Tejas Anand: Waterloo Engineering, AI Agent Evaluation (NVIDIA, ICML ‘26)

Hi! I’m Tejas, a Computer Engineering student at Waterloo and a research engineer at NVIDIA, where I work on post-training: fine-tuning, synthetic data, and agents.

A couple of highlights:

• AEVAL (ICML 2026): I led our work on making AI agents stop grading their own homework, so agent testing becomes deterministic.

• Data Efficient Fine Tuning: I worked on a loop that finds where a vision model fails and fixes it with targeted real and synthetic data. It matches full-data fine-tuning on a fraction of the data, and it’s open source in NVIDIA’s TAO skill bank.

Always happy to chat about post-training, agents, or evals!