Freda Shi

Freda Shi is an Assistant Professor at the David R. Cheriton School of Computer Science, University of Waterloo, and a Faculty Member at the Vector Institute. She holds a Canada CIFAR AI Chair. Her research focuses on computational linguistics, natural language processing (NLP), and grounded language learning, with emphasis on multilingualism and spatial reasoning in vision-language systems. She earned her Ph.D. in Computer Science from the Toyota Technological Institute at Chicago (2024), advised by Karen Livescu and Kevin Gimpel, supported by a Google Ph.D. Fellowship. Her undergraduate degree is from Peking University (2018), with a minor in Sociology.

Her academic career includes affiliations with the CompLING Lab at Waterloo and contributions to major conferences like ACL and NAACL. She has organized tutorials on NLP grounding and is actively involved in research on model robustness and cognitive insights. Awards include the Google Ph.D. Fellowship and Best Paper Nominations at ACL 2024 and EMNLP 2021, alongside her Thesis of Distinction. She teaches courses such as CS 784 (Computational Linguistics) and CS 486/686 (Artificial Intelligence), emphasizing both theoretical and applied aspects of NLP.

Research trends in her articles highlight advancements in vision-language spatial reasoning, multilingualism, and model interpretability. Her work bridges cognitive science and computational methods, exploring how human language mechanisms inform the design of more trustworthy AI systems.

• Scientific Awards:
  • Google Ph.D. Fellowship
  • Best Paper Nominee (ACL 2024)
  • Best Paper Nominee (EMNLP 2021)
  • Thesis of Distinction (2024)

Advising and Grants: As an advisor, she encourages prospective students to review her guidelines. Her grants include support from the Canada CIFAR AI Chair program and the Vector Institute. She collaborates in labs such as CompLING at Waterloo and co-organizes events at NAACL and ICLR.

Labs/Teams: She leads the CompLING Lab at the University of Waterloo, affiliated with the Vector Institute. Her work integrates interdisciplinary teams focusing on grounded learning and multilingual NLP challenges.