Wei Guo

About Me

I currently serve as an Applied Scientist at Amazon, where my passion and expertise in safe and trustworthy machine learning. In 2023, I earned my PhD in Computer Science from George Washington University. My doctoral journey was enriched by the guidance and mentorship of Professors Peng Wei and Professor Robert Pless. My research is now dedicated to advancing natural language processing techniques, with a specific focus on enhancing the safety and trustworthiness of machine learning systems.

Research Interests

• Methods: Natural Language Processing, Deep Reinforcement Learning, Multi-agent Reinforcement Learning, Deep Learning, Statistical Machine Learning
• Focused Applications: Trustworthy Natural Langauge Processing, Safety Verification for Deep Reinforcement Learning

News

• [Sept. 2023] Our paper about safety validation on deep reinforcement learning algorithm is accepted to DASC 2023.
• [Sept. 2022] Our paper about explainable deep reinforcement learning is selected as one of the finalists for the best student paper award and won the best of session award in DASC 2022.
• [May 2022] I graduated with a PhD in Computer Science from GWU and will join Amazon as Applied Scientist intern this summer.
• [Apr. 2022] Our paper about explainable deep reinforcement learning is accepted to DASC 2022.
• [July 2021] Our paper about safety enhancement in autonomous separation assurance is accepted to ITSC 2021.
• [Apr. 2021] Our paper about semantic bias in neural language models is accepted to AIES 2021 and selected for the oral presentation.
• [Jan. 2021] Our paper about characterizing biases on Twitter is accepted to ICSC 2021.

Publications

• Safety Validation for Deep Reinforcement Learning Based Aircraft Separation Assurance with Adaptive Stress Testing
  W. Guo, M. Brittain, P. Wei
  42th Digital Avionics Systems Conference. DASC 2023.
  [PDF]

• Explainable Deep Reinforcement Learning for Aircraft Separation Assurance
  W. Guo, P. Wei
  41th Digital Avionics Systems Conference. DASC 2022.
  [PDF] [Slides]

• A Survey of eVTOL Aircraft and AAM Operation Hazards
  E. L. Thompson, A. G. Taye, W. Guo, P. Wei, M. Quinones-Grueiro, I. Ahmed, G. Biswas, J. Quattrociocchi, S. Carr, U. Topcu, J. Jones and M. Brittain
  AIAA AVIATION 2022 Forum.
  [PDF]

• Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance
  W. Guo, M. Brittain, P. Wei
  24th IEEE Intelligent Transportation Systems Conference. ITSC 2021.
  [PDF] [Slides]

• Detecting emergent intersectional biases: Contextualized word embeddings contain a distribution of human-like biases
  W. Guo, A. Caliskan
  4th AAAI/ACM Conference on AI, Ethics, and Society. AIES 2021.
  [PDF] [Code] [Slides] [Presentation] [Poster]

• Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter
  A. Toney, A. Pandey, W. Guo, D. Broniatowski, A. Caliskan
  15th IEEE International Conference on Semantic Computing. ICSC 2021.
  [PDF] [Code]

• Analysis on the Satisfaction of Farmers to the Construction of High Standard Farmland in 12th Five-year: Case of a Town in Shanghai City
  W. Guo, K. Wang
  Journal of Agrotechnical Economics: 39–45, 2016.

Preprints

• Pro-Russian Biases in Anti-Chinese Tweets about the Novel Coronavirus
  A. Toney, A. Pandey, W. Guo, D. Broniatowski, A. Caliskan
  [PDF]

Awards

• Outstanding Undergraduate Graduate Thesis, Shanghai, China, 2016
• Outstanding winner for 17th East China Cup College Students’ Mathematical Modeling Contest, Shanghai, China, 2015
• Scholarship for Academic Excellence, Shanghai, China, 2015

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