The machine learning and data analytics lab at NTU EEE (MLDA@EEE) regularly host workshops on machine learning and related topics for students within NTU to come together to share, learn and discuss. As a senior member of MLDA@EEE, I hosted a workshop on spiking neural networks (SNN) in 2022 to share a part of my research interest in Neuromorphic engineering. Being the first to give a workshop on this topic was exciting, and I got to do so while mentoring a freshman member of MLDA@EEE as my co-instructor. Not only was Ho Chi a fast learner, he was responsible and well-prepared, enabling him to to deliver his first workshop at MLDA@EEE successfully. The workshop saw over 70 participants, both undergraduate and graduate students, and with students from the school of Computer Science and Computer Engineering and even the Nanyang Business School. It consist of two segments. The theory segement introduces the motivation, mathematics model of a leaky integrate-and-fire neuron, the spike-encoding styles and the value of it. The second segement is a practical session where participants were guided in implementing a SNN on Google Colab using snnTorch to for a image classification task. The participants were excited and showed passion in the topic, as they asked numerous questions and some even reached out to learn more after the workshop. The workshop recording can be watched on the MLDA@EEE Youtube Channel.

Reference for snnTorch Jason K. Eshraghian, Max Ward, Emre Neftci, Xinxin Wang, Gregor Lenz, Girish Dwivedi, Mohammed Bennamoun, Doo Seok Jeong, and Wei D. Lu “Training Spiking Neural Networks Using Lessons From Deep Learning”. arXiv preprint arXiv:2109.12894, September 2021.