Recap: AI Planning & Human-Aware Systems Research Forum

We kicked off Spring 2026 with a packed house and a deep dive into the future of autonomy.
The highlight?
Prof. Siddharth Srivastava taking us under the hood of Human-Aware AI Planning.
The industry is moving past simple automation.
We are entering an era where robots need to explain themselves.
Here are the critical takeaways from the session:

1. “Be Wise, Generalize”
If you train a robot to pick up a mug, it usually memorizes the motor trajectory. Move the mug 5cm? The robot fails. Prof. Srivastava showed us that true autonomy requires learning the concept of the task, not just the motion.

2. The Evaluation Gap
How do you trust a robot in your house without it setting the kitchen on fire? You can’t run a million physical tests. We learned about AutoEval systems that can predict failure modes and success rates without needing dangerous real-world trials.

3. Interpretability is Safety
When a robot fails to pick up a “blue key” because it’s in a slightly different spot, does it know why? We discussed frameworks like JEDAI that help everyday users understand (and trust) what a black-box AI is actually thinking.

4. The Future is Hybrid
Pure deep learning has limits. Pure symbolic logic is too rigid. The breakthrough lies in combining them. Robots need to learn the language of a task to create their own training data.

Thank you to Prof. Srivastava for the incredible roadmap and for staying late to answer every single student question.
Thank you to every student who showed up ready to bridge the gap between textbook theory and real-world execution.
This is going to be a massive semester.

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