Nikolai Matni

According to our database, Nikolai Matni authored at least 130 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples.

Thomas T. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

CoRR, 2024

State space models, emergence, and ergodicity: How many parameters are needed for stable predictions?

Ingvar M. Ziemann, Nikolai Matni, George J. Pappas

CoRR, 2024

Closed-loop Analysis of ADMM-based Suboptimal Linear Model Predictive Control.

Anusha Srikanthan, Aren Karapetyan, Vijay Kumar, Nikolai Matni

CoRR, 2024

Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning.

Fengjun Yang, Nikolai Matni

CoRR, 2024

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control.

Bruce D. Lee, Leonardo F. Toso, Thomas T. C. K. Zhang, James Anderson, Nikolai Matni

CoRR, 2024

Single Trajectory Conformal Prediction.

Brian Lee, Nikolai Matni

CoRR, 2024

Vision Transformers for End-to-End Vision-Based Quadrotor Obstacle Avoidance.

Anish Bhattacharya, Nishanth Rao, Dhruv Parikh, Pratik Kunapuli, Nikolai Matni, Vijay Kumar

CoRR, 2024

Reactive Temporal Logic-based Planning and Control for Interactive Robotic Tasks.

Farhad Nawaz, Shaoting Peng, Lars Lindemann, Nadia Figueroa, Nikolai Matni

CoRR, 2024

Active Learning for Control-Oriented Identification of Nonlinear Systems.

Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

CoRR, 2024

Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies.

Bo Wu, Bruce D. Lee, Kostas Daniilidis, Bernadette Bucher, Nikolai Matni

CoRR, 2024

Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control.

Nikolai Matni, Aaron D. Ames, John C. Doyle

CoRR, 2024

Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems.

Hanli Zhang, Anusha Srikanthan, Spencer Folk, Vijay Kumar, Nikolai Matni

CoRR, 2024

Robust model predictive control with polytopic model uncertainty through System Level Synthesis.

Shaoru Chen, Victor M. Preciado, Manfred Morari, Nikolai Matni

Autom., 2024

EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields.

Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera Ojeda, Sai Vemprala, Rogerio Bonatti, Kostas Daniilidis, Ashish Kapoor, Vijay Kumar, Nikolai Matni, Jayesh K. Gupta

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification.

Bruce D. Lee, Anders Rantzer, Nikolai Matni

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Learning Complex Motion Plans using Neural ODEs with Safety and Stability Guarantees.

Farhad Nawaz, Tianyu Li, Nikolai Matni, Nadia Figueroa

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss.

Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples.

Thomas T. C. K. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data.

Thomas T. C. K. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Distributed and Localized Model Predictive Control - Part II: Theoretical Guarantees.

Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni, James Anderson

IEEE Trans. Control. Netw. Syst., September, 2023

Distributed and Localized Model-Predictive Control-Part I: Synthesis and Implementation.

Carmen Amo Alonso, Jing Shuang Li, James Anderson, Nikolai Matni

IEEE Trans. Control. Netw. Syst., June, 2023

Risk of Stochastic Systems for Temporal Logic Specifications.

Lars Lindemann, Lejun Jiang, Nikolai Matni, George J. Pappas

ACM Trans. Embed. Comput. Syst., 2023

Augmented Lagrangian Methods as Layered Control Architectures.

Anusha Srikanthan, Vijay Kumar, Nikolai Matni

CoRR, 2023

Meta-Learning Operators to Optimality from Multi-Task Non-IID Data.

Thomas T. C. K. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni

CoRR, 2023

Learning Safe and Stable Motion Plans with Neural Ordinary Differential Equations.

Farhad Nawaz, Tianyu Li, Nikolai Matni, Nadia Figueroa

CoRR, 2023

Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

CoRR, 2023

Toward Certified Robustness Against Real-World Distribution Shifts.

Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

The noise level in linear regression with dependent data.

Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Task Imitation Learning for Linear Dynamical Systems.

Thomas T. C. K. Zhang, Katie Kang, Bruce D. Lee, Claire J. Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni

Proceedings of the Learning for Dynamics and Control Conference, 2023

Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles.

Kong Yao Chee, M. Ani Hsieh, Nikolai Matni

Proceedings of the Learning for Dynamics and Control Conference, 2023

A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems.

Anusha Srikanthan, Fengjun Yang, Igor Spasojevic, Dinesh Thakur, Vijay Kumar, Nikolai Matni

IROS, 2023

Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning.

David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization.

Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu

Proceedings of the International Conference on Machine Learning, 2023

A Tutorial on the Non-Asymptotic Theory of System Identification.

Ingvar M. Ziemann, Anastasios Tsiamis, Bruce D. Lee, Yassir Jedra, Nikolai Matni, George J. Pappas

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

The Fundamental Limitations of Learning Linear-Quadratic Regulators.

Bruce D. Lee, Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Safety Filter Design for Neural Network Systems via Convex Optimization.

Shaoru Chen, Kong Yao Chee, Nikolai Matni, M. Ani Hsieh, George J. Pappas

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Adversarial Tradeoffs in Robust State Estimation.

Thomas T. C. K. Zhang, Bruce D. Lee, Hamed Hassani, Nikolai Matni

Proceedings of the American Control Conference, 2023

2022

Statistical Learning Theory for Control: A Finite Sample Perspective.

Anastasios Tsiamis, Ingvar M. Ziemann, Nikolai Matni, George J. Pappas

CoRR, 2022

Linear Variational State Space Filtering.

Daniel Pfrommer, Nikolai Matni

CoRR, 2022

TaSIL: Taylor Series Imitation Learning.

Daniel Pfrommer, Thomas T. C. K. Zhang, Stephen Tu, Nikolai Matni

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarially Robust Stability Certificates can be Sample-Efficient.

Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni

Proceedings of the Learning for Dynamics and Control Conference, 2022

On the Sample Complexity of Stability Constrained Imitation Learning.

Stephen Tu, Alexander Robey, Tingnan Zhang, Nikolai Matni

Proceedings of the Learning for Dynamics and Control Conference, 2022

Generalization Bounded Implicit Learning of Nearly Discontinuous Functions.

Bibit Bianchini, Mathew Halm, Nikolai Matni, Michael Posa

Proceedings of the Learning for Dynamics and Control Conference, 2022

Uncertainty-driven Planner for Exploration and Navigation.

Georgios Georgakis, Bernadette Bucher, Anton Arapin, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Single Trajectory Nonparametric Learning of Nonlinear Dynamics.

Ingvar M. Ziemann, Henrik Sandberg, Nikolai Matni

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Learning to Control Linear Systems can be Hard.

Anastasios Tsiamis, Ingvar M. Ziemann, Manfred Morari, Nikolai Matni, George J. Pappas

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

How are policy gradient methods affected by the limits of control?

Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Distributed Optimal Control of Graph Symmetric Systems via Graph Filters.

Fengjun Yang, Fernando Gama, Somayeh Sojoudi, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Robust Model Predictive Control of Time-Delay Systems through System Level Synthesis.

Shaoru Chen, Ning-Yuan Li, Victor M. Preciado, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Data-driven Distributed and Localized Model Predictive Control.

Carmen Amo Alonso, Fengjun Yang, Nikolai Matni

CoRR, 2021

Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations.

Lars Lindemann, Alexander Robey, Lejun Jiang, Stephen Tu, Nikolai Matni

CoRR, 2021

Adversarial Tradeoffs in Linear Inverse Problems and Robust State Estimation.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

CoRR, 2021

System Level Synthesis-based Robust Model Predictive Control through Convex Inner Approximation.

Shaoru Chen, Nikolai Matni, Manfred Morari, Victor M. Preciado

CoRR, 2021

Closing the Closed-Loop Distribution Shift in Safe Imitation Learning.

Stephen Tu, Alexander Robey, Nikolai Matni

CoRR, 2021

Data-Driven System Level Synthesis.

Anton Xue, Nikolai Matni

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

Jingxi Xu, Bruce D. Lee, Nikolai Matni, Dinesh Jayaraman

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

An Adversarial Objective for Scalable Exploration.

Bernadette Bucher, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Communication Topology Co-Design in Graph Recurrent Neural Network based Distributed Control.

Fengjun Yang, Nikolai Matni

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

STL Robustness Risk over Discrete-Time Stochastic Processes.

Lars Lindemann, Nikolai Matni, George J. Pappas

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Learning Robust Hybrid Control Barrier Functions for Uncertain Systems.

Alexander Robey, Lars Lindemann, Stephen Tu, Nikolai Matni

Proceedings of the 7th IFAC Conference on Analysis and Design of Hybrid Systems, 2021

2020

Efficient Learning of Distributed Linear-Quadratic Control Policies.

Salar Fattahi, Nikolai Matni, Somayeh Sojoudi

SIAM J. Control. Optim., 2020

On the Sample Complexity of the Linear Quadratic Regulator.

Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

Found. Comput. Math., 2020

Evaluating Robust, Perception Based Control with Quadrotors.

Laura Jarin-Lipschitz, Rebecca Li, Ty Nguyen, Vijay Kumar, Nikolai Matni

CoRR, 2020

Action for Better Prediction.

Bernadette Bucher, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis

CoRR, 2020

Sample Complexity of Kalman Filtering for Unknown Systems.

Anastasios Tsiamis, Nikolai Matni, George J. Pappas

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Robust Guarantees for Perception-Based Control.

Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Robust, Perception Based Control with Quadrotors.

Laura Jarin-Lipschitz, Rebecca Li, Ty Nguyen, Vijay Kumar, Nikolai Matni

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction.

Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Hybrid Control Barrier Functions from Data.

Lars Lindemann, Haimin Hu, Alexander Robey, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, Nikolai Matni

Proceedings of the 4th Conference on Robot Learning, 2020

Learning Stability Certificates from Data.

Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani

Proceedings of the 4th Conference on Robot Learning, 2020

Learning Control Barrier Functions from Expert Demonstrations.

Alexander Robey, Haimin Hu, Lars Lindemann, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, Nikolai Matni

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Robust Closed-loop Model Predictive Control via System Level Synthesis.

Shaoru Chen, Han Wang, Manfred Morari, Victor M. Preciado, Nikolai Matni

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Distributed and Localized Closed Loop Model Predictive Control via System Level Synthesis.

Carmen Amo Alonso, Nikolai Matni

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Explicit Distributed and Localized Model Predictive Control via System Level Synthesis.

Carmen Amo Alonso, Nikolai Matni, James Anderson

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Robust Performance Guarantees for System Level Synthesis.

Nikolai Matni, Anish A. Sarma

Proceedings of the 2020 American Control Conference, 2020

The driver and the engineer: Reinforcement learning and robust control.

Natalie Bernat, Jiexin Chen, Nikolai Matni, John Doyle

Proceedings of the 2020 American Control Conference, 2020

2019

A System-Level Approach to Controller Synthesis.

Yuh-Shyang Wang, Nikolai Matni, John C. Doyle

IEEE Trans. Autom. Control., 2019

Distributed and Localized Model Predictive Control via System Level Synthesis.

Carmen Amo Alonso, Nikolai Matni

CoRR, 2019

Efficient Learning of Distributed Linear-Quadratic Controllers.

Salar Fattahi, Nikolai Matni, Somayeh Sojoudi

CoRR, 2019

Sparsity Preserving Discretization With Error Bounds.

James Anderson, Nikolai Matni, Yuxiao Chen

CoRR, 2019

System level synthesis.

James Anderson, John C. Doyle, Steven H. Low, Nikolai Matni

Annu. Rev. Control., 2019

A Tutorial on Concentration Bounds for System Identification.

Nikolai Matni, Stephen Tu

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

From self-tuning regulators to reinforcement learning and back again.

Nikolai Matni, Alexandre Proutière, Anders Rantzer, Stephen Tu

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Learning Sparse Dynamical Systems from a Single Sample Trajectory.

Salar Fattahi, Nikolai Matni, Somayeh Sojoudi

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Safely Learning to Control the Constrained Linear Quadratic Regulator.

Sarah Dean, Stephen Tu, Nikolai Matni, Benjamin Recht

Proceedings of the 2019 American Control Conference, 2019

2018

A Control-Theoretic Approach to In-Network Congestion Management.

Ning Wu, Yingjie Bi, Nithin Michael, Ao Tang, John C. Doyle, Nikolai Matni

IEEE/ACM Trans. Netw., 2018

Separable and Localized System-Level Synthesis for Large-Scale Systems.

Yuh-Shyang Wang, Nikolai Matni, John C. Doyle

IEEE Trans. Autom. Control., 2018

Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator.

Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System.

Ross Boczar, Nikolai Matni, Benjamin Recht

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Passive-Aggressive Learning and Control.

Dimitar Ho, Nikolai Matni, John C. Doyle

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Communication Delay Co-Design in ℋ₂-Distributed Control Using Atomic Norm Minimization.

Nikolai Matni

IEEE Trans. Control. Netw. Syst., 2017

Separable and Localized System Level Synthesis for Large-Scale Systems.

Yuh Shyang Wang, Nikolai Matni, John C. Doyle

CoRR, 2017

HFTraC: High-Frequency Traffic Control.

Ning Wu, Yingjie Bi, Nithin Michael, Ao Tang, John Doyle, Nikolai Matni

Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 05, 2017

Scalable system level synthesis for virtually localizable systems.

Nikolai Matni, Yuh-Shyang Wang, James Anderson

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

System level synthesis: A tutorial.

John C. Doyle, Nikolai Matni, Yuh Shyang Wang, James Anderson, Steven H. Low

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

System Level Parameterizations, constraints and synthesis.

Yuh Shyang Wang, Nikolai Matni, John C. Doyle

Proceedings of the 2017 American Control Conference, 2017

Optimal zero-queue congestion control using ADMM.

Nikolai Matni

Proceedings of the 2017 American Control Conference, 2017

Structured state space realizations for SLS distributed controllers.

James Anderson, Nikolai Matni

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Regularization for Design.

Nikolai Matni, Venkat Chandrasekaran

IEEE Trans. Autom. Control., 2016

A System Level Approach to Controller Synthesis.

Yuh Shyang Wang, Nikolai Matni, John C. Doyle

CoRR, 2016

Teaching control theory in high school.

John Doyle, Yorie Nakahira, Yoke Peng Leong, Emily Jenson, Adam Dai, Dimitar Ho, Nikolai Matni

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Localized LQR control with actuator regularization.

Yuh Shyang Wang, Nikolai Matni, John C. Doyle

Proceedings of the 2016 American Control Conference, 2016

Localized LQG optimal control for large-scale systems.

Yuh Shyang Wang, Nikolai Matni

Proceedings of the 2016 American Control Conference, 2016

A Theory of dynamics, control and optimization in layered architectures.

Nikolai Matni, John C. Doyle

Proceedings of the 2016 American Control Conference, 2016

2015

A Convex Approach to Sparse H infinity Analysis & Synthesis.

Seungil You, Nikolai Matni

CoRR, 2015

A case study in network architecture tradeoffs.

Nikolai Matni, Ao Tang, John C. Doyle

Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research, 2015

A convex approach to sparse ℋ∞ analysis & synthesis.

Seungil You, Nikolai Matni

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Hard limits on robust control over delayed and quantized communication channels with applications to sensorimotor control.

Yorie Nakahira, Nikolai Matni, John C. Doyle

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014

Low-Rank and Low-Order Decompositions for Local System Identification.

Nikolai Matni, Anders Rantzer

CoRR, 2014

Optimal Two Player LQR State Feedback With Varying Delay.

Nikolai Matni, Andrew G. Lamperski, John C. Doyle

CoRR, 2014

Communication Delay Co-Design in $\mathcal{H}_2$ Distributed Control Using Atomic Norm Minimization.

Nikolai Matni

CoRR, 2014

Convex relaxations of SE(2) and SE(3) for visual pose estimation.

Matanya B. Horowitz, Nikolai Matni, Joel W. Burdick

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Resilience in Large Scale Distributed Systems.

Nikolai Matni, Yoke Peng Leong, Yuh Shyang Wang, Seungil You, Matanya B. Horowitz, John C. Doyle

Proceedings of the Conference on Systems Engineering Research, 2014

Localized LQR optimal control.

Yuh Shyang Wang, Nikolai Matni, John C. Doyle

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Distributed control subject to delays satisfying an ℋ1 norm bound.

Nikolai Matni

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Synthesizing combination therapies for evolutionary dynamics of disease for nonlinear pharmacodynamics.

Vanessa Jonsson, Nikolai Matni, Richard M. Murray

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Localized distributed state feedback control with communication delays.

Yuh Shyang Wang, Nikolai Matni, Seungil You, John C. Doyle

Proceedings of the American Control Conference, 2014

Localized distributed optimal control with output feedback and communication delays.

Yuh-Shyan Wang, Nikolai Matni

Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

A convex approach to consensus on SO(n).

Nikolai Matni, Matanya B. Horowitz

Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013

Optimal distributed LQG state feedback with varying communication delay.

Nikolai Matni, John C. Doyle

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Communication delay co-design in ℌ2 decentralized control Using atomic norm minimization.

Nikolai Matni

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Reverse engineering combination therapies for evolutionary dynamics of disease: An ℌ∞ approach.

Vanessa Jonsson, Nikolai Matni, Richard M. Murray

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

A heuristic for sub-optimal ℌ2 decentralized control subject to delay in non-quadratically-invariant systems.

Nikolai Matni, John C. Doyle

Proceedings of the American Control Conference, 2013

A dual problem in ℌ2 decentralized control subject to delays.

Nikolai Matni, John C. Doyle

Proceedings of the American Control Conference, 2013

2012

A projection framework for near-potential polynomial games.

Nikolai Matni

Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011

Stability of switched block upper-triangular linear systems with switching delay: Application to large distributed systems.

Nikolai Matni, Meeko Oishi

Proceedings of the American Control Conference, 2011

2009

Reachability analysis for continuous systems under shared control: Application to user-interface design.

Nikolai Matni, Meeko Oishi

Proceedings of the 48th IEEE Conference on Decision and Control, 2009

2008

Reachability-based abstraction for an aircraft landing under shared control.

Nikolai Matni, Meeko Oishi

Proceedings of the American Control Conference, 2008

Towards Provably Safe Control for Smart Wheelchairs.

Meeko Oishi, Nikolai Matni

Proceedings of the AI in Eldercare: New Solutions to Old Problems, 2008