Hong-You Chen
About Me
I am a Machine Learning Researcher at Apple AI/ML. I have been working on vision foundation models, multimodal language models, video understanding, etc.
During my PhD, I worked on improving deep learning for practical problems to serve the end users better, such as federated learning and personalization. Thesis title: Machine Learning with Many Users
I received my Ph.D. from the Department of Computer Science and Engineering (CSE) at the Ohio State University (OSU), where I was fortunate to be advised by Dr. Wei-Lun (Harry) Chao in 2019-2023. I was a visiting student in the Machine Learning Department at Carnegie Mellon University in 2018. During my undergraduate study, I worked with Dr. Shou-De Lin at National Taiwan University and Dr. Chi-Jen Lu at Academia Sinica.
[Google Scholar] [LinkedIn] [CV] (updated on Oct 2024)
Feel free to DM me on LinkedIn
News
[Oct 24] We release CLOC -- CLIP with better localization for MLLMs. Also, check out our new multimodal works: VeCap-v2 and MM1.5
[Aug 24] Check out our recent works on multimodal large language models: Ferret-v2, SlowFast-LLaVA
[Dec 23] Joined Apple AI/ML @ Seattle
[Nov 23] Successfully defended my PhD dissertation
[Sep 23] "Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data" has been accepted to the NeurIPS 2023 main track.
[Apr 23] Graduate Research Award at CSE, OSU.
[Mar 23] Wondering whether to use batch normalization or group normalization in federated learning? Check out our new work on arXiv.
[Feb 23] My work "Train-Once-for-All Personalization" done as a student researcher at Google Research is accepted to CVPR 2023. Thanks to all my advisors!
[Feb 23] I will be interning at Microsoft Research in Redmond for the 2023 summer to work on privacy-protected dataset synthesis via large language models.
[Jan 23] Our paper "On the Importance and Applicability of Pre-Training for Federated Learning" has been accepted to ICLR 2023.
[Jan 23] Received AAAI-2023 travel grant.
Experience
Machine Learning Researcher at Apple AI/ML, Seattle, USA (Dec 2023 - current)
Research Intern at Microsoft Research & Security, Redmond, USA (May 2023 - Aug 2023)
Student Researcher at Google Research, Seattle, USA (May 2022 - Dec 2022)
Research Intern at Google Research, Seattle, USA (remote, May 2021 - Aug 2021)
Research Intern at Google Ads, Mountain View, USA (remote, May 2020 - Aug 2020)
Honors and Service
Top-10% reviewers at ICML 2022, AISTATS 2022
Reviewers at ICML, NeurIPS, ICLR, CVPR, ECCV, TMM, AISTATS, ACL, EMNLP, NAACL
Best student paper at NeurIPS 2020 Workshop on Scalability, Privacy, and Security in Federated Learning
