Xiaochen is a Research Scientist at ByteDance with expertise in AutoML, deep learning, and computer vision. He holds a PhD from UCLA, where his research centered on efficient Neural Architecture Search. His work focuses on developing and optimizing advanced AI models.
His PhD dissertation and subsequent publications focus on Neural Architecture Search (NAS), a key technique for automating the design of efficient AI models.
Xiaochen Lian
Research Scientist at ByteDance
Los Angeles, California, United States
Overview
Topics They Care About
Neural Architecture Search
His PhD thesis at UCLA and multiple publications focus on this topic, indicating it is a core area of his professional expertise and interest.
Efficient Deep Learning
Much of his published research aims to make AI models more efficient and optimized for specific hardware, a key challenge in the field.
AutoML
This is a primary focus of his current role at ByteDance and a recurring theme throughout his academic and professional work.
Media Appearances
Xiaochen has no verified media appearances
Work History
1-2019
Research Scientist at ByteDance
4-2017 - 1-2019
Research Scientist at Baidu USA
7-2009 - 4-2010
Internship at Microsoft
7-2007 - 10-2007
Internship at Microsoft
Education
2011 - 2016
PhD from UCLA
2008 - 2011
Master of Science (M.S.) from Shanghai Jiao Tong University
More Information
Social Presence :
Prographics :
Exp : 9
Location : Los Angeles, California, United States
Job Level : N/A
Designation : Research Scientist at ByteDance
