Yao Ma

Image of Yao 

Assistant Professor
Department of Computer Science
Ying Wu College of Computing
New Jersey Institute of Technology

Data Analytics and Machine Intelligence (DAMI) Lab

Email: yao dot ma at njit dot edu
Office: GITC 4204

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Short Bio

Yao Ma is an assistant professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT).
He got his PhD from Michigan State University in 2021 under the supervision of Dr. Jiliang Tang. Before that, he completed his MS (2016) in Statistics, Probability & Operations Research at Eindhoven University of Technology and BS (2015) in Mathematics and Applied Mathematics at Zhejiang University.

I have several fully-funded PhD positions available in Spring 2023 and Fall 2023. If you are interested in working with me, please feel free to email me. Please check here for more details.

Research Interests

  • Machine Learning with Graphs, Graph Neural Networks

  • Trustworthy AI: Robustness, Fairness, Privacy

  • Data Centric-AI: Data Augmentation, Active Learning, Data Valuation, Data Condensation

Call for Papers

  • Machine Learning on Complex Graphs - Frontiers in Big Data (Topic Editor)

    • Welcomed topics include: graph kernels/summarization/coarsening/alignment/etc, graph neural networks, network embedding, related applications, etc

    • We especially invite submissions with emphasis on complex graphs such as dynamic/hyper/heterogeneous/knowledge graphs

    • Paper Submission Deadline: November 25th 2022 (link)

News (more)

  • 01/2023 Receving a gift grant from Shell for the project Supply Chain Network Optimization. Thanks Shell!

  • 12/2022 Invited to serve as a grant proposal panelist for NSF.

  • 11/2022 Our workshop Data Science for Smart Manufacturing and Healthcare was accepted by SDM2023.

  • 10/2022 Our workshop Machine Learning on Graphs (MLoG) is accepted by WSDM2023.

  • 08/2022 Honored to receive a research grant from NSF for the project Collaborative Research: III: Medium: Graph Neural Networks for Heterophilous Data: Advancing the Theory, Models, and Applications as the Site PI at NJIT.

  • 08/2022 Invited to give a talk for the Data Science Show at AT&T Labs.

  • 08/2022 New preprint on graph contrastive learning is available here.

  • 07/2022 Invited to serve as Senior PC member for AAAI2023.

  • 05/2022 One paper accepted by KDD2022.

  • 04/2022 Our workshop Machine Learning on Graphs (MLoG) is accepted at ICDM2022.

  • 03/2022 Invited to serve as a PC menber for KDD2022, ICML2022, IJCAI2022, and NeurIPS2022.

  • 02/2022 Gratefully received an NSF CRII grant (IIS-2153326) as the PI to support our research on advancing graph neural networks.

  • 01/2022 Two papers accepted by ICLR2022.

  • 11/2021 Our workshop “Machine Learning on Graphs (MLoG)” has been accpeted by WSDM2022.

  • 10/2021 Invited to serve as Proceddings Co-chair of KDD2022.

  • 10/2021 Invited to serve as PC member for SDM 2022.

  • 10/2021 Invited to serve as PC menber for The Web Conference 2022.

  • 09/2021 One paper accepted by NeurIPS2021.

  • 08/2021 Two papers accepted by CIKM2021.