Nora Chen

I am a senior undergraduate student at the University of California San Diego majoring in Cognitive Science and specializing in Language and Culture.

Research: I am broadly interested in exploring the cognitive underpinnings that allow people to understand and make fast, robust inferences about diverse, unknown physical phenomena. To facilitate these capabilities, I research how latent physical properties can be inferred from observed data and how humans use this information to improve predictive models of the world. Through this, I aim to shed light on the cognitive processes enabling robust inferential performance and inform the design of artificial intelligence systems that are better equipped to cope with the dynamic, uncertain nature of the physical world and more attuned to its nuanced complexities. (cont.)

Previously, I was an undergraduate research assistant in the Cognitive Tools Lab, advised by Dr. Judith Fan (Stanford).

Currently, I reside as a Research Fellow at Harvard University in the Computation, Cognition, and Development (Ullman) Lab.

This summer, I will join the Cognitive Development and Learning (Gopnik) Lab at UC Berkeley as a Research Intern.

GitHub / Email / CV / Google Scholar / LinkedIn

Publications 


Physical Intuition and the Role of Counterfactual Reasoning: Insights from Jenga and Fluid Dynamics Simulations

[PDF]

We show that people can use counterfactual reasoning to make inferences about the physical world, even when kinetic information is degraded. Furthermore, we extend and focus on the specific physical properties that lead people to determine the viscosity of a liquid in our three fluid simulations. 

The Role of Perception in Language Comprehension 

[Psyarxiv]

In this paper,  I show that the motor system plays a vital role in understanding language, suggest that the motor system may be necessary for understanding language in general and not just for specific tasks or language phenomena, and conclude by discussing the implications of this research for our understanding of language and cognition.

Behind Clubhouse’s Trajectory and Phenom

[Preprint]

In this paper, I explore Clubhouse's model and market trajectory, examining exclusivity and celebrity impact on user engagement and platform sustainability. This analysis seeks to elucidate the dynamics influencing the rise and decline of audio-based social media within the digital landscape.

Conferences

N. Chen, E. Cain, and R. Ryskin. Meaning Representations Across Life Span. Poster presentation to be delivered at the 2022 UROC Annual Undergraduate Research Symposium, Merced, CA, August 2022. Poster Info

N. Chen, D. Richardson, and E. Isbell. Identifying eye movements in pediatric electroencephalogram (EEG): A machine learning approach. Cognitive Neuroscience Society. Poster presentation delivered at the Cognitive Neuroscience Society conference, San Francisco, CA, April 2022. 

Talks/Presentations:

The Risks of Fast-Paced Deployments of Large AI Models


How well can models emulate people’s ability to infer the physical properties of objects?


Learning World Models For Physical Interactions

Writing:

AI Governance


Combating Bias in AI-Driven Healthcare

Highlighted Projects:

Edge Write:

Edge Write is a digital platform that enhances productivity by utilizing text obfuscation and content elimination to emphasize continuous engagement: https://edgewrite.xyz et. EdgeWrite.AI: https://ewai.dreamhosters.com/


(More projects in Other)