I am a Software Engineer at Google. I received my PhD in Department of Computer Science at the CSE department of Texas A&M University. I worked at the DATA Lab under the supervision of Dr. Xia Hu since 2017. Before joining TAMU, I received my B.S. degree in Computer Science from Wuhan University in 2017. My research interests focus on data mining and machine learning, with interests in anomaly detection, network embedding, and automated machine learning (AutoML).

Education

• B.S. in Computer Science, Wuhan University, 2017
• Ph.D. in Computer Science, Texas A&M University, 2021

Work experience

• Spring 2022 - Now: Software Engineer, Google

• Summer 2021: Research Intern, Google

• Summer 2020: Research Intern, Google

• Spring 2020: Research Intern, NEC Laboratories America

• Fall 2015 - Fall 2021: Research Assistant, Texas A&M University

Service and leadership

• Conference program committees: WSDM 2023, SDM 2023, NeurIPS 2022, KDD 2022, ICML 2022, ICLR 2022, AAAI 2022, WSDM 2022, NeurIPS 2021, KDD 2021, CIKM 2021, AAAI 2021, NeurIPS 2020, AAAI 2020, ICBD 2020, KDD 2020, CIKM 2019
• Journal reviewers: IEEE Transactions on Neural Networks and Learning Systems, IEEE Intelligent Systems, ACM Transactions on Intelligent Systems and Technology, IEEE/CAA Journal of Automatica Sinica, Neurocomputing

Publications

You can also find my articles on my Google Scholar profile.

Towards Learning Disentangled Representations for Time Series

Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

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RES: An Interpretaable Replicability Estimation System for Research Articles

Published in AAAI Conference on Artificial Intelligence (AAAI), 2022

Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning

Published in IEEE Transactions on Neural Networks and Learning Systems, 2021

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AutoOD: Neural Architecture Search for Outlier Detection

Published in IEEE International Conference on Data Engineering (ICDE), 2021

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Mitigating Gender Bias in Captioning Systems

Published in International World Wide Web Conference (WWW), 2021

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PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning

Published in International World Wide Web Conference (WWW), 2020

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Towards Deeper Graph Neural Networks with Differentiable Group Normalization

Published in Conference on Neural Information Processing Systems (NeurIPS), 2020

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Dual Policy Distillation

Published in International Joint Conference on Artificial Intelligence (IJCAI), 2020

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Locality Aware Autoencoder for Manipulated Forgery Detection

Published in ACM International Conference on Information and Knowledge Management (CIKM), 2020

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Spectral Autoencoder for Anomaly Detection in Attributed Networks

Published in ACM International Conference on Information and Knowledge Management (CIKM), 2019

Best Refereed Paper Finalist, INFORMS QSR Section.

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Graph Recurrent Networks with Attributed Random Walks

Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

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Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

Published in ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

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Deep Structured Cross-Modal Anomaly Detection

Published in IEEE International Joint Conference on Neural Networks (IJCNN), 2019

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