Rushi Wang Contact

Hi, I'm Rushi Wang

Floating companion

My research focuses on building human-centered, reliable AI systems that support organizational decision-making and professional workflows in real-world business scenarios. I study how AI tools, agentic assistants, and information systems can be designed, governed, and evaluated to improve decision quality, efficiency, and accountability in high-stakes business settings. To advance this goal, I work at the intersection of (1) AI Security & Safety for LLMs and Agents, (2) Enterprise data analytics for security and risk, and (3) Agentic system design for decision support and workflow automation.

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Selected Publications

Google Scholar →

Please visit my Google Scholar page for a complete list of publications.

Peer-reviewed Publications

RW-Steering Context Control Diagram
EMNLP-2025 AI Safety

Context Engineering for Trustworthiness: Rescorla–Wagner Steering Under Mixed and Inappropriate Contexts

Rushi Wang, Jiateng Liu, Cheng Qian, Yifan Shen, Yanzhou Pan, Zhaozhuo Xu, Ahmed Abbasi, Heng Ji, Denghui Zhang

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP-2025 Main Conference).

AuditBench Financial Statement Analysis Diagram
AAAI-2024 AI for Finance

AuditBench: A Benchmark for Large Language Models in Financial Statement Auditing

Rushi Wang, Jiateng Liu, Weijie Zhao, Shenglan Li, and Denghui Zhang

Proceedings of the AAAI-2024 Workshop on AI for Financial Services.

Contact

Email: rushiw2@illinois.edu · r15990588570@gmail.com