Anh Tong

Assistant Professor @ Korea University

My name is Anh Tong. I’m an Assistant Professor in the Department of Artificial Intelligence at Korea University (visit our lab website here). Before joining Korea University, I was a postdoc researcher at KAIST. I obtained a Ph.D. in Computer Science at Ulsan National Institute of Science and Technology (UNIST) working with Prof. Jaesik Choi. My research interests include probabilistic machine learning methods, Gaussian processes. My Ph.D. thesis studies model selection problems for Gaussian processes in relational learning settings for time series modeling, extending to scalable paradigm.

news

Sep 26, 2024 Give invited talk “Learning Fractional White Noise in Neural Stochastic Differential Equations” at Rough Path Interest Group.
Feb 27, 2024 Join the Department of Artificial Intelligence at Korea University as an Assistant Professor from Spring 2024
Sep 28, 2023 Our paper titled “SigFormer: Signature Transformers for Deep Hedging” is accepted for oral presentation at the ICAIF-2023 conference.
Aug 17, 2023 Visited ML group in TU Kaiserslautern last week. Grateful to Prof. Marius Kloft and DAAD for the support.
Apr 12, 2023 I was selected as one of the 2023 DAAD AInet fellows.

selected publications

  1. ICAIF
    SigFormer: Signature Transformers for Deep Hedging
    Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan Tran, and Jaesik Choi
    4th ACM International Conference on AI in Finance 2023
    PDF Code
  2. NeurIPS
    Learning Fractional White Noises in Neural Stochastic Differential Equations
    Anh Tong, Thanh Nguyen-Tang, Toan Tran, and Jaesik Choi
    NeurIPS 2022
    PDF Code
  3. AAAI
    Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior
    Anh Tong, Toan Tran, Hung Bui, and Jaesik Choi
    AAAI Conference on Artificial Intelligence (AAAI) 2021
    PDF
  4. AAAI
    Characterized Deep Gaussian Processes via Nonlinear Recurrence Systems
    Anh Tong, and Jaesik Choi
    AAAI Conference on Artificial Intelligence (AAAI) 2021
    PDF
  5. ICML
    Discovering Latent Covariance Structures for Multiple Time Series
    Anh Tong, and Jaesik Choi
    In Proceedings of the 36th International Conference on Machine Learning (ICML) 2019
    PDF
  6. ICML
    Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series
    Yunseong Hwang, Anh Tong, and Jaesik Choi
    In Proceedings of the 33nd International Conference on Machine Learning (ICML) 2016
    PDF