Publications related to Manifold Learning and Optimal Control for Obstacle Avoidance in Autonomous Driving

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

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Over-reliance on the automation of transportation systems is understood to be the cause of new types of accidents. In this paper, the automated driving system is augmented with control methods enabling driver intervention without its full deactivation. The ...

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Scalable constrained optimization

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Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

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The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

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A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

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Efficient Continual Finite-Sum Minimization

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Given a sequence of functions

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Manifold Learning and Optimal Control for Obstacle Avoidance in Autonomous Driving

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

The Haptic Link Enabling Driver-Automation Teaming

Scalable constrained optimization

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Graph generative deep learning models with an application to circuit topologies

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Inhalation of Microplastics—A Toxicological Complexity

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Efficient Continual Finite-Sum Minimization

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

The Haptic Link Enabling Driver-Automation Teaming

Scalable constrained optimization

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Graph generative deep learning models with an application to circuit topologies

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Inhalation of Microplastics—A Toxicological Complexity

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Efficient Continual Finite-Sum Minimization

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning