PeopleofSuperintelligence

Researcher

Freda Shi

Also known as Haoyue Shi, 石昊悦

Freda Shi is a computer scientist whose work links language learning with vision, program execution and multilingual grounding. She earned a bachelor's degree in Intelligence Science and Technology at Peking University in 2018 and completed a computer science PhD at Toyota Technological Institute at Chicago in 2024, where her thesis received a Thesis of Distinction. Her work includes the 2021 G2L2 system for grounded meaning and a 2022 method that uses program execution to select generated code. She coauthored a 2025 NAACL tutorial on learning language through grounding and a 2026 study of symbol grounding inside language models. As of October 2026, she is an Assistant Professor at Waterloo, a Vector Institute faculty member, and a Canada CIFAR AI Chair.

Timeline

  1. 2018

    A degree at Peking University

    She earns a bachelor's degree in Intelligence Science and Technology at Peking University in 2018, with a minor in Sociology.

  2. 2021

    G2L2 and a Google fellowship

    In 2021, she receives a Google PhD Fellowship in Natural Language Processing for a proposal about learning language structures through grounding signals. With Jiayuan Mao and other collaborators, she coauthors the NeurIPS paper “Grammar-Based Grounded Lexicon Learning,” which learns compositional meaning representations from paired images and texts.

  3. 2022

    Execution-based code translation

    In 2022, she coauthors the EMNLP paper “Natural Language to Code Translation with Execution,” which introduces MBR-EXEC, a method that selects generated code by comparing candidate programs' execution results.

  4. 2024

    A TTIC doctorate

    She completes a computer science PhD at Toyota Technological Institute at Chicago in 2024 under Karen Livescu and Kevin Gimpel, and her thesis “Learning Language Structures through Grounding” receives TTIC's Thesis of Distinction. Its methods use vision, program execution and annotations in other languages as supervision for learning language structures.

  5. July 2024–September 2024

    Waterloo and Vector appointments

    In July 2024, she joins the Cheriton School of Computer Science at the University of Waterloo as a tenure-track Assistant Professor. In September 2024, she becomes a Canada CIFAR AI Chair and a faculty member at the Vector Institute.

  6. 2025

    Learning language through grounding

    At NAACL 2025, she coauthors the tutorial “Learning Language through Grounding,” which surveys research on learning lexical semantics, syntax and complex meanings through grounding.

  7. 2026

    Symbol grounding in language models

    In 2026, she coauthors the ICML paper “The Mechanistic Emergence of Symbol Grounding in Language Models.” Its analysis finds grounding concentrated in middle-layer computations, where attention heads aggregate environmental grounds to predict linguistic forms.

  8. As of October 2026

    Waterloo and Vector faculty

    She is an Assistant Professor in Waterloo's Cheriton School of Computer Science, a Faculty Member at the Vector Institute, and a Canada CIFAR AI Chair.

Career

  1. Since 2024University of WaterlooAssistant Professor
  2. Since 2024Vector InstituteFaculty Member

Education

  1. 2024Toyota Technological Institute at ChicagoPhD
  2. 2018Peking UniversityBachelor's degree

From the biography.

  1. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Vector Institute. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  2. Nonprofit roles are 2.3 times as common in AI safetyIncludes Vector Institute. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.
  3. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Vector Institute. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.
  4. The United States employs an estimated 48% of people shaping AIIncludes Vector Institute. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Freda Shi yet. Send us a free-licensed photo.

  1. Freda Shi cs.uwaterloo.ca. Checked 21 October 2026.
  2. TTIC News ttic.edu. Checked 21 October 2026.
  3. Grammar-Based Grounded Lexicon Learning papers.nips.cc. Checked 21 October 2026.
  4. Natural Language to Code Translation with Execution - ACL Anthology aclanthology.org. Checked 21 October 2026.
  5. TTIC Freda Shi - Student Alumni Highlight ttic.edu. Checked 21 October 2026.
  6. Learning Language Structures through Grounding arxiv.org. Checked 21 October 2026.
  7. Meet Freda Shi, a computer scientist who advances grounded language learning and computational linguistics cs.uwaterloo.ca. Checked 21 October 2026.
  8. Freda Shi - ACL Anthology aclanthology.org. Checked 21 October 2026.
  9. The Mechanistic Emergence of Symbol Grounding in Language Models proceedings.mlr.press. Checked 21 October 2026.
  10. Freda Shi - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.