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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
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<td style="height: 169px; vertical-align: top;"> <img
style="width: 163px; height: 160px;" alt="yinghui wu"
src="0.jpg" id="circle"> </td>
<td style="white-space: nowrap; height: 169px;
vertical-align: top;"> <font size="5">Yinghui Wu</font><br>
<br>
Theodore L. and Dana J. Schroeder <br>
Associate Professor<br>
<a
href="https://engineering.case.edu/computer-and-data-sciences">Department
of Computer <br>
& Data Sciences</a><br>
<br>
<a href="https://engineering.case.edu/">Case School of
Engineering</a><br>
<a href="https://case.edu/">Case Western Reserve
University</a><br>
</td>
<td style="white-space: nowrap; height: 169px;
vertical-align: top;"><br>
<br>
Olin 515<br>
2101 Martin Luther King Jr Dr,<br>
Cleveland, OH 44106<br>
<br>
Office: 216.368.8829<br>
Email: yxw1650_at_case_dot_edu<br>
Homepage: <a href="https://yinghwu.github.io/">https://yinghwu.github.io/<br>
</a><br>
</td>
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<hr>
<p align="center"><big><a href="index.html">Home</a> | <a
href="yinghui-teaching.html">Teaching</a> | <a
href="yinghui-research.html">Research | </a><a
href="yinghui-service.html">Services</a> | <a
href="yinghui-students.html">Students</a> | <a
href="yinghui-publication.html">Publications</a> | <a
href="yinghui-talks.html">Talks</a> | <a
href="yinghui-bib.html">Bio</a> </big></p>
<hr><span style="font-weight: bold;">Full publication list</span>
[<a href="https://dblp.uni-trier.de/pid/32/6122-1.html"
moz-do-not-send="true">DBLP</a>] [<a
href="https://scholar.google.com/citations?user=9u7wNjUAAAAJ&hl=en">Google
Scholar</a>]<br>
<br>
<b>Selected</b>: View by [<a href="yinghui-publication-year.html">Year</a>] [<a
href="yinghui-publication.html">Type</a>] <br>
<br>
<span style="font-weight: bold;"><span style="font-weight: bold;"><span
style="font-weight: bold;"><span style="font-weight: bold;">2026</span></span></span></span><br>
<ol>
<li>Training-free Counterfactual Explanation for Temporal Graph
Model Inference<br>
The Fourteenth International Conference on Learning
Representations (<i><b>ICLR</b></i>)<br>
Mingjian Lu, Haolai Che, Yangxin Fan, Qu Liu, Fei Shao,
Tingjian Ge, Xusheng Xiao, Yinghui Wu</li>
<li>Assessing LLMs for Serendipity Discovery in Knowledge
Graphs: A Case for Drug Repurposing<br>
The 40th Annual AAAI Conference (<i><b>AAAI</b></i>)<br>
Mengying Wang, Chenhui Ma, Ao Jiao, Tuo Liang, Pengjun Lu,
Shrinidhi Hegde, Yu Yin, Evren Gurkan-Cavusoglu, Yinghui Wu</li>
<li>SliceGX: Layer-wise GNN Explanation with Model-slicing<br>
The ACM Web Conference (<i><b>WWW</b></i>)<br>
Cibo Yu, Tingting Zhu, Tingyang Chen, Yinghui Wu, Arijit Khan
and Xiangyu Ke<br>
</li>
<li>Graph Query Generation with Constraint-guided Large Language
Agents<br>
<span style="font-style: italic;">Int.Conf.on Data Engineering</span>
(<span style="font-weight: bold; font-style: italic;">ICDE</span>)<br>
Mengying Wang, Nicolaas Jedema, Rahul Pandey, RaviKiran
Krishnan, Jens Lehmann, Yinghui Wu</li>
<li>Interpreting Graph Inference with Skyline Explanations<br>
<span style="font-style: italic;">Int.Conf.on Data Engineering</span>
(<span style="font-weight: bold; font-style: italic;">ICDE</span>)<i><br>
</i>Dazhuo Qiu, Haolai Che, Arijit Khan, Yinghui Wu<i><br>
</i></li>
<li>GNN Explainers 2.0: User-centric and Data-driven Insights [<a
href="https://gnn-explainers.github.io/">Website</a>]<br>
The 19th ACM International Conference on Web Search and Data
Mining (<i><b>WSDM</b></i>)<br>
Arijit Khan, Xiangyu Ke, Yinghui Wu, Francesco Bonchi<br>
</li>
</ol>
<span style="font-weight: bold;"><span style="font-weight: bold;"><span
style="font-weight: bold;"><span style="font-weight: bold;">2025<br>
</span></span></span></span>
<ol>
<li>KROMA: Ontology Matching with Knowledge Retrieval and Large
Language Models<br>
The 24th International Semantic Web Conference (<b>ISWC</b>)<br>
Lam Nguyen, Erika Barcelos, Roger French and Yinghui Wu</li>
<li>GeoOutageKG: A Multimodal Geospatiotemporal Knowledge Graph
for Multiresolution Power Outage Analysis<br>
The 24th International Semantic Web Conference (<b>ISWC</b>)<br>
Ethan Frakes, Yinghui Wu, Roger French and Mengjie Li<br>
</li>
<li>Position: Current Model Licensing Practices are Dragging Us
into a Quagmire of Legal Noncompliance (<i>Oral</i>)<br>
The 42nd International Conference on Machine Learning (<b>ICML</b>)<br>
Moming Duan, Mingzhe Du, Rui Zhao, Mengying Wang, Yinghui Wu,
Nigel Shadbolt, Bingsheng He<br>
</li>
<li>Inference-friendly Graph Compression for Graph Neural
Networks<br>
The 51st International Conference on Very Large Data Bases (<b>VLDB</b>)<br>
Yangxin Fan, Haolai Che, Yinghui Wu</li>
<li>Graph Compression for Interpretable Graph Neural Network
Inference At Scale<br>
The 51st International Conference on Very Large Data Bases (<b>VLDB</b>),
<i>demo</i><br>
Yangxin Fan, Haolai Che, Mingjian Lu, Yinghui Wu</li>
<li>ML-Asset Management: Curation, Discovery, and Utilization<br>
The 51st International Conference on Very Large Data Bases (<b>VLDB</b>),
<i>tutorial</i><br>
Mengying Wang, Moming Duan, Yicong Huang, Chen Li, Bingsheng
He, Yinghui Wu</li>
<li><a href="https://arxiv.org/pdf/2502.11262">Generating
Skyline Datasets for Data Science Models</a> [<a
href="https://github.com/wang-mengying/modis">code</a>]<br>
<span style="font-style: italic;">The 28th International
Conference on Extending Database Technology</span> (<span
style="font-weight: bold; font-style: italic;">EDBT</span>)<br>
Mengying Wang, Hanchao Ma, Yiyang Bian, Yangxin Fan and
Yinghui Wu </li>
<li>Graph Data Management and Graph Machine Learning: Synergies
and Opportunities (<i><b>SIGMOD record</b></i>)<br>
Arijit Khan, Xiangyu Ke, Yinghui Wu<br>
</li>
<font size="-1"> </font>
<li><font size="-1">Materials Data Science Ontology (MDS-Onto):
Unifying domain knowledge in materials and applied data
science<br>
Rajamohan, Balashanmuga Priyan, et al. <b><i>Scientific
Data </i></b></font><br>
<span style="color: rgb(34, 34, 34); font-family: Arial,
Helvetica, sans-serif; font-size: 14.6667px; font-style:
normal; font-variant-ligatures: normal; font-variant-caps:
normal; font-weight: 400; letter-spacing: normal; orphans:
2; text-align: start; text-indent: 0px; text-transform:
none; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; white-space: normal;
background-color: rgb(255, 255, 255);
text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; display: inline
!important; float: none;">
<meta charset="utf-8">
</span></li>
</ol>
<span style="font-weight: bold;"><span style="font-weight: bold;"><span
style="font-weight: bold;"><span style="font-weight: bold;">2024</span></span></span></span><br>
<ol>
<li>Integrating Multimodal Geospatiotemporal Data for Societal,
Economic, and Environmental (SEE) Analysis of Large
Agricultural Systems<br>
IEEE International Conference on Big Data (<b>BigData</b>)<br>
Olatunde D Akanbi, Jiaqi Li, Vibha Mandayam, Arafath Nihar,
Yinghui Wu, Laura S Bruckman, Jeffrey M Yarus, Erika I
Barcelos, Roger French <span style="color: rgb(253, 8, 45);">(</span><span
style="color: rgb(253, 8, 45); font-style: italic;
font-weight: bold;">Best Poster Paper Award</span>)</li>
<li>Forecasting Nutrient Flows using Terrain Elevation-aware
Spatial-Temporal Graph Neural Networks<br>
IEEE International Conference on Big Data (<b>BigData</b>)<br>
Jiaqi Li, Yinghui Wu, Alexandar Harding Bradley, Olatunde
Akanbi, Erika I Barcelos, Laura S Bruckman, Roger H French<br>
</li>
<li>Parallel-friendly Spatio-Temporal Graph Learning for
Photovoltaic Degradation Analysis at Scale<br>
The 33rd ACM International Conference on Information and
Knowledge Management (<i><b>CIKM</b></i>)<br>
Yangxin Fan, Raymond Wieser, Laura Bruckman, Roger French and
Yinghui Wu<br>
</li>
<li> <a href="https://dl.acm.org/doi/10.14778/3685800.3685899">ModsNet:
Performance-aware Top-k Model Search using Exemplar Datasets</a>
[<a
href="https://wangmengying.me/assets/posters/modsnet_demo.pdf">poster</a>]
[<a
href="https://wangmengying.me/assets/videos/modsnet_demo.mp4">video</a>]<br>
<span style="font-style: italic;">The 50th International
Conference on Very Large Data Bases</span> (<span
style="font-weight: bold; font-style: italic;">VLDB</span>)<i>,
demo track, 2024</i><br>
Mengying Wang, Hanchao Ma, Sheng Guan, Yiyang Bian, Haolai
Che, Abhishek Daundkar, Alp Sehirlioglu, Yinghui Wu </li>
<li>User-friendly, Interactive, and Configurable Explanations
for Graph Neural Networks with Graph Views<br>
<span style="font-style: italic;">ACM SIGMOD Conference on
Management of Data</span> (<span style="font-weight: bold;
font-style: italic;">SIGMOD</span>)<i>, demo</i><br>
Tingyang Ghen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu
Ke, Yunjun Gao</li>
<li>View-based Explanations for Graph Neural Networks<br>
<span style="font-style: italic;">ACM SIGMOD Conference on
Management of Data</span> (<span style="font-weight: bold;
font-style: italic;">SIGMOD</span>)<br>
Tingyang Ghen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu
Ke, Yunjun Gao</li>
<li> <a href="https://ieeexplore.ieee.org/document/10597909">Generating
Robust Counterfactual Witnesses for Graph Neural Networks</a>
[<a href="https://wangmengying.me/assets/posters/robogexp.pdf">poster</a>]
[<a href="https://wangmengying.me/assets/slides/robogexp.pdf">slides</a>]
[<a href="https://github.com/DazhuoQ/RoboGExp">code</a>]<br>
<span style="font-style: italic;">Int.Conf.on Data Engineering</span>
(<span style="font-weight: bold; font-style: italic;">ICDE</span>)<i>,
2024</i><br>
Dazhuo Qiu, Mengying Wang, Arijit Khan, Yinghui Wu </li>
<li> <a href="https://ieeexplore.ieee.org/document/10597884">GraphLingo:
Domain Knowledge Exploration by Synchronizing Knowledge
Graphs and Large Language Models</a><br>
[<a
href="https://wangmengying.me/assets/posters/graphlingo.pdf">poster</a>]
[<a
href="https://wangmengying.me/assets/videos/graphlingo.mp4">video</a>]
[<a href="https://github.com/Escanord/GraphLingo">code</a>]<br>
<span style="font-style: italic;">Int.Conf.on Data Engineering</span>
(<span style="font-weight: bold; font-style: italic;">ICDE</span>),
<i>demo track, 2024</i><br>
Duy Le, Kris Zhao, Mengying Wang, Yinghui Wu </li>
<li>View-based Explanations for Graph Neural Networks (extended
abstract)<br>
Tingyang Ghen, Dazhuo Qiu, Yinghui Wu, Arijit Khan, Xiangyu
Ke, Yunjun Gao<br>
<span style="font-style: italic;">The 3rd Workshop on Search,
Exploration, and Analysis in Heterogeneous Datastores: Graph
Edition</span> (<i><b>SEA Graph</b></i>) (<i>invited</i>), <i>Co-located
w. ICDE 2024</i><br>
</li>
</ol>
<span style="font-weight: bold;"><span style="font-weight: bold;"><span
style="font-weight: bold;"><span style="font-weight: bold;"><br>
2023<br>
</span> </span> </span></span>
<ol>
<li>Accelerating Time to Science using CRADLE: A Framework for
Materials Data Science<br>
The 30th IEEE Int. Conf. on High Performance Computing, Data,
and Analytics (<i><b>HiPC</b></i>) <span style="color:
rgb(253, 8, 45);">(</span><span style="color: rgb(253, 8,
45); font-style: italic; font-weight: bold;">Best Paper
Nominee</span>)<br>
Arafath Nihar, Thomas Ciardi, Rounak Chawla, Olatunde Akanbi,
Yinghui Wu, Vipin Chaudhary, Roger French</li>
<li> <a href="https://dl.acm.org/doi/10.1145/3583780.3615051">Selecting
Top-K Data Science Models by Example Dataset</a> [<a
href="https://wangmengying.me/assets/videos/modsnet.mp4">video</a>]
[<a href="https://wangmengying.me/assets/slides/modsnet.pdf">slides</a>]
[<a
href="https://github.com/crux-project/crux-recommendModels">code</a>]<br>
<span style="font-style: italic;">The 32nd ACM International
Conference on Information and Knowledge Management</span> (<span
style="font-weight: bold; font-style: italic;">CIKM</span>)),
<i>2023</i><br>
Mengying Wang, Sheng Guan, Hanchao Ma, Yiyang Bian, Haolai
Che, Abhishek Daundkar, Alp Sehirlioglu, Yinghui Wu </li>
<li>Demonstration of Geyser: Provenance Extraction and
Applications over Data Science Scripts<br>
<span style="font-style: italic;">ACM SIGMOD Conference on
Management of Data</span> (<span style="font-weight: bold;
font-style: italic;">SIGMOD</span>)<br>
Fotis Psallidas, Megan Eileen Leszczynski, Mohammad Hossein
Namaki, Avrilia Floratou, Ashvin Agrawal, Konstantinos
Karanasos, Subru Krishnan, Pavle Subotic, Markus Weimer,
Yinghui Wu, Yiwen Zhu</li>
<li>Fair Group Summarization with Graph Patterns<br>
Int.Conf.on Data Engineering (<span style="font-weight: bold;
font-style: italic;">ICDE</span>)<br>
<span style="color: rgb(34, 34, 34); font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial,
sans-serif; font-size: 14px; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255); text-decoration-thickness: initial;
text-decoration-style: initial; text-decoration-color:
initial; display: inline !important; float: none;">Hanchao
Ma, Sheng Guan, Mengying Wang, Qi Song, Yinghui Wu</span></li>
<li>Spatio-Temporal Denoising Graph Autoencoders with Data
Augmentation for Photovoltaic Timeseries Data Imputation<br>
<span style="font-style: italic;">ACM SIGMOD Conference on
Management of Data</span> (<span style="font-weight: bold;
font-style: italic;">SIGMOD</span>)<br>
Yangxin Fan, Xuanji Yu, Raymond Wieser, David Meakin, Avishai
Shaton, Jean-Nicolas Jaubert, Robert Flottemesch, Michael
Howell, Jennifer Braid, Laura Bruckman, Roger French, Yinghui
Wu</li>
<li>GALE: Active Adversarial Learning for Erroneous Node
Detection in Graphs<br>
Int.Conf.on Data Engineering (<span style="font-weight: bold;
font-style: italic;">ICDE</span>)<br>
<span style="color: rgb(34, 34, 34); font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial,
sans-serif; font-size: 14px; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255); text-decoration-thickness: initial;
text-decoration-style: initial; text-decoration-color:
initial; display: inline !important; float: none;">Sheng
Guan, Hanchao Ma, Mengying Wang, Yinghui Wu</span></li>
<li>Inconsistency Detection with Temporal Graph Functional
Dependencies<br>
Int.Conf.on Data Engineering (<span style="font-weight: bold;
font-style: italic;">ICDE</span>)<br>
<span style="color: rgb(34, 34, 34); font-family: "Google
Sans", Roboto, RobotoDraft, Helvetica, Arial,
sans-serif; font-size: 14px; font-style: normal;
font-variant-ligatures: normal; font-variant-caps: normal;
font-weight: 400; letter-spacing: normal; orphans: 2;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 2; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255); text-decoration-thickness: initial;
text-decoration-style: initial; text-decoration-color:
initial; display: inline !important; float: none;">Morteza
Alipour Langouri</span>, Adam Mansfield, Fei Chiang, Yinghui
Wu </li>
<li>Event Analysis in Transmission Systems Using Spatial
Temporal Graph Encoder Decoder (STGED)<br>
<i><b>IEEE Transactions on Power Systems</b></i><br>
Arman Ahmed, Sajan K.Sadanandan, Shikhar Pandey, Sagnik
Basumallik, Anurag Srivastava, Yinghui Wu</li>
<li>Spatio-Temporal Deep Graph Network for Event Detection,
Localization and Classification in Cyber-Physical Electric
Distribution System<br>
<i><b>IEEE Transactions on Industrial Informatics<br>
</b></i>Arman Ahmed, Sagnik Basumallik, Amir Gholami, Sajan
K.Sadanandan, Mohammad Namaki, Anurag Srivastava, Yinghui Wu</li>
<li>Federated Synchrophasor Data Prediction, Aggregation and
Inference Using Deep Learning: A Case of Proactive Control for
Short-term Stability<br>
<i><b>IEEE Transactions on Power Delivery</b></i><br>
Arman Ahmed, Sagnik Basumallik, Anurag Srivastava, Yinghui Wu,
Sutanay Choudhury</li>
</ol>
<span style="font-weight: bold;"><span style="font-weight: bold;"><br>
2022<br>
</span> </span>
<ol>
<li> <a href="https://dl.acm.org/doi/10.1145/3511808.3557194">CRUX:
Crowdsourced Materials Science Resource and Workflow
Exploration</a> [<a
href="https://wangmengying.me/assets/posters/crux.pdf">poster</a>]
[<a href="https://github.com/crux-project/CRUX">code</a>] <br>
<span style="font-style: italic;">The 31st ACM International
Conference on Information and Knowledge Management</span> (<span
style="font-weight: bold; font-style: italic;">CIKM</span>)),
<i>2022</i><br>
Mengying Wang, Hanchao Ma, Abhishek Daundkar, Sheng Guan,
Yiyang Bian, Alp Sehirlioglu, Yinghui Wu<br>
</li>
<li>System-Auditing, Data Analysis and Characteristics of Cyber
Attacks for Big Data Systems<br>
The 31st ACM International Conference on Information and
Knowledge Management (<i><b>CIKM</b></i>)<br>
Liangyi Huang, Sophia R.Hall, Fei Shao, Arafath Nihar, Vipin
Chaudhary, Yinghui Wu, Roger French, Xusheng Xiao<br>
</li>
<li>RoboGNN: Robustifying Node Classification under Link
Perturbation<br>
<i>The 31st International Joint Conference on Artificial
Intelligence</i><i> </i>(<i><b>IJCAI</b></i>)<br>
Sheng Guan, Hanchao Ma, Yinghui Wu<br>
<meta charset="utf-8">
</li>
<li>Subgraph Query Generation with Fairness and Diversity
Constraints<br>
Int. Conf. on Data Engineering (<i><b>ICDE</b></i>)<br>
Hanchao Ma, Sheng Guan, Mengying Wang, Yen-shuo Chang, Yinghui
Wu</li>
<li>Diversified Subgraph Query Generation with Group Fairness<br>
<i>The 15th International Conference on Web Search and Data
Mining</i> (<i><b>WSDM</b></i>)<br>
Hanchao Ma, Sheng Guan, Christopher Toomey, Yinghui Wu</li>
<li>FAIRification, Quality Assessment, and Missingness Pattern
Discovery for Spatiotemporal Photovoltaic Data <br>
The 49th IEEE Photovoltaic Specialists Conference (<i><b>PVSC</b></i>)<br>
William Oltjen, Yangxin Fan, Jiqi Liu, Liangyi Huang, Mingjie
Li, Hubert Seigneur, Xusheng Xiao, Kristopher Davis, Laura
Bruckman, Yinghui Wu, Roger French.</li>
<li>Special Issue on Decision Making in Heterogeneous Network
Data Scenarios and Applications<br>
<i>World Wide Web Journal</i><br>
Jianxin Li, Chengfei Liu, Ziyu Guan, Yinghui Wu</li>
<li>Graph Neural Network and Koopman Models for Learning
Networked Dynamics: A Comparative Study on Power Grid
Transients Prediction, <b><i>IEEE Access</i></b>. <br>
Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu, Seemita Pal,
Khushbu Agarwal, Yinghui Wu, Sutanay Choudhury</li>
<li>Learning Distributed Geometric Koopman Operator for Sparse
Networked Dynamical Systems (D-KGNN), <b>Learning on Graphs
Conference</b>.<br>
Sayak Mukherjee, Sai Pushpack Nadanoori, Sheng Guan, Khushubu
Agarwal, Subhrajit Sinha, Soumya Kundu, Seemita Pal, Yinghui
Wu, Draguna L Vrabie, Sutanay Choudhury<br>
</li>
</ol>
<span style="font-weight: bold;"><br>
2021<br>
</span>
<ol>
<li>GEDet: Detecting Erroneous Nodes with A Few Examples<br>
<span style="font-style: italic;">The 47rd International
Conference on Very Large Data Bases</span> (<span
style="font-weight: bold; font-style: italic;">VLDB</span>),
demo track, 2021<br>
Sheng Guan, Hanchao Ma, Sutanay Choudhury, Yinghui Wu</li>
<li><a href="https://dl.acm.org/doi/abs/10.1145/3448016.3452758">GRIP:
Constraint-based Explanation of Missing Entities in Graph
Search</a><br>
<span style="font-style: italic;">ACM SIGMOD Conference on
Management of Data</span> (<span style="font-weight: bold;
font-style: italic;">SIGMOD</span>), demo track <span
style="font-style: italic;">[<a
href="https://www.youtube.com/watch?v=OwGGCHWKLkk&list=PL3xUNnH4TdbsfndCMn02BqAAgGB0z7cwq&ab_channel=SIGMOD2021">Video</a>]</span><br>
Qi Song, Peng Lin, Hanchao Ma, Yinghui Wu<br>
</li>
<li>Explaining Missing Data in Graphs: A Constraint-based
Approach<br>
Int.Conf.on Data Engineering (<span style="font-weight: bold;
font-style: italic;">ICDE</span>)<br>
Qi Song, Peng Lin, Hanchao Ma, Yinghui Wu<br>
</li>
<li><a href="https://ieeexplore.ieee.org/document/9335975/">Anomaly
Detection, Localization and Classification using Drifting
Snchrophasor Data Streams</a><br>
<span style="font-style: italic; font-weight: bold;">IEEE
Transactions on Smart Grid</span><br>
Arman Ahmed, Sajan Kaduvettykun, Anurag Srivastava, Yinghui Wu
<br>
</li>
<li><a
href="https://ojs.aaai.org/index.php/AAAI/article/view/17799">Spatialtemporal
Graph Neural Network for Performance Prediction of
Photovoltaic Power Systems</a><br>
<span style="font-style: italic;">The 33rd Annual Conference
on Innovative Applications of Artificial Intelligence</span>
(<span style="font-weight: bold; font-style: italic;">AAAI</span>-<b>IAAI</b>)
<br>
Ahmad Maroof Karimi, Yinghui Wu, Mehmet Koyuturk, Roger French</li>
</ol>
<span style="font-weight: bold;"><br>
2020</span><br>
<ol>
<li><a href="https://ieeexplore.ieee.org/document/9377897">GEDet:
Adversarially Learned Few-shot Detection of Erroneous Nodes
in Graphs</a><br>
<span style="font-style: italic;">IEEE International
Conference on Big Data</span> (<span style="font-weight:
bold; font-style: italic;">IEEE BigData</span>) <span
style="color: rgb(253, 8, 45);">(</span><span style="color:
rgb(253, 8, 45); font-style: italic; font-weight: bold;">Best
Paper Award</span><span style="color: rgb(253, 8, 45);">)</span><br>
Sheng Guan, Peng Lin, Hanchao Ma, Yinghui Wu</li>
<li><a href="https://ieeexplore.ieee.org/document/9302877">Answering
Why-Quetions for Subgraph Queries</a><br>
IEEE Transactions on Knowledge and Data Engineering (<span
style="font-weight: bold; font-style: italic;">TKDE</span>)<br>
Qi Song, Mohammad Hossein Namaki, Peng Lin, Yinghui Wu</li>
<li><a href="https://ieeexplore.ieee.org/document/9201321">A
Stochastic Approach to Finding Densest Temporal Subgraphs in
Dynamic Graphs</a><br>
IEEE Transactions on Knowledge and Data Engineering (<span
style="font-weight: bold; font-style: italic;">TKDE</span>).
<br>
Xuanmin Liu, Tingjian Ge, Yinghui Wu</li>
<li><a
href="https://www.kdd.org/kdd2020/accepted-papers/view/vamsa-automated-provenance-tracking-in-data-science-scripts">Vamsa:Automated
Provenance Tracking in Data Science Scripts</a><br>
The 26th Int. Conf. on Knowledge Discovery and Data Mining<span
style="font-style: italic;">(</span><span
style="font-weight: bold; font-style: italic;">KDD</span><span
style="font-style: italic;">)</span><br>
Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas,
Subru Krishnan, Ashvin Agrawal, Yinghui Wu<br>
</li>
<li><a href="https://ieeexplore.ieee.org/document/9101867">Kronos:
Lightweight Knowledge-based Event Analysis in Cyber-Physical
Data Streams</a><br>
Int.Conf.on Data Engineering (<span style="font-weight: bold;
font-style: italic;">ICDE</span>)<br>
Mohammad Hossein Namaki, Xin Zhang, Sukhjinder Singh, Arman
Ahmed, Armina Foroutan, Yinghui Wu, Anurag Srivastava, Anton
Kocheturov. <br>
</li>
<li><a href="https://ieeexplore.ieee.org/document/9101352">Repairing
Entities using Star Constraints in Multirelational Graphs.</a>
<br>
<span style="color: rgb(0, 0, 0); font-family:
Verdana,Geneva,Tahoma,sans-serif; font-size: small;
font-style: normal; font-variant: normal; font-weight:
normal; letter-spacing: normal; line-height: normal;
text-align: left; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px; display:
inline ! important; float: none; background-color: rgb(255,
255, 255);">Int.Conf.on Data Engineering (<span
style="font-weight: bold; font-style: italic;">ICDE</span>)</span>
<br>
<span style="color: rgb(0, 0, 0); font-family:
Verdana,Geneva,Tahoma,sans-serif; font-size: small;
font-style: normal; font-variant: normal; font-weight:
normal; letter-spacing: normal; line-height: normal;
text-align: left; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px; display:
inline ! important; float: none; background-color: rgb(255,
255, 255);">Peng Lin, Qi Song, Yinghui Wu, Jiiaxing Pi.</span></li>
</ol>
<span style="font-weight: bold;">2019 </span><br>
<ol>
<li><a href="http://www.vldb.org/pvldb/vol12/p1195-ma.pdf">Ontology-based
Entity Matching in Attributed Graphs</a>.<br>
<span style="font-style: italic;">The 45rd International
Conference on Very Large Data Bases</span> (<span
style="font-weight: bold; font-style: italic;">VLDB</span>),
2019<br>
Hanchao Ma, Morteza Alipour Langouri, Yinghui Wu, Fei Chiang,
Jiaxing Pi</li>
<li><a
href="https://www.kdd.org/kdd2019/accepted-papers/view/attribute-driven-backbone-discovery">Attribute-Driven
Backbone Discovery. </a><br>
The 25th Int. Conf. on Knowledge Discovery and Data Mining<span
style="font-style: italic;">(</span><span
style="font-weight: bold; font-style: italic;">KDD</span><span
style="font-style: italic;">),</span>2019<br>
Sheng Guan, Hanchao Ma, Yinghui Wu, Jiaxing Pi<br>
</li>
<li><a href="https://dl.acm.org/doi/10.1145/3299869.3320245">NAVIGATE:
Explainable Visual Graph Exploration by Examples.</a> <br>
ACM SIGMOD Conference on Management of Data <span
style="font-style: italic;">(</span><span
style="font-weight: bold; font-style: italic;">SIGMOD</span><span
style="font-style: italic;">)</span>, 2019<br>
Mohammad Hossein Namaki, Qi Song, Yinghui Wu</li>
<li><a href="https://dl.acm.org/doi/10.1145/3299869.3319890">Answering