Princeton University — CS Research

Computer science research from Princeton University, including algorithms, theory, networks, and security.

Sample of the collection (25 of 2,681 items)

• Aerodynamic Mechanisms and Flow Physics of Bioinspired Slotted Wingtips Princeton University Bird wings contain several feather groups, some of which contribute to their aerodynamic performance during flight. One of these groups…
• Shape optimization of box-type structures under waves using multi-objective Bayesian Optimization: Reducing wave loads and improving wave attenuation Princeton University Box-type structures are widely used as coastal infrastructure - including protective structures, like box-type breakwaters, providing…
• Towards grounded autonomous research: an end-to-end LLM mini research loop on published computational physics Princeton University Recent autonomous LLM agents have demonstrated end-to-end automation of machine-learning research. Real-world physical science is…
• Reinforcement Learning, Optimal Control, and Bayesian Filtering in Data Assimilation Princeton University We give a finite-horizon variational formulation that places Bayesian filtering and smoothing, variational data assimilation,…
• The Augmented Undercommons: A Framework for Liberatory HCI Research within Ethically Compromised Institutions University of California, Santa Barbara Sociocultural engineering research is being systematically attacked under the current US government, pressuring researchers to eliminate…
• Developing disruption avoidance functions for the ITER plasma control system ITER Abstract Disruption avoidance is a key facet of the overall task to manage tokamak disruptions. This paper defines the disruption…
• A Multi-Institutional Digital Twin and AI Educational Platform for Advanced Microelectronics Fabrication and Device Packaging Training University of California, Irvine Technology today is at a crossroad between Industry 4.0 and 5.0, where products and services are manufactured and designed to be…
• Minimizing Data Requirements for Material Property Prediction via Cluster-based Training Set Selection Princeton University Machine learning (ML) is increasingly employed to predict material properties, and when data are scarce, data acquisition is often…
• Digital Actuation Control of Soft Robotic Origami With Self‐Folding Liquid Crystal Elastomer Hinges Princeton University ABSTRACT Soft robotics has sought to integrate seamless, programmable shape morphing into dynamic, complex structures. We present a…
• The edge is already there: Experimental insights into the origins of stone tool technology Appalachian State University • Natural edges may have served as precursors to manufactured sharp edges. • Free-hand percussion required incremental technical…
• Accurately and Efficiently Predicting High-Resolution Inundation using a Hybrid Machine Learning and Physics-Based Approach Princeton University Predicting high-resolution inundation at large spatial and temporal scales is important in understanding future water availability and…
• Advancing integrated continental-scale hydrologic forecasting through democratized data and ML-accelerated modeling Princeton University Today water and resource managers face a significant challenge managing systems that are rapidly evolving in a warming climate, where…
• Large-domain transferability of machine learning metamodels for predicting water transit time to baseflow National University of Singapore Transit time to baseflow refers to the amount of time between when a water parcel enters a catchment as precipitation and when it exits…
• Learning, creating, and sharing: A science communication framework for water and climate education Princeton University Since 2015, the Integrated GroundWater Modeling Center has engaged diverse audiences in water and climate science through community…
• Coupling techniques in the new high-resolution SHiELD: implicit land-atmosphere coupling. Princeton University As part of the development of GFDL’s new high resolution, seamless weather to S2S to climate timescale coupled model, we present the…
• Robust Software for the Modeling of Spatial Random Fields across Geoscience Disciplines Princeton University We have developed theory, algorithmic tools, and two software suites (written in MATLAB and Python) that are openly available for use by…
• Wigglers and the Willing:  A Within-Subject Analysis of Inequality Concerns Mariana Blanco et al. People make pro-social choices, yet researchers still lack tools to quantify how much moral wiggle room individuals exploit or how…
• Cognitive capacity and control in the evolution of intelligence Princeton University A diversity of intelligences arises from the constraints under which animals evolve. However, characterizing how constraints shape…
• Cognitive Constraints and Reward Environments Jointly Shape Memory Formation Si Ma et al. A key adaptive feature of human episodic memory is its ability to selectively encode important information. While extensive empirical…
• SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction Marshall Space Flight Center This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory…
• Quantifying the Impact of Sampling Error in Composite Index Construction Princeton University Composite indicators are widely used to assess multifaceted phenomena; however, they rarely account for the uncertainty inherent in…
• Uncertainty-Aware Grid Planning in the Real World: A Method Enabling Large-Scale, Two-Stage Adaptive Robust Optimization for Capacity Expansion Planning Princeton University Capacity expansion models are frequently used to inform multi-billion dollar grid infrastructure decisions, a context in which there is…
• Exploring the Relationship Between Plan Features and Argument Essay Performance Princeton University We conducted a post hoc analysis of 771 students’ argumentative writing plans and essays in the Criterion ® database, a digital writing…
• Proposing PaFRIA: A Participatory Fundamental Rights Impact Assessment Process Aligned with the EU AI Act for High-Risk AI System Deployers Chiara Ullstein et al. Assessing the impact of AI systems on fundamental rights (FRIA) is a core obligation under the EU AI Act for certain high-risk AI system…
• Investigating High School Students' Code Comprehension and Strategy Use Across Block-Based and Text-Based Programming University of Florida Understanding how students comprehend code is essential for designing effective instructional support in computer science (CS). While…

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