Colloquium
MAE Baetjer Colloquium - Safe Learning in Control
In many applications of autonomy in robotics, guarantees that constraints are satisfied throughout the learning process are paramount. We present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory.
BioE Colloquium: Machine learning for discovery: Deciphering the logic of RNA
To request disability-related accommodations, please contact Jessica Varela at jv2026@princeton.edu no later than three working days prior to the event.
The Role of Archaic Admixture in Human Evolution
Over the past decade, the ability to sequence genomes from both present-day and archaic humans (including our closest evolutionary relatives, the Neanderthals) has transformed our understanding of human history.
Dialog with Robots: Perceptually Grounded Communication with Lifelong Learning
Developing robots that can accept instructions from and collaborate with human users is greatly enhanced by an ability to engage in natural language dialog. Unlike most other dialog scenarios, this requires grounding the semantic analysis of language in perception and action in the world.
Graduate Certificate in Computational Science & Engineering Colloquium
One of the graduate certificate requirements is for students to give a seminar on their dissertation research before graduation, typically in the last year once significant results can be reported.
JAX: Accelerated machine learning research via composable function transformations in Python
JAX is a system for high-performance machine learning research. It offers the familiarity of Python+NumPy and the speed of hardware accelerators, and it enables the definition and the composition of function transformations useful for machine learning programs.