Yuchen Shen

I am a master’s student at the Language Technologies Institute, Carnegie Mellon University. My current research focuses on AI for drug discovery. In particular, I am interested in molecule optimization and designing better neural models for molecules by leveraging their topological structures.

I am fortunate to be working with Professor Barnabás Póczos on generative models for molecules. Additionally, I am interested in optimization and have the privilege of working with Professor Xiaorui Liu on decentralized algorithms.

During my undergraduate years, I concentrated on Natural Language Processing (NLP) and worked on summarization, few-shot sentiment analysis, and chatbots.

Email is the best way to reach me and please feel free to send me an email to discuss research! I try to read all my emails carefully, but don’t hesitate to send another one if you don’t receive my reply after one week!

news

Jan 11, 2024	New website is now live
Aug 29, 2023	Begin to study at CMU
Oct 08, 2022	One paper is accepted by Findings of EMNLP 2022

selected publications

EMNLP

Label-Driven Denoising Framework for Multi-Label Few-Shot Aspect Category Detection

Fei Zhao* , Yuchen Shen* , Zhen Wu , and Xinyu Dai

In Findings of the Association for Computational Linguistics: EMNLP 2022 , Dec 2022

Bib HTML

@inproceedings{zhao-etal-2022-label,
  title = {Label-Driven Denoising Framework for Multi-Label Few-Shot Aspect Category Detection},
  author = {Zhao*, Fei and Shen*, Yuchen and Wu, Zhen and Dai, Xinyu},
  editor = {Goldberg, Yoav and Kozareva, Zornitsa and Zhang, Yue},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2022},
  month = dec,
  year = {2022},
  address = {Abu Dhabi, United Arab Emirates},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2022.findings-emnlp.177},
  doi = {10.18653/v1/2022.findings-emnlp.177},
  pages = {2390--2402},
}