Dr. Hongjie Chen

(LinkedIn)

(Google Scholar)

I am a Researcher at Dolby Labs. My current research centers on graph, time series, audio, and representation learning, all within the domain of AI.

Publications

Journals

  • Graph Time-series Modeling in Deep Learning: A Survey [ACM]
    H. Chen, H. Eldardiry
    2024 ACM Transactions on Knowledge Discovery from Data (TKDD)

  • Graph Deep Factors for Probabilistic Time-series Forecasting [ACM]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2023 ACM Transactions on Knowledge Discovery from Data (TKDD)

Conferences

  • A Work on Graph Time-Series Forecasting (To Appear)
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2025 Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD)

  • A Quantitative Metric Selection Approach for Time-series Forecasting Foundation Models [IEEE]
    H. Chen, A. Mehra, J. Kimball, S. Kim
    2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

  • LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series [IEEE]
    H. Chen, A. D. Beachnau, P. Thomas, P. Maneriker, J. Kimball, R. A. Rossi
    2024 IEEE International Conference on Big Data (IEEE BigData)

  • A Study of Foundation Models for Large-scale Time-series Forecasting [IEEE]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2024 IEEE International Conference on Big Data (IEEE BigData)

  • Evolving Super Graph Neural Networks for Large-scale Time-Series Forecasting [Springer]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2024 ACM The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

  • Hypergraph Neural Networks for Time-series Forecasting [IEEE]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2023 IEEE International Conference on Big Data (IEEE BigData)

  • Context Integrated Relational Spatio-Temporal Resource Forecasting [IEEE]
    H. Chen, R. A. Rossi, K. Mahadik, H. Eldardiry
    2021 IEEE International Conference on Big Data (IEEE BigData)

  • Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation [ACM]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2021 Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD)

  • LncRNA-disease association prediction based on neighborhood information aggregation in neural network [IEEE]
    H. Chen, X. Wang, X. Zhang, X. Zeng, T. Song, A. Rodríguez-Patón
    2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Patents & Copyrights

  • US patent - Deep Hybrid Graph-Based Forecasting Systems

  • China software copyright - Continuous Weighing of Living Aquatic Creatures

Experiences

Research

  • 2024 - Virginia Tech, Doctoral degree from Computer Science at Virginia Tech

  • 2023 - Yahoo! Research Intern, Research on large-scale graphs and graph classification with Dr. Meizhu Liu

  • 2020 - Adobe Research Intern, Research on graphs and time-series with Dr. Kanak Mahadik and Dr. Ryan Rossi

Services

  • Reviewer, CIKM (2023), ICASSP (2025), IJCNN (2025), KDD (2025, 2024), TKDE (2025)

  • Advisor, Master@VT (2024)

  • Mentor, 4 Master@Umass Amherst (2025), Master@VT (2025, 2023), 3 Undergraduate@VT(2022)

Teaching

  • Teaching Assistant, CS4824 Introduction to Machine Learning (2024S), CS5704 Software Engineering (2023F), CS4824 Introduction to Machine Learning (2022S), CS4604 Introduction to Data Base Management Systems (2021F), CS4104 Data and Algorithm Analysis (2021S), CS4824 Introduction to Machine Learning (2020F), CS4804 Introduction to Artificial Intelligence (2020S)

  • Instructor, Instruct CS4824 Introduction to Machine Learning (2022 Summer)

  • Guest lecturer, 2X CS5806 Machine Learning II (2023F), CS6804 Multisource Machine Learning (2022F), CS4984 Machine Learning Capstone (2020F)

Journals

  • Graph Time-series Modeling in Deep Learning: A Survey [ACM]
    H. Chen, H. Eldardiry
    2024 ACM Transactions on Knowledge Discovery from Data (TKDD)

  • Graph Deep Factors for Probabilistic Time-series Forecasting [ACM]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2023 ACM Transactions on Knowledge Discovery from Data (TKDD)

Conferences

  • Evolving Super Graph Neural Networks for Large-scale Time-Series Forecasting [Springer]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2024 ACM The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

  • Hypergraph Neural Networks for Time-series Forecasting [IEEE]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2023 IEEE International Conference on Big Data (IEEE BigData)

  • Context Integrated Relational Spatio-Temporal Resource Forecasting [IEEE]
    H. Chen, R. A. Rossi, K. Mahadik, H. Eldardiry
    2021 IEEE International Conference on Big Data (IEEE BigData)

  • Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation [ACM]
    H. Chen, R. A. Rossi, K. Mahadik, S. Kim, H. Eldardiry
    2021 Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD)

  • LncRNA-disease association prediction based on neighborhood information aggregation in neural network [IEEE]
    H. Chen, X. Wang, X. Zhang, X. Zeng, T. Song, A. Rodríguez-Patón
    2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Patents & Copyrights

  • US patent - Deep Hybrid Graph-Based Forecasting Systems

  • China software copyright - Continuous Weighing of Living Aquatic Creatures

Research

  • 2023 - Yahoo! Research Intern, Research on the topic of large-scale graphs and graph classification under the supervision of Dr. Meizhu Liu

  • 2020 - Adobe Research Intern, Research on the topic of graphs and time-series under the supervision of Dr. Kanak Mahadik and Dr. Ryan Rossi

Services

  • 2024 - Reviewer, Serve to review papers for KDD, ICASSP, Journal of Supercomputing

  • 2023 - Reviewer, Serve to review papers for CIKM

  • 2023 - Mentor, Mentor a graduate student

  • 2023 - Panelist, Serve as a panelist for TechGirls camp

  • 2023 - Presenter, Present a poster in ML Day: Amazon - VT Initiative for Efficient and Robust Machine Learning

  • 2022 - Mentor, Mentor three undergraduate students

Teaching

  • 2024 - Teaching Assistant, Assist for an undergraduate senior class CS4824 Introduction to Machine Learning

  • 2023 - Guest speaker, Give a talk for an undergraduate-level class CS3604 Professionalism in Computing

  • 2023 - Guest lecturer, Give two lectures for a graduate-level class CS5806 Machine Learning II

  • 2023 - Teaching Assistant, Assist for a graduate-level class CS5704 Software Engineering

  • 2022 - Instructor, Instruct an undergraduate senior class CS4824 Introduction to Machine Learning

  • 2022 - Guest lecturer, Give a lecture for a graduate-level class CS6804 Multisource Machine Learning

  • 2022 - Teaching Assistant, Assist for an undergraduate senior class CS4824 Introduction to Machine Learning

  • 2021 - Teaching Assistant, Assist for an undergraduate senior class CS4604 Introduction to Data Base Management Systems

  • 2021 - Teaching Assistant, Assist for an undergraduate senior class CS4104 Data and Algorithm Analysis

  • 2020 - Guest lecturer, Give a lecture for an undergraduate senior class CS4984 Machine Learning Capstone

  • 2020 - Teaching Assistant, Assist for an undergraduate senior class CS4824 Introduction to Machine Learning

  • 2020 - Teaching Assistant, Assist for an undergraduate senior class CS4804 Introduction to Artificial Intelligence