Modeling, identification and state estimation of diesel engine torque and NOx dynamics in response to fuel quantity and timing excitations. - Avra Brahma; Devesh Upadhyay; Andrea Serrani; Giorgio Rizzoni (ACC, 2004)

Control Design of Electrically Assisted Boosting Systems for Diesel Powertrain Applications. - Bradley Charles Glenn; Devesh Upadhyay; Gregory N. Washington (IEEE Trans. Control. Syst. Technol., 2010)

Physics-based turbine power models for a Variable Geometry Turbocharger. - Tao Zeng; Devesh Upadhyay; Harold Sun; Guoming G. Zhu (ACC, 2016)

A physics-based control-oriented model for compressor mass flow rate. - Kang Song; Devesh Upadhyay; Harold Sun; Hui Xie 004; Guoming Zhu 001 (CDC, 2016)

A stochastic dynamic programming approach to selective catalytic reduction control. - Cory Hendrickson; Devesh Upadhyay; Michiel Van Nieuwstadt (ACC, 2017)

Linear quadratic air-path control for diesel engines with regenerative and assisted turbocharger. - Tao Zeng; Devesh Upadhyay; Guoming Zhu 001 (CDC, 2017)

Lagrangian Models for Controlling Large-Scale Heterogeneous Traffic. - Tamás G. Molnár; Devesh Upadhyay; Michael Hopka; Michiel Van Nieuwstadt; Gábor Orosz (CDC, 2019)

Special issue on Internet of Things (IoT) for in-vehicle systems. - Shih-Chia Huang; Jenq-Neng Hwang; Sy-Yen Kuo; Alécio P. D. Binotto; Devesh Upadhyay; Patrick C. K. Hung (Eng. Appl. Artif. Intell., 2019)

Open and closed loop traffic control by connected automated vehicles. - Tamás G. Molnár; Devesh Upadhyay; Michael Hopka; Michiel Van Nieuwstadt; Gábor Orosz (CDC, 2020)

Deep Adversarial Koopman Model for Reaction-Diffusion systems. - Kaushik Balakrishnan; Devesh Upadhyay (CoRR, 2020)

NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations. - Kirill Zubov; Zoe McCarthy; Yingbo Ma; Francesco Calisto; Valerio Pagliarino; Simone Azeglio; Luca Bottero; Emmanuel Luján; Valentin Sulzer; Ashutosh Bharambe; Nand Vinchhi; Kaushik Balakrishnan; et al. (CoRR, 2021)

Stochastic Adversarial Koopman Model for Dynamical Systems. - Kaushik Balakrishnan; Devesh Upadhyay (CoRR, 2021)

On-Board Traffic Prediction for Connected Vehicles: Implementation and Experiments on Highways. - Tamás G. Molnár; Xunbi A. Ji; Sanghoon Oh; Dénes Takács; Michael Hopka; Devesh Upadhyay; Michiel Van Nieuwstadt; Gábor Orosz (ACC, 2022)

Appearance-Based Gaze Estimation for Driver Monitoring. - Soodeh Nikan; Devesh Upadhyay (Gaze Meets ML, 2022)

BTranspose: Bottleneck Transformers for Human Pose Estimation with Self-Supervised Pre-Training. - Kaushik Balakrishnan; Devesh Upadhyay (CoRR, 2022)

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles. - Tamás G. Molnár; Michael Hopka; Devesh Upadhyay; Michiel Van Nieuwstadt; Gábor Orosz (CoRR, 2022)

Towards Accurate and Robust Classification in Continuously Transitioning Industrial Sprays with Mixup. - Hongjiang Li; Huanyi Shui; Alemayehu Admasu; Praveen Narayanan; Devesh Upadhyay (CoRR, 2022)

Real-Time Driver Monitoring Systems through Modality and View Analysis. - Yiming Ma 003; Victor Sanchez; Soodeh Nikan; Devesh Upadhyay; Bhushan Atote; Tanaya Guha (CoRR, 2022)

A Survey on Evaluation Metrics for Synthetic Material Micro-Structure Images from Generative Models. - Devesh Shah; Anirudh Suresh; Alemayehu Admasu; Devesh Upadhyay; Kalyanmoy Deb (CoRR, 2022)

Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention. - Yiming Ma 003; Victor Sanchez; Soodeh Nikan; Devesh Upadhyay; Bhushan Atote; Tanaya Guha (CVPR Workshops, 2023)

Using simulation to quantify the performance of automotive perception systems. - Zhenyi Liu; Devesh Shah; Alireza Rahimpour; Devesh Upadhyay; Joyce E. Farrell; Brian A. Wandell (Autonomous Vehicles and Machines, 2023)

Cross Modality Knowledge Distillation for Robust Pedestrian Detection in Low Light and Adverse Weather Conditions. - Mazin Hnewa; Alireza Rahimpour; Justin Miller; Devesh Upadhyay; Hayder Radha (ICASSP, 2023)

Deer in the headlights: FIR-based Future Trajectory Prediction in Nighttime Autonomous Driving. - Alireza Rahimpour; Navid Fallahinia; Devesh Upadhyay; Justin Miller (IV, 2023)

Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Index. - Aria Khademi; Michael Hopka; Devesh Upadhyay (CoRR, 2023)

A Novel Two-level Causal Inference Framework for On-road Vehicle Quality Issues Diagnosis. - Qian Wang 035; Huanyi Shui; Thi Tu Trinh Tran; Milad Zafar Nezhad; Devesh Upadhyay; Kamran Paynabar; Anqi He (CoRR, 2023)

FIR-based Future Trajectory Prediction in Nighttime Autonomous Driving. - Alireza Rahimpour; Navid Fallahinia; Devesh Upadhyay; Justin Miller (CoRR, 2023)

Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems. - Zhiyi Chen; Harshal Maske; Huanyi Shui; Devesh Upadhyay; Michael Hopka; Joseph Cohen; Xingjian Lai; Xun Huan; Jun Ni 002 (CoRR, 2023)

Deep Bayesian-Assisted Keypoint Detection for Pose Estimation in Assembly Automation. - Debo Shi; Alireza Rahimpour; Amin Ghafourian; Mohammad Mahdi Naddaf Shargh; Devesh Upadhyay; Ty A. Lasky; Iman Soltani 001 (Sensors, 2023)

Deep Koopman-Based Control of Quality Variation in Multistage Manufacturing Systems. - Zhiyi Chen; Harshal Maske; Devesh Upadhyay; Huanyi Shui; Xun Huan; Jun Ni 002 (ACC, 2024)

Development and Deployment of Reinforcement Learning based Control for Large Scale Decision-Making in Manufacturing: A Case Study. - Harshal Maske; Devesh Upadhyay; Shuyu Long (CDC, 2024)

Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller. - Mingxin Yu; Chenning Yu; M.-Mahdi Naddaf-Sh; Devesh Upadhyay; Sicun Gao; Chuchu Fan (ICRA, 2024)

Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection. - Liangqi Yuan; Dong-Jun Han; Su Wang 007; Devesh Upadhyay; Christopher G. Brinton (CoRR, 2024)

Inherent Diverse Redundant Safety Mechanisms for AI-based Software Elements in Automotive Applications. - Mandar Pitale; Alireza Abbaspour; Devesh Upadhyay (CoRR, 2024)

C3D: Cascade Control with Change Point Detection and Deep Koopman Learning for Autonomous Surface Vehicles. - Jianwen Li; Hyunsang Park; Wenjian Hao; Lei Xin; Jalil Chavez-Galaviz; Ajinkya Chaudhary; Meredith Bloss; Kyle Pattison; Christopher Vo; Devesh Upadhyay; Shreyas Sundaram; Shaoshuai Mou; et al. (CoRR, 2024)

A Distributed Deep Koopman Learning Algorithm for Control. - Wenjian Hao; Zehui Lu; Devesh Upadhyay; Shaoshuai Mou (CoRR, 2024)

Transfer Learning for Anomaly Detection in Rotating Machinery Using Data-Driven Key Order Estimation. - Jia Liang; Huanyi Shui; Rajesh Gupta; Devesh Upadhyay; Eric Darve (IEEE Trans Autom. Sci. Eng., 2025)

Deep Koopman Learning using Noisy Data. - Wenjian Hao; Devesh Upadhyay; Shaoshuai Mou (Trans. Mach. Learn. Res., 2025)

Targeted Collapse Regularized Autoencoder for Anomaly Detection: Black Hole at the Center. - Amin Ghafourian; Huanyi Shui; Devesh Upadhyay; Rajesh Gupta; Dimitar P. Filev; Iman Soltani 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)