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ORCIDMrinal Kumar 0002
Person information
- affiliation: Ohio State University, Department of Mechanical and Aerospace University, Columbus, OH, USA
- affiliation (2010 - 2016): University of Florida, Gainesville, Department of Mechanical and Aerospace Engineering, FL, USA
- affiliation (PhD 2009): Texas A&M University, Department of Aerospace Engineering, College Station, TX, USA
Other persons with the same name
- Mrinal Kumar 0001
![[0000-0002-6430-0219]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-6430-0219")
— Tata Institute of Fundamental Research, Mumbai, India (and 4 more) - Mrinal Kumar 0003 — Maharashtra Institute of Technology, Optimization and Agent Technology (OAT) Research Lab, Pune, India
- Mrinal Kumar 0004 — Georgia Institute of Technology, Atlanta, GA, USA
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2020 – today
- 2024
[c30]Bryce Ford, Mrinal Kumar:
Analysis of Backtracking A* for Resource Constrained Shortest Path Problems. ACC 2024: 3545-3550- [i2]Sriram Narayanan, Mohamed Naveed Gul Mohamed, Indranil Nayak, Suman Chakravorty, Mrinal Kumar:
On the Predictive Capability of Dynamic Mode Decomposition for Nonlinear Periodic Systems with Focus on Orbital Mechanics. CoRR abs/2401.13784 (2024) - [i1]Indranil Nayak, Debdipta Goswami, Mrinal Kumar, Fernando L. Teixeira:
Temporally-Consistent Koopman Autoencoders for Forecasting Dynamical Systems. CoRR abs/2403.12335 (2024) - 2023
- [j7]Andrew W. Vanfossen, Mrinal Kumar:
Efficient Adaptive Monte Carlo Uncertainty Forecasting for High Dimensional Nonlinear Dynamic Systems. IEEE Access 11: 12119-12138 (2023) - [j6]Alexander A. Soderlund, Mrinal Kumar:
Estimating the Spread of Wildland Fires via Evidence-Based Information Fusion. IEEE Trans. Control. Syst. Technol. 31(2): 511-526 (2023) - 2022
- [c29]Pradhyumn Bhale, Mrinal Kumar, Amit K. Sanyal:
Finite-time stable disturbance observer for unmanned aerial vehicles. ACC 2022: 5010-5015 - [c28]Mrinal Kumar, Roger Williams, Amit K. Sanyal:
Role of Autonomous Unmanned Aerial Systems in Prescribed Burn Projects. DDDAS 2022: 395-402 - 2021
- [j5]Indranil Nayak, Mrinal Kumar, Fernando L. Teixeira:
Detection and prediction of equilibrium states in kinetic plasma simulations via mode tracking using reduced-order dynamic mode decomposition. J. Comput. Phys. 447: 110671 (2021) - 2020
- [c27]Rachit Aggarwal, Alexander A. Soderlund, Mrinal Kumar, David J. Grymin:
Risk Aware SUAS Path Planning in an Unstructured Wildfire Environment. ACC 2020: 1767-1772 - [c26]Sriram Krishnaswamy, Shane Vitullo, Will Laidler, Mrinal Kumar:
Dynamic Joint Probabilistic Data Association Framework for Target Tracking with Ground Robots. ACC 2020: 2076-2081 - [c25]Rachel E. Keil, Alexander Miller, Mrinal Kumar, Anil V. Rao:
Biased Kernel Density Estimators for Chance Constrained Optimal Control Problems. ACC 2020: 2820-2825
2010 – 2019
- 2019
- [c24]Meng Huang, Mrinal Kumar, Chao Yang:
On the Optimal Condition for Battery Aging Assessment Based on an Electrochemical Model. ACC 2019: 181-186 - [c23]Sriram Krishnaswamy, Mrinal Kumar:
A Window-based Tensor Decomposition Approach to Data-Association for Multi Target Tracking. ACC 2019: 5148-5153 - 2018
- [j4]Chao Yang, Mrinal Kumar:
On the effectiveness of Monte Carlo for initial uncertainty forecasting in nonlinear dynamical systems. Autom. 87: 301-309 (2018) - [c22]Chao Yang, Mrinal Kumar:
Discrepancy Driven Adaptive Monte Carlo for Forward Uncertainty Forecasting in Nonlinear Dynamical Systems. ACC 2018: 5448-5453 - [c21]Alexander A. Soderlund, Mrinal Kumar:
Markovian Wildfire Modeling via Evidential Reasoning. CDC 2018: 5592-5597 - [p1]Alexander A. Soderlund, Mrinal Kumar:
Optimization of Multi-target Tracking Within a Sensor Network Via Information Guided Clustering. Handbook of Dynamic Data Driven Applications Systems 2018: 337-380 - 2017
- [c20]Chao Yang, Mrinal Kumar:
On the transient performance of Monte Carlo simulations for initial uncertainty forecasting. CDC 2017: 1669-1674 - 2016
- [c19]Yifei Sun, Mrinal Kumar:
Uncertainty forecasting in the perturbed two-body problem via tensor decomposition. ACC 2016: 5431-5436 - 2015
- [j3]Yifei Sun, Mrinal Kumar:
A numerical solver for high dimensional transient Fokker-Planck equation in modeling polymeric fluids. J. Comput. Phys. 289: 149-168 (2015) - [j2]Chao Yang, Mrinal Kumar:
An information guided framework for simulated annealing. J. Glob. Optim. 62(1): 131-154 (2015) - [c18]Yifei Sun, Mrinal Kumar:
Solution of high dimensional transient Fokker-Planck equations by tensor decomposition. ACC 2015: 1475-1480 - [c17]Zinan Zhao, Fengjin Liu, Mrinal Kumar, Anil V. Rao:
A novel approach to chance constrained optimal control problems. ACC 2015: 5611-5616 - [c16]Chao Yang, Kevin Buck, Mrinal Kumar:
An evaluation of Monte Carlo for nonlinear initial uncertainty propagation in Keplerian mechanics. FUSION 2015: 119-125 - [c15]Yifei Sun, Mrinal Kumar:
Nonlinear Bayesian filtering based on Fokker-Planck equation and tensor decomposition. FUSION 2015: 1483-1488 - 2014
- [j1]Yifei Sun, Mrinal Kumar:
Numerical solution of high dimensional stationary Fokker-Planck equations via tensor decomposition and Chebyshev spectral differentiation. Comput. Math. Appl. 67(10): 1960-1977 (2014) - [c14]Zinan Zhao, Mrinal Kumar:
A MCMC/Bernstein approach to chance constrained programs. ACC 2014: 4318-4323 - [c13]Yifei Sun, Mrinal Kumar:
A tensor decomposition approach to high dimensional stationary Fokker-Planck equations. ACC 2014: 4500-4505 - [c12]Chao Yang, Mrinal Kumar:
Beyond Monte Carlo for the initial uncertainty propagation problem. CDC 2014: 5183-5188 - [c11]Zinan Zhao, Mrinal Kumar:
A split-bernstein approach to chance constrained programs. CDC 2014: 6621-6626 - 2012
- [c10]Yifei Sun, Mrinal Kumar:
A meshless p-PUFEM Fokker-Planck equation solver with automatic boundary condition enforcement. ACC 2012: 74-79 - [c9]Mrinal Kumar:
An information guided framework for simulated annealing. ACC 2012: 827-832 - [c8]Zinan Zhao, Mrinal Kumar:
An MCMC-based particle filter for multiple target tracking. FUSION 2012: 1676-1682 - [c7]Zinan Zhao, Mrinal Kumar:
A comparative study of randomized algorithms for multidimensional integration. FUSION 2012: 2236-2242 - 2010
- [c6]Mrinal Kumar, Suman Chakravorty:
A nonlinear filter based on Fokker-Planck equation. ACC 2010: 3136-3141 - [c5]Mrinal Kumar, Suman Chakravorty:
A nonlinear filter based on Fokker Planck equation and MCMC measurement updates. CDC 2010: 7357-7362 - [c4]Amanda Kathryn Lampton, John Valasek, Mrinal Kumar:
Multi-resolution state-space discretization for Q-Learning with pseudo-randomized discretization. IJCNN 2010: 1-8
2000 – 2009
- 2007
- [c3]Mrinal Kumar, Suman Chakravorty, John L. Junkins:
A Homotopic Approach to Domain Determination and Solution Refinement for the Fokker-Planck Equation. ACC 2007: 1045-1050 - [c2]Mrinal Kumar, Suman Chakravorty, John L. Junkins:
A semianalytic meshless approach to the Fokker-Planck equation with application to hybrid systems. CDC 2007: 3078-3083 - 2006
- [c1]Suman Chakravorty, Mrinal Kumar, Puneet Singla:
A quasi-Gaussian Kalman filter. ACC 2006
Coauthor Index
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