164 citations · 233 across the 14 of their papers we have counts for
15 papers
A Hierarchical Test Platform for Vision Language Model (VLM)-Integrated Real-World Autonomous Driving
Yupeng Zhou, Can Cui, Juntong Peng +5
Vision-Language Models (VLMs) have demonstrated notable promise in autonomous driving by offering the potential for multimodal reasoning through pretraining on extensive image-text…
Hybrid SIS Dynamics for Demand Modeling of Frequently Updated Products
Ian Walter, Jitesh H. Panchal, Philip E. Paré
We propose a hybrid spreading process model to capture the dynamics of demand for software-based products. We introduce discontinuous jumps in the state to model sudden surges in d…
On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation
Can Cui, Zichong Yang, Yupeng Zhou +11
Personalized driving refers to an autonomous vehicle's ability to adapt its driving behavior or control strategies to match individual users' preferences and driving styles while m…
LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments, and Future Trends
Can Cui, Yunsheng Ma, Sung-Yeon Park +14
With the broader adoption and highly successful development of Large Language Models (LLMs), there has been growing interest and demand for applying LLMs to autonomous driving tech…
Optimal Ordering Policies for Multi-Echelon Supply Networks
Jose I. Caiza, Ian Walter, Jitesh H. Panchal +2
In this paper, we formulate an optimal ordering policy as a stochastic control problem where each firm decides the amount of input goods to order from their upstream suppliers base…
Test and Evaluation Framework for Multi-Agent Systems of Autonomous Intelligent Agents
Erin Lanus, Ivan Hernandez, Adam Dachowicz +6
Test and evaluation is a necessary process for ensuring that engineered systems perform as intended under a variety of conditions, both expected and unexpected. In this work, we co…
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis +1
Estimating arbitrary quantities of interest (QoIs) that are non-linear operators of complex, expensive-to-evaluate, black-box functions is a challenging problem due to missing doma…
A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design
Salar Safarkhani, Vikranth Reddy Kattakuri, Ilias Bilionis +1
We present a principal-agent model of a one-shot, shallow, systems engineering process. The process is one-shot in the sense that decisions are made during one time step and that t…
Towards a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process
Salar Safarkhani, Ilias Bilionis, Jitesh Panchal
Systems engineering processes coordinate the effort of different individuals to generate a product satisfying certain requirements. As the involved engineers are self-interested ag…
Simulator-free Solution of High-Dimensional Stochastic Elliptic Partial Differential Equations using Deep Neural Networks
Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis +1
Stochastic partial differential equations (SPDEs) are ubiquitous in engineering and computational sciences. The stochasticity arises as a consequence of uncertainty in input parame…
Bayesian Optimal Design of Experiments For Inferring The Statistical Expectation Of A Black-Box Function
Piyush Pandita, Ilias Bilionis, Jitesh Panchal
Bayesian optimal design of experiments (BODE) has been successful in acquiring information about a quantity of interest (QoI) which depends on a black-box function. BODE is charact…
Stochastic Multi-objective Optimization on a Budget: Application to multi-pass wire drawing with quantified uncertainties
Piyush Pandita, Ilias Bilionis, Jitesh Panchal +3
Design optimization of engineering systems with multiple competing objectives is a painstakingly tedious process especially when the objective functions are expensive-to-evaluate c…
Extending Expected Improvement for High-dimensional Stochastic Optimization of Expensive Black-Box Functions
Piyush Pandita, Ilias Bilionis, Jitesh Panchal
Design optimization under uncertainty is notoriously difficult when the objective function is expensive to evaluate. State-of-the-art techniques, e.g, stochastic optimization or sa…
Dynamic State Estimation under Cyber Attacks: A Comparative Study of Kalman Filters and Observers
Ahmad F. Taha, Junjian Qi, Jianhui Wang +1
Utilizing highly synchronized measurements from synchrophasors, dynamic state estimation (DSE) can be applied for real-time monitoring of smart grids. Concurrent DSE studies for po…
Risk Mitigation for Dynamic State Estimation Against Cyber Attacks and Unknown Inputs
Ahmad F. Taha, Junjian Qi, Jianhui Wang +1
Phasor measurement units (PMUs) can be effectively utilized for the monitoring and control of the power grid. As the cyber-world becomes increasingly embedded into power grids, the…