Chandrajit Bajaj

The University of Texas at Austin — United States

Computer Science · Physical Sciences

49h-index9.8kcitations440works0.52yr avg
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Research Topics

Computer Graphics and Visualization Techniques(143), Advanced Numerical Analysis Techniques(96), Computational Geometry and Mesh Generation(91), 3D Shape Modeling and Analysis(73), Advanced Vision and Imaging(37)

Publications439 total

GRL-SNAM: Geometric Reinforcement Learning with Path Differential Hamiltonians for Simultaneous Navigation and Mapping in Unknown Environments
ArXiv.org·2025Open Access
GRL-SNAM: Geometric Reinforcement Learning with Path Differential Hamiltonians for Simultaneous Navigation and Mapping in Unknown Environments
arXiv (Cornell University)·2025Open Access
Scalable Risk-Averse Well-Placement Optimization Using Quadratic Knapsack Problem and Randomized Singular Value Decomposition
SPE Journal·2025
Self-balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-kernel Estimation
Lecture notes in computer science·2025
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
arXiv (Cornell University)·2025Open Access
Self-Balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-Kernel Estimation
arXiv (Cornell University)·2025Open Access
Scalable Robust Bayesian Co-Clustering with Compositional ELBOs
arXiv (Cornell University)·2025Open Access
Reinforcement Learning for Molecular Dynamics Optimization: A Stochastic Pontryagin Maximum Principle Approach
Communications in computer and information science·2025
Low-Cost Robust Night-Time Aerial Material Segmentation Through Hyperspectral Data and Sparse Spatio-Temporal Learning
Communications in computer and information science·2025
Low-cost Robust Night-time Aerial Material Segmentation through Hyperspectral Data and Sparse Spatio-Temporal Learning
arXiv (Cornell University)·2024Open Access
DPO: Differential reinforcement learning with application to optimal configuration search
2024· 1 citedOpen Access
4DRecons: 4D Neural Implicit Deformable Objects Reconstruction from a single RGB-D Camera with Geometrical and Topological Regularizations
arXiv (Cornell University)·2024Open Access
A Differential and Pointwise Control Approach to Reinforcement Learning
2024Open Access
DeblurSR: Event-Based Motion Deblurring under the Spiking Representation
Proceedings of the AAAI Conference on Artificial Intelligence·2024· 6 citedOpen Access
Motion Code: Robust Time Series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning
arXiv (Cornell University)·2024Open Access
Physics-Informed Neural Networks via Stochastic Hamiltonian Dynamics Learning
Lecture notes in networks and systems·2024· 2 cited
An ensemble technique of SmoteENN and random forest for classification of the cardiotocography data
IET conference proceedings.·2023· 2 cited
Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal Processing
2023
A Novel Perspective on Brain Tumor Classification Using Hybrid Algorithm
2023· 1 cited
TAssembly: Data-driven fractured object assembly using a linear template model
Computers & Graphics·2023· 7 cited
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Frequent Co-authors

Yongjie Zhang(8), Valerio Pascucci(8), Daniel R. Schikore(6), Guoliang Xu(4), Fausto Bernardini(3), Guoliang Xu(3), Zeyun Yu(3), Insung Ihm(3), Thomas J.R. Hughes(2), Justin P. Kinney(2), Thomas M. Bartol(2), Kristen M. Harris(2), Terrence J. Sejnowski(2), D.R. Schikore(2), Guoliang Xu(2), Alexander Rand(2), Guozhong Zhuang(2), Joe Warren(2), Yuri Bazilevs(1), Samrat Goswami(1)