Jonathan DeCastro

749 citations

40 papers · 470 indexed · h-index 12

Impact in

Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Control and Systems Engineering top 5%
- Fault Detection and Control Systems
- Advanced Control Systems Optimization
- Machine Fault Diagnosis Techniques

Papers in ⓘ

Automotive Engineering 14
- Autonomous Vehicle Technology and Safety 13
Artificial Intelligence 13
- Reinforcement Learning in Robotics 4
- Anomaly Detection Techniques and Applications 4

Co-authors: Hadas Kress‐Gazit (6 shared papers)Liang Tang (5 shared papers)Xiaodong Zhang (2 shared papers)Kai Goebel (5 shared papers)Daniela Rus (6 shared papers)Guy Rosman (11 shared papers)Vasumathi Raman (2 shared papers)Liang Tang (3 shared papers)
Journals: IEEE Robotics and Automation Letters (4 papers)The International Journal of Robotics Research (2 papers)Scientific Reports (1 paper)IEEE Transactions on Industrial Electronics (1 paper)IEEE Transactions on Control Systems Technology (1 paper)
Partner nations: United States Switzerland Canada

In The Last Decade

Jonathan DeCastro

38 papers receiving 462 citations

Peers

Countries citing papers authored by Jonathan DeCastro

Since Specialization

Citations

This map shows the geographic impact of Jonathan DeCastro's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jonathan DeCastro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan DeCastro more than expected).

Fields of papers citing papers by Jonathan DeCastro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan DeCastro. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jonathan DeCastro. The network helps show where Jonathan DeCastro may publish in the future.

Co-authors

The 25 scholars most cited alongside Jonathan DeCastro, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan DeCastro Line = papers co-authored together Jonathan DeCastro links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Robust Fault Diagnosis of Aircraft Engines: A Nonlinear Adaptive Estimation-Based Approach IEEE Transactions on Control Systems Technology ·Xiaodong Zhang, Liang Tang, Jonathan DeCastro	2012	52
2	DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling IEEE Robotics and Automation Letters ·Xin Huang, Stephen G. McGill, Jonathan DeCastro, Luke Fletcher, John J. Leonard, Brian Williams, Guy Rosman	2020	49
3	Reactive mission and motion planning with deadlock resolution avoiding dynamic obstacles Autonomous Robots ·Javier Alonso–Mora, Jonathan DeCastro, Vasumathi Raman, Daniela Rus, Hadas Kress‐Gazit	2017	47
4	Rate-Based Model Predictive Control of Turbofan Engine Clearance Journal of Propulsion and Power ·Jonathan DeCastro	2007	41
5	Vehicle Trajectory Prediction Using Generative Adversarial Network With Temporal Logic Syntax Tree Features IEEE Robotics and Automation Letters ·Xiao Li, Guy Rosman, Igor Gilitschenski, Cristian-Ioan Vasile, Jonathan DeCastro, Sertaç Karaman, Daniela Rus	2021	40
6	A Recursive Receding Horizon Planning for Unmanned Vehicles IEEE Transactions on Industrial Electronics ·Bin Zhang, Liang Tang, Jonathan DeCastro, Michael Roemer, Kai Goebel	2014	39
7	Filtering and prediction techniques for model-based prognosis and uncertainty management Liang Tang, Jonathan DeCastro, Greg Kacprzynski, Kai Goebel, George Vachtsevanos	2010	23
8	Synthesis of nonlinear continuous controllers for verifiably correct high-level, reactive behaviors The International Journal of Robotics Research ·Jonathan DeCastro, Hadas Kress‐Gazit	2015	21
9	A Testbed for Real-Time Autonomous Vehicle PHM and Contingency Management Applications Annual Conference of the PHM Society ·Liang Tang, Eric Hettler, Bin Zhang, Jonathan DeCastro	2011	20
10	A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults NASA STI Repository (National Aeronautics and Space Administration) ·Liang Tang, Xiaodong Zhang, Jonathan DeCastro, Luis Farfan-Ramos, Donald L. Simon	2010	13
11	A verification methodology for prognostic algorithms Bin Zhang, Liang Tang, Jonathan DeCastro, Kai Goebel	2010	12
12	Guaranteeing reactive high-level behaviors for robots with complex dynamics Jonathan DeCastro, Hadas Kress‐Gazit	2013	11
13	Interpretable Policies from Formally-Specified Temporal Properties Jonathan DeCastro, Karen Leung, Nikos Aréchiga, Marco Pavone	2020	9
14	Nonlinear Controller Synthesis and Automatic Workspace Partitioning for Reactive High-Level Behaviors Jonathan DeCastro, Hadas Kress‐Gazit	2016	8
15	Autonomous Vehicle Battery State-of-Charge Prognostics Enhanced Mission Planning International Journal of Prognostics and Health Management ·Bin Zhang, Liang Tang, Jonathan DeCastro, Michael Roemer, Kai Goebel	2020	8
16	Analysis of Decentralization and Fault-Tolerance Concepts for Distributed Engine Control Jonathan DeCastro, Liang Tang, Carl S. Byington, Dennis E. Culley	2009	7
17	Dynamics-driven adaptive abstraction for reactive high-level mission and motion planning Jonathan DeCastro, Vasumathi Raman, Hadas Kress‐Gazit	2015	6
18	Automated generation of dynamics-based runtime certificates for high-level control Discrete Event Dynamic Systems ·Jonathan DeCastro, Rüdiger Ehlers, Matthias Rungger, Ayça Balkan, Hadas Kress‐Gazit	2016	6
19	CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy IEEE Robotics and Automation Letters ·Xin Huang, Stephen G. McGill, Jonathan DeCastro, Luke Fletcher, John J. Leonard, Brian Williams, Guy Rosman	2021	5
20	Prognostics-enhanced Receding Horizon Mission Planning for Field Unmanned Vehicles AIAA Guidance, Navigation, and Control Conference ·Bin Zhang, Liang Tang, Jonathan DeCastro, Kai Goebel	2011	5

About Jonathan DeCastro

Jonathan DeCastro is a scholar working on Automotive Engineering, Artificial Intelligence, Control and Systems Engineering, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 470 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (13 papers), Formal Methods in Verification (9 papers), Robotic Path Planning Algorithms (6 papers), Traffic and Road Safety (5 papers), Fault Detection and Control Systems (5 papers), Reinforcement Learning in Robotics (4 papers), Anomaly Detection Techniques and Applications (4 papers) and Human-Automation Interaction and Safety (3 papers). The work is most often cited by research in Automotive Engineering (111 citations), Control and Systems Engineering (202 citations), Software (32 citations), Computer Vision and Pattern Recognition (122 citations) and Safety, Risk, Reliability and Quality (51 citations). Jonathan DeCastro has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Hadas Kress‐Gazit, Liang Tang, Xiaodong Zhang, Kai Goebel, Daniela Rus, Guy Rosman, Vasumathi Raman, Liang Tang, Bin Zhang and Michael Roemer. Their work appears in journals such as IEEE Robotics and Automation Letters, The International Journal of Robotics Research, Scientific Reports, IEEE Transactions on Industrial Electronics and IEEE Transactions on Control Systems Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact