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Shenyang Huang

Preferred name: Andy
Ph.D. student at School of Computer Science, McGill University
and Mila - Quebec Artificial Intelligence Institute
E-mail: shenyang.huang@mail.mcgill.ca
Github: https://github.com/shenyangHuang
CV: Shenyang Huang
Linkedin: https://www.linkedin.com/in/shenyang-huang

Bio

I am a Ph.D. student at Mila and McGill University , supervised by Professor Reihaneh Rabbany and Professor Guillaume Rabusseau . Previously I obtained an Honours in Computer Science from McGill University in 2019. My current research focus on anomaly detection in dynamic graph using spectral techniques. I have also worked on integrating autoML techniques into continual learning settings.


Publications

2021

  • Huang, S., François-Lavet, V., & Rabusseau, G. Understanding Capacity Saturation in Incremental Learning. Canadian Conference on Artificial Intelligence 2021
  • Ding, X., Huang, S., Leung, A., Rabbany, R. Incorporating dynamic flight network in SEIR to model mobility between populations. Applied Network Science, Special issue on Epidemics Dynamics & Control on Networks
  • 2020

  • Huang, S., Hitti, Y., Rabusseau, G. & Rabbany, R. Laplacian Change Point Detection for Dynamic Graphs. (KDD 2020)
  • Leung, A., Ding, X., Huang, S., Rabbany, R. Contact Graph Epidemic Modelling of COVID-19 for Transmission and Intervention Strategies.
  • Alletto, S., Huang, S., François-Lavet, V., Nakata, Y., & Rabusseau, G. RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. AAAI 2020 Meta-Eval Workshop
  • 2019

  • Huang, S., François-Lavet, V., & Rabusseau, G. Neural Architecture Search for Class-incremental Learning (previous version of "Understanding Capacity Saturation in Incremental Learning")
  • 2018

  • Huang, S., François-Lavet, V., Rabusseau, G. & Pineau, J. Exploring Continual Learning Using Incremental Architecture Search NeuIPS Continual Learning Workshop 2018.

  • Reviewing

  • KDD 2021 External Reviewer
  • IEEE Transactions on Neural Networks and Learning Systems Reviewer 2021
  • ECML PKDD 2020 Program Committee Member
  • Teaching Assistantship

  • Winter 2020 COMP 250, Introduction to Computer Science
  • Fall 2019 COMP 202, Introduction to Programming