Chenyang Huang
About Chenyang Huang
Chenyang Huang is a Machine Learning Research Intern at Borealis AI, where he has worked since 2019. He holds a Doctor of Philosophy from the University of Alberta and has contributed to research on optimizing deeper transformers.
Work at Borealis AI
Chenyang Huang has been employed at Borealis AI as a Machine Learning Research Intern since 2019. In this role, he focuses on machine learning applications and contributes to various research projects. His work involves applying advanced machine learning techniques to optimize algorithms and improve performance in practical scenarios.
Education and Expertise
Chenyang Huang has an extensive educational background in the field of science and machine learning. He earned a Bachelor of Science degree from Northwestern Polytechnic University from 2009 to 2013. He then completed a Bachelor of Science at the University of Windsor from 2013 to 2015. Following this, he pursued a Master's degree from the University of Alberta from 2015 to 2019, culminating in a Doctor of Philosophy degree from the same institution from 2019 to 2023.
Research Contributions
Chenyang Huang has contributed to significant research in the field of machine learning, particularly focusing on optimizing deeper transformers for small datasets. His work in this area aims to enhance the efficiency and effectiveness of machine learning models when working with limited data resources.
Publications and Collaborations
Chenyang Huang co-authored a research paper on optimizing deeper transformers, collaborating with several researchers including Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi, Jackie Chi Kit Cheung, Simon J.D. Prince, and Yanshuai Cao. This publication reflects his active involvement in the academic community and his contributions to advancing knowledge in machine learning.