Hi! I am Jennifer. I am a graduate student at Yale University. Before coming to Yale,I obtained my BASc in Engineering Science at University of Toronto. I was fortunate to be guided by Professor Julian McAuley, Professor Han Liu, and Professor William Cunningham on various research projects.

My research interests lie in the intersection of large foundation models, agentic systems, and multimodal models. I am particularly interested in
1. understanding the capabilities of large foundation models,
2. developing and applying agentic systems for various applications,
3. exploring the potential of multimodal models for complex tasks.
I am also passionate about exploring the societal implications of AI and developing responsible AI technologies.

In my free time, I enjoy outdoor activities and all kinds of sports. I love exploring new technologies: you can see my blog posts here. If you would love to have a chat, feel free to shoot me an email!

Jennifer Zhang
Email GitHub LinkedIn Scholar

Selected Work

For a complete list of my publications, please visit my Google Scholar.

In-Context Algorithm Emulation in Fixed-Weight Transformers

J. Y.-C. Hu*, Hude Liu*, J. Y. Zhang*, Han Liu
ICLR 2026. * Equal contribution.

SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes

C. Wang*, X. Li*, J. Y. Zhang, J. Wu, C. Huang, L. Yao, J. McAuley, J. Shang
ACL 2026.

WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization

G. Mundada, Z. Huang, R. Surana, S. Yu, J. Y. Zhang, X. Li, T. Yu, L. Yao, J. Shang, J. McAuley, J. Wu
ICML 2026.

Experience

May 2026 - Aug 2026

Machine Learning Researcher

RBC Borealis

#Research

Sep 2024 - May 2025

Total Fund Risk Analyst Intern

Ontario Teachers' Pension Plan

  • Researched and implemented LLM multi-agent systems for chatbot question-answering with in-house large financial datasets.
  • Enhanced and maintained the risk calculation pipeline across data extraction, scenario generation, calculation, and dashboarding.

#Langchain #Python #SQL #Julia #C# #Flask

May 2024 - Aug 2024

Business Analyst Intern

EQ Bank

  • Analyzed the bank's financial reconciliation process and identified major workflow bottlenecks and inefficiencies.
  • Developed an automated reconciliation system for financial reporting, reducing manual work and operational error.
  • Designed and implemented an ETL pipeline for financial data, improving consistency and reducing redundancy by 30%.

#Python #SQL #Tableau #VBA #Excel

May 2023 - Dec 2023

Data Engineering Intern

National Research Council Canada

  • Processed and analyzed large-scale geographical data to investigate factors contributing to fire incidents along railroads.
  • Developed and compared machine learning models to predict active fire locations, achieving an accuracy of 89%.
  • Created an interactive Tableau dashboard to visualize predicted high-risk fire areas along railroad routes for preventive planning.
  • Collaborated across teams to integrate machine learning models into the existing data pipeline and improve processing efficiency.

#scikit-learn #Optuna #GeoPandas #Python #C# #Tableau #SQL

Sunflower