1D inverse problem in diffusion based optical tomography using iteratively regularized Gauss-Newton algorithm. - Taufiquar Khan; Alexandra Smirnova (Appl. Math. Comput., 2005)

Statistical Inversion of Absolute Permeability in Single-phase Darcy Flow. - Thilo Strauss; Xiaolin Fan; Shuyu Sun 001; Taufiquar Khan (ICCS, 2015)

Improving the Efficacy of Car-Following Models With a New Stochastic Parameter Estimation and Calibration Method. - Mizanur Rahman; Mashrur Chowdhury; Taufiquar Khan; Parth Bhavsar (IEEE Trans. Intell. Transp. Syst., 2015)

Comparison of statistical inversion with iteratively regularized Gauss Newton method for image reconstruction in electrical impedance tomography. - Sanwar Ahmad; Thilo Strauss; Shyla Kupis; Taufiquar Khan (Appl. Math. Comput., 2019)

Development of a Connected and Automated Vehicle Longitudinal Control Model. - Mizanur Rahman; Md Rafiul Islam; Mashrur Chowdhury; Taufiquar Khan (CoRR, 2020)

Statistical Inversion Using Sparsity and Total Variation Prior And Monte Carlo Sampling Method For Diffuse Optical Tomography. - Thilo Strauss; Sanwar Ahmad; Taufiquar Khan (CoRR, 2020)

A Physics-Based Longitudinal Driver Model for Automated Vehicles. - Mizanur Rahman; Md Rafiul Islam; Mashrur Chowdhury; Taufiquar Khan (IEEE Access, 2022)

The Carleman-Newton method to globally reconstruct a source term for nonlinear parabolic equation. - Anuj Abhishek; Thuy T. Le; Loc Nguyen; Taufiquar Khan (CoRR, 2022)

Dynamics of heterogeneous population due to spatially distributed parameters and an ideal free pair. - Ishrat Zahan; Md. Kamrujjaman; Md Abdul Alim; Muhammad Mohebujjaman; Taufiquar Khan (Frontiers Appl. Math. Stat., 2022)

An Optimal Bayesian Estimator for Absorption Coefficient in Diffuse Optical Tomography. - Anuj Abhishek; Thilo Strauss; Taufiquar Khan (SIAM J. Imaging Sci., 2022)

Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography. - Akarsh Pokkunuru; Pedram Rooshenas; Thilo Strauss; Anuj Abhishek; Taufiquar Khan (ICLR, 2023)

Physics-Informed Neural Networks for the Heat Equation with Source Term under Various Boundary Conditions. - Brett Bowman; Chad Oian; Jason Kurz; Taufiquar Khan; Eddie Gil; Nick Gamez (Algorithms, 2023)

Comparison of Different Radial Basis Function Networks for the Electrical Impedance Tomography (EIT) Inverse Problem. - Chowdhury Abrar Faiyaz; Pabel Shahrear; Rakibul Alam Shamim; Thilo Strauss; Taufiquar Khan (Algorithms, 2023)

Recovering the Forcing Function in Systems with One Degree of Freedom Using ANN and Physics Information. - Shadab Anwar Shaikh; Harish Cherukuri; Taufiquar Khan (Algorithms, 2023)

The evolution of resource distribution, slow diffusion, and dispersal strategies in heterogeneous populations. - Ishrat Zahan; Md. Kamrujjaman; Md Abdul Alim; Md. Shahidul Islam; Taufiquar Khan (Frontiers Appl. Math. Stat., 2023)

Implicit Solutions of the Electrical Impedance Tomography Inverse Problem in the Continuous Domain with Deep Neural Networks. - Thilo Strauss; Taufiquar Khan (Entropy, 2023)

A Bayesian level-set inversion method for simultaneous reconstruction of absorption and diffusion coefficients in diffuse optical tomography. - Anuj Abhishek; Thilo Strauss; Taufiquar Khan (CoRR, 2024)

Stocking and Harvesting Effects in Advection-Reaction-Diffusion Model: Exploring Decoupled Algorithms and Analysis. - Mayesha Sharmim Tisha; Md. Kamrujjaman; Muhammad Mohebujjaman; Taufiquar Khan (CoRR, 2024)

Sensitivity Analysis and Monte Carlo Based Uncertainty Quantification of the In-process Modal Parameters in Milling. - M. Hashemitaheri; T. T. Le; Taufiquar Khan; Harish Cherukuri (CoRR, 2024)

Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification. - Andrew C. Pangia; Agus Sudjianto; Aijun Zhang; Taufiquar Khan (CoRR, 2024)

MCMC-Net: Accelerating Markov Chain Monte Carlo with Neural Networks for Inverse Problems. - Sudeb Majee; Anuj Abhishek; Thilo Strauss; Taufiquar Khan (CoRR, 2024)

The Carleman-Newton method to globally reconstruct the initial condition for nonlinear parabolic equations. - Anuj Abhishek; Thuy T. Le; Loc H. Nguyen; Taufiquar Khan (J. Comput. Appl. Math., 2024)

Decoupled algorithms for non-linearly coupled reaction-diffusion competition model with harvesting and stocking. - Muhammad Mohebujjaman; Clarisa Buenrostro; Md. Kamrujjaman; Taufiquar Khan (J. Comput. Appl. Math., 2024)

A physics-informed kernel approach to learning the operator for parametric PDEs. - Jason Kurz; Brett Bowman; M. Seman; Chad Oian; Taufiquar Khan (Neural Comput. Appl., 2024)

Decoupled algorithms and analyses for an advection-reaction-diffusion model with stocking and harvesting. - Mayesha Sharmim Tisha; Md. Kamrujjaman; Muhammad Mohebujjaman; Taufiquar Khan (Comput. Math. Appl., 2025)