Feasibility of Computational Estimation of Task-Oriented Visual Attention. - Yorie Nakahira; Minoru Nakayama (AUIC, 2012)

Computational Model for Probability Prediction of Scan Paths in Static Scenes. - Yorie Nakahira; Minoru Nakayama (VISAPP (1), 2012)

Dynamic state estimation in the presence of compromised sensory data. - Yorie Nakahira; Yilin Mo (CDC, 2015)

Hard limits on robust control over delayed and quantized communication channels with applications to sensorimotor control. - Yorie Nakahira; Nikolai Matni; John C. Doyle 001 (CDC, 2015)

Teaching control theory in high school. - John Doyle 001; Yorie Nakahira; Yoke Peng Leong; Emily Jenson; Adam Dai; Dimitar Ho; Nikolai Matni (CDC, 2016)

LQ vs. ℓ∞ in controller design for systems with delay and quantization. - Yorie Nakahira (CDC, 2016)

Algorithms for optimal control with fixed-rate feedback. - Anatoly Khina; Yorie Nakahira; Yu Su 001; Babak Hassibi (CDC, 2017)

Smoothed Least-laxity-first Algorithm for EV Charging. - Yorie Nakahira; Niangjun Chen; Lijun Chen 001; Steven H. Low (e-Energy, 2017)

Electric vehicle charging: a queueing approach. - Angelos Aveklouris; Yorie Nakahira; Maria Vlasiou; Bert Zwart (SIGMETRICS Perform. Evaluation Rev., 2017)

Fundamental limits and achievable performance in biomolecular control. - Yorie Nakahira; Fangzhou Xiao; Victoria Kostina; John C. Doyle 001 (ACC, 2018)

Algorithms for Optimal Control with Fixed-Rate Feedback. - Anatoly Khina; Yorie Nakahira; Yu Su 001; Hikmet Yildiz; Babak Hassibi (CoRR, 2018)

Minimal-variance distributed scheduling under strict demands and deadlines. - Yorie Nakahira; Andrés Ferragut; Adam Wierman (SIGMETRICS Perform. Evaluation Rev., 2018)

Minimal-Variance Distributed Deadline Scheduling in a Stationary Environment. - Yorie Nakahira; Andrés Ferragut; Adam Wierman (SIGMETRICS Perform. Evaluation Rev., 2018)

Attack-Resilient ℋ2, ℋ∩, and ℓ1 State Estimator. - Yorie Nakahira; Yilin Mo (IEEE Trans. Autom. Control., 2018)

Experimental and educational platforms for studying architecture and tradeoffs in human sensorimotor control. - Quanying Liu; Yorie Nakahira; Ahkeel Mohideen; Adam Dai; Sunghoon Choi; Angelina Pan; Dimitar Ho; John C. Doyle 001 (ACC, 2019)

Theoretical foundations for layered architectures and speed-accuracy tradeoffs in sensorimotor control. - Yorie Nakahira; Quanying Liu; Natalie Bernat; Terrence J. Sejnowski; John Doyle 001 (ACC, 2019)

Fitts' Law for speed-accuracy trade-off is a diversity sweet spot in sensorimotor control. - Yorie Nakahira; Quanying Liu; Terrence J. Sejnowski; John C. Doyle 001 (CoRR, 2019)

Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control. - Yorie Nakahira; Quanying Liu; Terrence J. Sejnowski; John C. Doyle 001 (CoRR, 2019)

An Integrative Perspective to LQ and $ ell _ infty$ Control for Delayed and Quantized Systems. - Yorie Nakahira; Lijun Chen 001 (IEEE Trans. Autom. Control., 2020)

Safe Control in the Presence of Stochastic Uncertainties. - Albert Chern; Xiang Wang; Abhiram Iyer; Yorie Nakahira (CDC, 2021)

Axon Arbor Trade-off Between Wiring Cost, Delay, and Synchronization in Neuronal Networks. - Quanying Liu; Christian Kurniawan; Chenxi Xu; Siddhant Jagtap; Xiyu Deng; Kexin Lou; Yong Sheng Soh; Yorie Nakahira (CISS, 2021)

Smoothed Least-Laxity-First Algorithm for EV Charging. - Niangjun Chen; Christian Kurniawan; Yorie Nakahira; Lijun Chen 001; Steven H. Low (CoRR, 2021)

Myopically Verifiable Probabilistic Certificate for Long-term Safety. - Zhuoyuan Wang; Haoming Jing; Christian Kurniawan; Albert Chern; Yorie Nakahira (ACC, 2022)

Probabilistic Safety Certificate for Multi-agent Systems. - Haoming Jing; Yorie Nakahira (CDC, 2022)

Adaptive Safe Control for Driving in Uncertain Environments. - Siddharth Gangadhar; Zhuoyuan Wang; Haoming Jing; Yorie Nakahira (IV, 2022)

Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis With Resource Augmentation. - Niangjun Chen; Christian Kurniawan; Yorie Nakahira; Lijun Chen 001; Steven H. Low (IEEE Trans. Smart Grid, 2022)

Rethinking Safe Control in the Presence of Self-Seeking Humans. - Zixuan Zhang; Maitham Al-Sunni; Haoming Jing; Hirokazu Shirado; Yorie Nakahira (AAAI, 2023)

Bayesian Network-Based Probabilistic Constraints for Safe Autonomous Driving in Occlusion Environments. - Naoya Yamada; Kohei Honda 002; Hiroyuki Okuda; Tatsuya Suzuki 001; Yorie Nakahira (ITSC, 2023)

A Learning and Control Perspective for Microfinance. - Xiyu Deng; Christian Kurniawan; Adhiraj Chakraborty; Assane Gueye; Niangjun Chen; Yorie Nakahira (L4DC, 2023)

A Generalizable Physics-informed Learning Framework for Risk Probability Estimation. - Zhuoyuan Wang; Yorie Nakahira (L4DC, 2023)

Scalable Long-Term Safety Certificate for Large-Scale Systems. - Kenta Hoshino; Zhuoyuan Wang; Yorie Nakahira (IEEE Control. Syst. Lett., 2023)

Research Challenges for Energy-Efficient Computing in Automated Vehicles. - Robert P. Dick; Rob Aitken; Jace Mogill; John Paul Strachan; Kirk Bresniker; Wei Lu 003; Yorie Nakahira; Zhiyong Li; Matthew J. Marinella; William Severa; A. Alec Talin; Craig M. Vineyard; et al. (Computer, 2023)

Generalized Exact Scheduling: A Minimal-Variance Distributed Deadline Scheduler. - Yorie Nakahira; Andrés Ferragut; Adam Wierman (Oper. Res., 2023)

Physics-Informed Representation and Learning: Control and Risk Quantification. - Zhuoyuan Wang; Reece Keller; Xiyu Deng; Kenta Hoshino; Takashi Tanaka; Yorie Nakahira (AAAI, 2024)

An Analytic Solution to Covariance Propagation in Neural Networks. - Oren Wright; Yorie Nakahira; José M. F. Moura (AISTATS, 2024)

Physics-informed RL for Maximal Safety Probability Estimation. - Hikaru Hoshino; Yorie Nakahira (ACC, 2024)

Towards Proactive Safe Human-Robot Collaborations via Data-Efficient Conditional Behavior Prediction. - Ravi Pandya; Zhuoyuan Wang; Yorie Nakahira; Changliu Liu (ICRA, 2024)

Autonomous Drifting Based on Maximal Safety Probability Learning. - Hikaru Hoshino; Jiaxing Li; Arnav Menon; John M. Dolan; Yorie Nakahira (ITSC, 2024)

Sample-Optimal Zero-Violation Safety For Continuous Control. - Ritabrata Ray; Yorie Nakahira; Soummya Kar (CoRR, 2024)

Context-aware LLM-based Safe Control Against Latent Risks. - Quan Khanh Luu; Xiyu Deng; Anh Van Ho; Yorie Nakahira (CoRR, 2024)

Myopically Verifiable Probabilistic Certificates for Safe Control and Learning. - Zhuoyuan Wang; Haoming Jing; Christian Kurniawan; Albert Chern; Yorie Nakahira (CoRR, 2024)

Generalizable Physics-Informed Learning for Stochastic Safety-Critical Systems. - Zhuoyuan Wang; Albert Chern; Yorie Nakahira (CoRR, 2024)

Orthogonal Modal Representation in Long-Term Risk Quantification for Dynamic Multi-Agent Systems. - Ryoma Yasunaga; Yorie Nakahira; Yutaka Hori (IEEE Control. Syst. Lett., 2024)

Fast Bandit-based Policy Adaptation in Diverse Environments. - Ziyi Zhang; Guannan Qu; Yorie Nakahira (ACC, 2025)

Learning to Stabilize Unknown LTI Systems on a Single Trajectory under Stochastic Noise. - Ziyi Zhang; Yorie Nakahira; Guannan Qu (UAI, 2025)

Predictive Control and Regret Analysis of Non-Stationary MDP with Look-ahead Information. - Ziyi Zhang; Yorie Nakahira; Guannan Qu (Trans. Mach. Learn. Res., 2025)

Stabilizing Linear Systems under Partial Observability: Sample Complexity and Fundamental Limits. - Ziyi Zhang; Yorie Nakahira; Guannan Qu (CoRR, 2025)

Physics-Informed Deep B-Spline Networks for Dynamical Systems. - Zhuoyuan Wang; Raffaele Romagnoli; Jasmine Ratchford; Yorie Nakahira (CoRR, 2025)

Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics. - Haoming Jing; Yorie Nakahira (CoRR, 2025)