Kaylene Stocking

Kaylene Stocking

Ph.D. Student

UC Berkeley


I am a PhD student in the Hybrid Systems Lab at UC Berkeley under the advisorship of Professor Claire Tomlin. My recent research has focused on modeling human behavior, but I am becoming increasingly interested in the intersection between cognitive science and robotics. In addition, I’m broadly interested in how we can design human-technology interfaces that are safe and beneficial on the scale of both individuals and society. I’m especially passionate about ideas that span areas of research that are usually disparate, reflecting my intense general curiosity about how things work (and how we might be able to make them work better).

Outside of research, I love reading, being outdoors, and learning languages, among way too many other miscellaneous hobbies.

Education

  • PhD in Electrical Engineering and Computer Science, Expected 2024

    UC Berkeley

  • BSE in Computer Engineering and Bioengineering, 2019

    University of Pittsburgh

Recent Publications

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From Robot Learning To Robot Understanding: Leveraging Causal Graphical Models For Robotics

Causal graphical models have been proposed as a way to efficiently and explicitly reason about novel situations and the likely outcomes …

Discretizing Dynamics for Maximum Likelihood Constraint Inference

Maximum likelihood constraint inference is a powerful technique for identifying unmodeled constraints that affect the behavior of a …

Maximum Likelihood Constraint Inference from Stochastic Demonstrations

When an expert operates a perilous dynamic system, ideal constraint information is tacitly contained in their demonstrated trajectories …

Recapitulation of human embryonic heart beating to promote differentiation of hepatic endoderm to hepatoblasts

A microfluidic platform recapitulating human embryonic heart beat improves the functionalization state of hepatocytes derived from …

Intracortical Neural Stimulation With Untethered, Ultrasmall Carbon Fiber Electrodes Mediated by the Photoelectric Effect

Objective: Neural stimulation with tethered, electrically activated probes is damaging to neural tissue and lacks good spatial …