About me

I’m Kaiwen Sheng, currently a PhD student in bioengineering at Stanford University. In the summer of 2023, I worked with Prof. Jun Ding at Stanford on motor learning. Previously, I got my Master’s degree in neuroscience from UCL, supervised by Prof. Michael Häusser, Prof. Beverley Clark and Dr. Brendan Bicknell, working on dendrites and cell types. Previous than that, I obtained my Bachelor degree in Computer Science from Peking University in 2020, supervised by Dr. Kai Du and Prof. Tiejun Huang. My research interests lie in learning and computation in neural circuits.

NEWS

• 2024.04 Paper published on Cell Research: System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning [link]

• 2022.10 Preprint published on bioRxiv: Domain Adaptive Neural Inference for Neurons, Microcircuits and Networks [link]

• 2022.04 Paper published on Frontiers in Computational Neuroscience: U-RISC: An Annotated Ultra-High-Resolution Electron Microscopy Dataset Challenging the Existing Deep Learning Algorithms [link]

• 2022.03 Paper published on Frontiers in Behavioral Neuroscience: Siamese Network-Based All-Purpose-Tracker, a Model-Free Deep Learning Tool for Animal Behavioral Tracking [link]

• 2021.03 Preprint published on bioRxiv: A General LSTM-based Deep Learning Method for Estimating Neuronal Models and Inferring Neural Circuitry [link]

• 2020.10 Preprint published on arXiv: Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation [link]

• 2020.03 Paper published on ASPLOS 2020: FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System [link]