Xin Chen, Cynthia

Xin Chen, Cynthia

Hi! I’m currently a Direct PhD student at ETH Zurich, supervised by Prof. Andreas Krause. I am deeply passionate about developing AI solutions that are beneficial to society and align with human values. I previously graduated from The University of Hong Kong, and I also spent some time at UC Berkeley (Center for Human-Compatible AI), Stanford University and Columbia University prior to ETH. You can call me Cynthia or Chen Xin (陈欣). My current research interests span across:

  • Improving robustness and reliability in decision making algorithms (reinforcement learning / imitation learning),
  • Learning the right human preferences/intentions, and
  • Representation learning.

I am grateful to be supported by the Open Phil AI Fellowship and the Vitalik Buterin PhD Fellowship for my research.

To help with growing the AI alignment research field, I am among the main organizers of SafeAI workshop at AAAI and AISafety workshop at IJCAI. The best way to reach me is through my email chexin AT ethz.ch.

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I was previously supported by the HKU Foundation Scholarship for my undergrad studies (ranked top 0.02% in Chinese National College Entrance Exam, Gaokao). Out of my concern for poverty, animal, and climate change, I donate a considerable portion of my income to the most effective charities every year. I enjoy reading, playing the piano, and marathon running outside of my academic pursuits.

Recent Publications

Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture Search (CVPR2022)

Minbin Huang, Zhijian Huang, Changlin Li, Xin Chen, Hang Xu, Zhenguo Li, Xiaodan Liang

[Paper]

An Empirical Investigation of Representation Learning for Imitation (NeurIPS2021) Undergraduate thesis

Xin Chen*, Sam Toyer*, Cody Wild*, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah

[Paper] [Code] [Talk]


Exploring Geometry-aware Contrast and Clustering Harmonization for Self-supervised 3D Object Detection (ICCV2021)

Hanxue Liang*, Dapeng Feng*, ChenHan Jiang, Xin Chen, Hang Xu, Xiaodan Liang, Zhenguo Li, Wei Zhang, Luc Van Gool

[Paper]


TransNAS-Bench-101: Improving transferability and Generalizability of Cross-Task Neural Architecture Search (CVPR2021)

Yawen Duan*, Xin Chen*, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li

[Paper] [Benchmark]


CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search (ECCV2020)

Xin Chen*, Yawen Duan*, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li

[Paper] [Website]

Blog Posts

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