My name is Chenghao Yang. I am currently an applied scientist at AWS AI, under the lead of Andrew O. Arnold.

I also worked as unpaid part-time RAs at Johns Hopkins University (advised by Prof. Jason Eisner). I keep close connections with Prof. Smaranda Muresan at Columbia University, Prof. Zhiyuan Liu at Tsinghua University and Dr. Mo Yu at IBM Research.

Before I join AWS, I obtained my M.S. degree in Computer Science Department at Columbia University (ML track) and my bachelor's degree in Software College, Beihang University.

My research interest focuses on natural language processing (NLP), knowledge graph (KG), and information retrieval (IR). My goal is to design practical NLP systems as well as understand the underlying human intelligence behind the natural language. Recently, I worked on word-level semantics, robustness, Question-Answering and continuous-time event stream modeling.

I enjoy listening to music, playing the guitar, watching the movie, and the anime in my personal spare time. I recently become fascinated by cooking Chinese dishes.

Personal News

  • [Jan, 2022] Excited to share that my work collaborated with Prof. Jason Eisner and Prof. Hongyuan Mei has been accepted to ICLR 2022! It mainly focuses on building a neural-symbolic hybrids based on Transformer architecture and can be used for event stream modeling. Please take a look at our full paper and our codebase!
  • [Oct, 2021] Officially be invited to serve as reviewers for ACL Rolling Reviews. Will work on September (as emergency), October and November.
  • [June, 2021] Officially join AWS AI as an applied scientist intern. Looking forward to explore Robustness + QA project! Feel free to reach out if you are also at AWS!
  • [May, 2021] Three Important News:
    • My TACL paper on NarrativeQA has been officially accepted by TACL (work done during my internship at IBM). Thanks to my great mentor Mo Yu and co-authors!
    • My paper on suicide risk assessment has been accepted to ACL 2021 as a short paper! Thanks to my great advisor Smara and my supportive co-author Yudong!
    • Also, our colaboration works with Columbia School of Social Work on COVID-19 social media analysis has also been officially accepted by Journal of Addiction Medicine Production. Thanks to all great collaborators! Very excited to contribute my efforts on COVID-19 related researches.
  • [April, 2021] Officially graduated with a Master's degree in Computer Science from Columbia. Thanks to my great research advisor Smaranda Muresan, my awesome and patient lecturers and TAs and thanks for the accompany of my classmates!
  • [Oct, 2020] I will start my visiting research assistant at JHU CLSP during Spring 2021. I will work with Prof. Jason Eisner and his PhD advisee Hongyuan Mei on a remote basis.
  • [Jun, 2020] I start my internship at IBM Watson as a Sr. Cognitive Software Developer. I will work with Dr. Mo Yu on NarrativeQA projects. Feel free to connect if you are also at IBM!
  • [Jan, 2020] I start working as a Research Assistant at Columbia University, working with Prof. Smaranda Muresan on the topic of NLP for health and social good.
  • [Dec, 2019] I finished my visiting at Tsinghua University as a Visiting Student Research Assistant. Great thanks for my advisor Prof. Zhiyuan Liu and my great collaborators Hao Zhu, Ruobin Xie, Fanchao Qi, Yuan Zang and Junjie Huang.

Publication

(“*” indicates equal contribution)

Journal Papers

  1. Chenghao Yang*, Xiangyang Mou*, Mo Yu*, Bingsheng Yao, Xiaoxiao Guo, Saloni Potdar, Hui Su., Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study TACL 2021 [paper]
  2. Nabila El-Bassel, Karli R Hochstatter, Melissa Slavin, Chenghao Yang*, Yudong Zhang*, Smaranda Muresan., Harnessing the Power of Social Media to Understand the Impact of COVID-19 on People Who Use Drugs During Lockdown and Social Distancing. Journal of Addiction Medicine

Conference Papers

  1. Chenghao Yang, Hongyuan Mei, Jason Eisner., Transformer Embeddings of Irregularly Spaced Events and Their Participants, ICLR 2022 [full paper] [codebase]
  2. Chenghao Yang, Yudong Zhang, Smaranda Muresan., Weakly-Supervised Methods for Suicide Risk Assessment: Role of Related Domains, ACL 2021 (Short) [paper] [codebase]
  3. Chenghao Yang*, Yuan Zang*, Fanchao Qi*, Zhiyuan Liu, Meng Zhang, Qun Liu, Maosong Sun., Word-level Textual Adversarial Attacking as Combinatorial Optimization, ACL 2020 (Long) [paper] [codebase]
  4. Fanchao Qi*, Junjie Huang*, Chenghao Yang, Zhiyuan Liu et al., Modeling Semantic Compositionality with Sememe Knowledge, ACL 2019 (Long & Oral) [paper] [codebase]

Workshop Papers

  1. Chenghao Yang*, Yuhui Zhang*, Zhengping Zhou*, Zhiyuan Liu., Enhancing Transformer with Sememe Knowledge, RepL4NLP@ACL 2020 [paper]
  2. Xiangyang Mou, Mo Yu, Bingsheng Yao, Chenghao Yang, Xiaoxiao Guo, Saloni Potdar, Hui Su., Frustratingly Hard Evidence Retrieval for QA Over Books, NUSE@ACL 2020 [paper]

Service

  • ARR Reviewer: {Sept, Oct, Nov} 2021
  • Reviewer: EMNLP 2021, ACL 2021, NAACL 2021, ACL 2020, COLING 2020, NLPCC 2020