About Me




Gateway South 448
1 Castle Point Terrace, Hoboken, NJ, USA



Hello! I am an Assistant Professor in the department of Computer Science at Stevens Institute of Technology.

My research interests lie at the intersection of machine learning, graph mining, and data analytics, focusing on social informatics, health care, and financial technologies. In particular, my research group is dedicated to developing predictive and generative methods that effectively capture spatio-temporal, dynamic, and interpretable patterns in large-scale datasets. Our work is supported by the National Science Foundation, Nvidia, and Stevens Institute of Technology.

I received my Ph.D. from the Department of Computer Science of Virginia Tech under Dr. Naren Ramakrishnan.

I am also affiliated with Stevens Institute for Artificial Intelligence (SIAI), Center for Research Toward Advancing Financial Technologies (CRAFT), and Semcer Center for Healthcare Innovation (CHI).

Openings: I am looking for PhD and undergraduate students. Click here if you are interested in working with me.

Research Interests

News

10.2024           Paper on Continual Graph Learning was accepted by NeurIPS 2024.
09.2024           Invited talk at University of Delaware.
08.2024           Tutorial talk at KDD 2024.
08.2024           I will serve as Co-chair for AAAI Doctoral Consortium (2025).
02.2024           Congratulations to Chang on successfully defending his PhD thesis!
11.2023           Invited talk at Case Western Reserve University.
09.2023           Paper on contrastive learning for ICD coding was accepted by NeurIPS 2023.
09.2023           Paper on fair federated graph neural networks was accepted by ICDM 2023.
08.2023           Paper on time series generation was accepted by TKDE.
05.2023           Paper on graph unlearning was accepted by KDD 2023.
05.2023           Received Early Career Award for Research Excellence from Stevens.
03.2023           Stevens media published a nice article on my research.
02.2023           Invited talk at ADP Data Science and Machine Learning.
12.2022           Invited keynote talk at MLoG workshop at ICDM'22.
10.2022           Paper on news-enhanced pandemic forecasting was accepted by IEEE BigData 2022.
09.2022           Two papers were accepted by ICDM 2022.
07.2022           Congratulations to Dr. Deng who successfully defended her PhD thesis!
05.2022           Songgaojun Deng received the Excellence in Graduate Research Award from Stevens!
05.2022           Chang Lu started summer internship at NEC Labs America.
05.2022           Paper on causal event analysis was accepted by KDD 2022.
12.2021           Paper on health event prediction using dynamic disease graphs was accepted by AAAI 2022.
11.2021           Invited talk at the Computer Science department, NJIT.
11.2021           Paper on anti-Asian hate speech detection was accepted by ICWSM 2022.
09.2021           I am serving as student travel award co-chair for KDD 2022.
08.2021           Paper on interpretable event prediction was accepted by CIKM 2021.
06.2021           I am honored to receive an NSF CAREER award to explore deep interpretable methods for temporal event modeling. Thanks NSF!
05.2021           PhD student Songgaojun Deng received Excellence Doctoral Fellowship. Congratulations Songgaojun!
04.2021           Paper on collaborative graph learning for health event prediction was accepted by IJCAI 2021.
02.2021           Check out our toturial on Explainable AI for Societal Event Predictions in AAAI 2021.
02.2021           Paper on fake news detection was accepted by PAKDD 2021.
01.2021           I will serve on the Bergen County Academies ATCS advisory board.
11.2020           I will serve as a senior PC for IJCAI-2021.
10.2020           Paper on asynchronous online federated learning was accepted by IEEE BigData 2020.
07.2020           Paper on predicting long-term influenza-like illness cases was accepted by CIKM 2020.
07.2020           Invited to serve on the PC of ICLR 2021, IJCAI 2021, TheWebConf 2021.
05.2020           Paper on dynamic knowledge graph based multi-event forecasting was accepted by KDD 2020.
05.2020           Received an NSF CRII award to explore and create deep learning models for learning dynamic graph-based event precursors. Thanks NSF!
03.2020           Paper on reducing identity bias in detecting toxic comment detection was accepted by ICWSM 2020.
09.2019           Received an Nvidia GPU grant. Thanks Nvidia!
08.2019           I will be teaching a new course: Natural Language Processing in the fall semester.
08.2019           Invited to serve on the PC of AAAI 2020.
04.2019           Paper on modeling dynamic event context graphs was accepted by KDD 2019.
04.2019           Check out our tutorial on Spatio-Temporal Event Forecasting and Precursor Identification in KDD 2019.
01.2019           Invited to serve on the PC of KDD 2019, ASONAM 2019, SDM 2019.

Professional Service

  • Organizing Committee
    • Doctoral Consortium Co-chair: AAAI 2025
    • Local Arrangement Chair: IEEE INFOCOM 2023
    • Student Travel Award Co-chair: KDD 2022
  • Area Chair: KDD 2024, KDD 2025
  • Session Chair
    • SDM 2021
    • KDD 2020
  • Senior PC: IJCAI 2021
  • Program Committee: KDD 2019-2023
  • Program Committee: AAAI 2020-2024
  • Program Committee: ICLR 2021, 2023, 2024
  • Program Committee: ICML 2020-2023
  • Program Committee: NeurIPS 2021-2023
  • Program Committee: IJCAI 2021-2023
  • Program Committee: CVPR 2023
  • Program Committee: The Web Conf (previously WWW) 2021-2023
  • Program Committee: CIKM short paper track 2022
  • Program Committee: PAKDD 2020-2022
  • Program Committee: SDM 2019-2024
  • Program Committee: IEEE BigData 2020-2023
  • Program Committee: ICMLA 2019
  • Program Committee: ASONAM 2018-2022
  • Reviewer: Sensors, published by MDPI
  • Reviewer: Nature Communications
  • Reviewer: Pattern Recognition
  • Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Reviewer: ACM Transactions on Knowledge Discovery from Data (TKDD)
  • Reviewer: IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • Reviewer: Social Network Analysis and Mining (SNAM)
  • Reviewer: IEEE Transactions on Intelligent Transportation Systems (T-ITS)
  • Reviewer: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
  • Reviewer: IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • Guest Editor: Frontiers in Big Data

Contact

Mailing Address

1 Castle Point Terrace,
Hoboken, NJ 07030,
USA

Office

Gateway South 448

Email

yue.ning AT stevens.edu