Hongyu (Charlie) Chen

Hongyu (Charlie) Chen's work experience begins in 2018 when they worked as a Mathematics Tutor for the University of Toronto Medical Society. In 2019, they joined MannLab as a Research Assistant, where they worked on projects related to Brain-Computer Interfaces, Artificial Intelligence, and Electronics. During this time, they also published a paper on the integrity and trust of sensors in eye technology.

In 2019, Hongyu became a Committee Member for AI Squared Forum, where they organized and managed researcher panels and research talks. In 2020, they worked as a Data Research Analyst for Synced 机器之心, where they co-authored the annual AI Technology Development Report and developed a Python text mining tool for insight extraction.

In the same year, they joined Qualcomm as a Machine Learning Researcher & Engineer, where they researched neural network quantization for training and inference on mobile devices. Hongyu (Charlie) published a study on low-precision quantization for TinyML and built a flexible framework for post-training quantization techniques.

Starting in 2021, Hongyu worked as a Student Researcher at the Vector Institute, focusing on "Trustworthy ML" research under the guidance of Professor Nicolas Papernot. Hongyu (Charlie) also completed their undergraduate thesis on the topic of quantization advised by a professor.

Finally, in 2022, Hongyu joined Cohere as a Machine Learning Engineer, where they are currently employed.

From 2017 to 2022, Hongyu (Charlie) Chen attended the University of Toronto, where they earned a Bachelor of Applied Science in Engineering Science. Their field of study during this time was focused on Machine Intelligence.