Hi, I'm Wang Shida(汪铈达).

I'm a final year Ph.D. candidate at math department, National University of Singapore (NUS).
I'm fortunate to be advised by Professor Li Qianxiao. Before that, I studied applied math at Fudan University.
My research interests are about sequence modelling in machine learning, language models and nonlinear systems.

Educational Background:
Ph.D. in Mathematics, National University of Singapore, Singapore, 2020-2024
B.S. in Mathematics, Fudan University, Shanghai, China, 2016-2020

Published:
1. Inverse Approximation Theory for Nonlinear Recurrent Neural Networks (ICLR 2024, spotlight)
    GitHub repo: Curse-of-memory
2. StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization (ICML 2024)
3. State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory (NeurIPS 2023)
    GitHub repo: Awesome-state-space-models
4. Efficient Hyperdimensional Computing (ECML 2023)
5. A Brief Survey on the Approximation Theory for Sequence Modelling (JML 2023)
6. Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences (ACS Synthetic Biology)

Manuscripts:
1. LongSSM: On the Length Extension of State-space Models in Language Modelling (ICML 2024 NGSM workshop)
2. Improve Long-term Memory Learning Through Rescaling the Error Temporally
3. HyperSNN: A new efficient and robust deep learning model for resource constrained control applications

Internships:
2024.04-2024.08 01.AI Multi-modal Intern
2023.04-2023.12 Sea AI Lab Intern
2021.08-2021.10 Advance.AI R&D Intern
2019.07-2020.01 Megvii Intern
2019.01-2019.02 Goku-data Intern

Travels:
2023.12.10-2023.12.16 NeurIPS 2023
2024.01.08-2024.01.12 GYSS
2024.05.06-2024.05.10 ICLR 2024
2024.07.08-2024.07.12 Symposium on ML and DS
2024.07.15-2024.07.19 SciCADE
2024.07.21-2024.07.27 ICML 2024
2024.08.19-2024.08.20 Changsha, Central South University
2024.08.30-2024.09.01 Ningbo, Eastern Institute of Technology
2024.09.04-2024.09.08 Shanghai, Fudan University

TA positions:
Teaching Assistant for DSA5102 (2021.08-11)
Teaching Assistant for DSA5101, DSA5102 (2020.08-11)

Skills:
Code: Python (PyTorch, JAX, TensorFlow), C/C++, Haskell

Languages:
Chinese (Mandarin) and English