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Intentional Formation of Persistent Surface Redox Mediators by Adsorption of Polyconjugated Carbonyl Complexes to Pd Nanoparticles

https://doi.org/10.1021/jacs.4c15874

Adams, Jason_S; Tanwar, Mayank; Chen, Haoyu; Vijayaraghavan, Sucharita; Ricciardulli, Tomas; Neurock, Matthew; Flaherty, David_W (April 2025, Journal of the American Chemical Society)
Minimizing Human Labor for In-the-Wild Camera Trap Processing Pipeline

https://doi.org/10.1109/MMSP61759.2024.10743995

Chen, Haoyu; Reibman, Amy R (October 2024, IEEE)

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Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning

https://doi.org/10.1145/3610977.3634984

Trinh, Tu; Chen, Haoyu; Brown, Daniel S (March 2024, ACM)

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Largest Angle Path Distance for Multi-Manifold Clustering

https://doi.org/10.1109/SampTA59647.2023.10301401

Chen, Haoyu; Little, Anna; Narayan, Akil (July 2023, International Conference on Sampling Theory and Applications)

We propose a novel, angle-based path metric for the multi-manifold clustering problem. This metric, which we call the largest-angle path distance (LAPD), is computed as a bottleneck path distance in a graph constructed on d-simplices of data points. When data is sampled from a collection of d-dimensional manifolds which may intersect, the method can cluster the manifolds with high accuracy and automatically detect how many manifolds are present. By leveraging fast approximation schemes for bottleneck distance, this method exhibits quasi-linear computational complexity in the number of data points. In addition to being highly scalable, the method outperforms existing algorithms in numerous numerical experiments on intersecting manifolds, and exhibits robustness with respect to noise and curvature in the data.
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Dynamic mechanical properties and σ precipitates strengthening of a NiCrFeCoMo0.2 high-entropy alloy additively manufactured by selective laser melting

https://doi.org/10.1016/j.jallcom.2023.172244

Huang, Yiyu; Li, Wenshu; Liu, Ruoyu; Chen, Haoyu; Wu, Qi; Wei, Shaohong; Liu, Bin; Liaw, Peter K.; Wang, Bingfeng (December 2023, Journal of Alloys and Compounds)

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