Khai Loong Aw


Welcome! I am Khai. I am interested in research at the intersection of machine learning and neuroscience. I am currently applying for PhD programs that start in Fall 2024.

In 2023, I worked with Martin Schrimpf and Antoine Bosselut at EPFL. We studied the representational and behavioral similarities between Large Language Models (LLMs) and the human language system.

In 2022, I worked with Mariya Toneva at the MPI for Software Systems. We studied how to train language models to improve their representational alignment to human brain activity.

Before this, I worked with Qianru Sun on the computer vision task of semantic segmentation, where we focused on approaches using transfer learning and self-supervised learning algorithms. I also worked with David Lo, where we applied machine learning methods to identify bugs in software programs.

Additionally, I worked in industry at GovTech Singapore, where I improved the processing speed of state-of-the-art algorithms for Multi-Object Tracking, i.e., tracking the motion of multiple animals and humans within a video sequence.

selected publications

  1. Instruction-tuning Aligns LLMs to the Human Brain
    Under Review 2023
  2. ICLRSpotlight
    Training language models to summarize narratives improves brain alignment
    Khai Loong Aw, and Mariya Toneva
    International Conference on Learning Representations (ICLR) 2023
  3. ICSE
    Detecting False Alarms from Automatic Static Analysis Tools: How Far are We?
    Hong Jin KangKhai Loong Aw, and David Lo
    International Conference on Software Engineering (ICSE) 2022