volume 25, Issue 1, 2024.
[22] B. Lee, J.-Y. Jhang, L.-Y. Yeh, M.-Y. Chang, C.-M. Chen, and C.-Y. Shen, ``Detecting Targets of Graph Adversarial Attacks with Edge and Feature Perturbations,'' IEEE Transactions on Computational Social Systems (TCSS), Volume 11, Issue 3, Pages 3218-3231, 2024.
[21] C.-C. Chang, C.-H. Lu, M.-Y. Chang, C.-E. Shen, Y.-C. Ho, and C.-Y. Shen, ``Learning to Augment Graphs: Machine Learning-based Social Network Intervention with Self-Supervision,'' IEEE Transactions on Computational Social Systems (TCSS), Volume 11, Issue 3, Pages 3286-3298, 2024.
[20] C.-C. Chang, C.-H. Lu, S.-J. Teng, M.-Y. Chang, Y.-C. Ho, and C.-Y. Shen, ``Maximizing (k, L)-core with Edge Augmentation in Multi-Layer Graphs.'' IEEE Transactions on Computational Social Systems (TCSS), Volume 11, Issue 3, Pages 3931-3943, 2024.
[19] K. Fotsing, C.-Y. Shen, L.-H. Huang, Y.-S. Chen, W.-C. Lee, and D.-N. Yang, ``On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization,'' IEEE Transactions on Services Computing (TSC), Volume 16, Issue 4, Pages 2812-2926, 2023.
[18] B.-Y. Hsu, L.-Y. Yeh, M.-Y. Chang, and C.-Y. Shen, ``Willingness Maximization for Ego Network Data Extraction in Multiple Online Social Networks,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 35, Issue 8, Pages 8672-8686, 2023.
[17] B.-Y. Hsu, Y.-L. Chen, Y.-C. Ho, P.-Y. Chang, C.-C. Chang, B.-C. Shia, and C.-Y. Shen, ``Diversity-Optimized Group Extraction in Social Networks,'' to appear in IEEE Transactions on Computational Social Systems (TCSS), 2023.
[16] L.-Y. Yeh, C.-Y. Shen, W.-C. Huang, W.-H. Hsu, and H.-C. Wu, ``GDPR-Aware Revocable P2P File-Sharing System Over Consortium Blockchain,'' IEEE Systems Journal, Volume 16, Issue 4, Pages 5234-5245, 2022.
[15] C.-H. Yang, H.-H. Shuai, C.-Y. Shen, and M.-S. Chen, ``Learning to Solve Task-Optimized Group Search for Social Internet of Things,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 34, Issue 11, Pages 5429-5445, 2022.
[14] C.-Y. Shen, H.-H. Shuai, D.-N. Yang, G.-S. Lee, L.-H. Huang, W.-C. Lee, and M.-S. Chen, ``On Extracting Socially Tenuous Groups for Online Social Networks with k-Triangles,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 34, Issue 7, Pages 3431-3446, 2022.
[13] C.-C. Chang, M.-Y. Chang, J.-Y. Jhang, L.-Y. Yeh, C.-Y. Shen, ``Learning to Extract Expert Teams in Social Networks,'' IEEE Transactions on Computational Social Systems (TCSS), Volume 9, Issue 5, Pages 1552-1562, 2022.
[12] C.-Y. Shen, D.-N. Yang, W.-C. Lee, and M.-S. Chen, ``Activity Organization for Friend-Making Optimization in Online Social Networks,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 24, Issue 1, Pages 122-137, 2022.
[11] B.-Y. Hsu, C.-Y. Shen, and X. Yan, ``Network Intervention for Mental Disorders with Minimum Small Dense Subgroups,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 33, Issue 5, Pages 2121-2136, 2021.
[10] Y.-L. Chen, D.-N. Yang, C.-Y. Shen, W.-C. Lee, and M.-S. Chen, ``On Efficient Processing of Group and Subsequent Queries for Social Activity Planning,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 31, Issue 12, Pages 2364-2378, 2019.
[9] K.-P. Lin, Y.-W. Chang, C.-Y. Shen, and M.-C. Lin, ``Leveraging Online Word-of-Mouth for Personalized App Recommendation,'' IEEE Transactions on Computational Social Systems (TCSS), Volume 5, Issue 4, Pages 1061-1070, 2018.
[8] M. Wu, C.-Y. Shen, E. Wang, and A. Chen, ``A Deep Architecture for Depression Detection using Posting, Behavior, and Living Environment Data,'' Journal of Intelligent Information Systems (JIIS), Volume 54, Pages 225-244, 2020.
[7] B.-Y. Hsu, Y.-F. Lan, and C.-Y. Shen, ``On Automatic Formation of Effective Therapy Groups in Social Networks,'' IEEE Transactions on Computational Social Systems (TCSS), Volume 5, Issue 3, Pages 713-726, 2018.
[6] H.-H. Shuai, C.-Y. Shen, D.-N. Yang, Y.-F. Lan, W.-C. Lee, P. S. Yu, and M.-S. Chen, ``A Comprehensive Study on Social Network Mental Disorders Detection via Online Social Media Mining,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 30, Issue 7, Pages 1212-1225, 2018.
[5] H.-H. Shuai, D.-N. Yang, C.-Y. Shen, P. S. Yu and M.-S. Chen, ``QMSampler: Joint Sampling of Multiple Networks with Quality Guarantee,'' IEEE Transactions on Big Data (TBD), Volume 4, Issue 1, Pages 90-104, 2018.
[4] C.-Y. Shen, D.-N. Yang, W.-C. Lee, and M.-S. Chen, ``Spatial-Proximity Optimization for Rapid Task Group Deployment,'' ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 10, Issue 4, July 2016.
[3] C.-Y. Shen, D.-N. Yang, W.-C. Lee, and M.-S. Chen, ``Socio-Spatial Group Queries for Impromptu Activity Planning,'' IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 28, Issue 1, Pages 196-210, 2016.
[2] C.-Y. Shen, D.-N. Yang, M.-S. Chen, ``Collaborative and Distributed Search System with Mobile Devices,'' IEEE Transactions on Mobile Computing (TMC), Volume 11, Issue 10, Pages 1478-1493, 2012
[1] Y.-L. Huang, C.-Y. Shen, S.-P. Shieh, ``S-AKA: A Provable and Secure Authentication Key Agreement Protocol for UMTS Networks,'' IEEE Transactions on Vehicular Technology (TVT), Volume 60, Issue 9, Pages 4509-4519, 2011.
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