Tahsin Khajah

Professor

Phone: 903.566.7245
Email: tkhajah@uttyler.edu
Building:   RBN 3010
Department: Mechanical Engineering

Degrees

• B.S., Mechanical Engineering, Razi University, Kermanshah, Iran 2001
• M.S.M.E., Mechanical Engineering, Sharif University of Technology, Tehran, Iran, 2006
• Ph.D., Mechanical Engineering, Old Dominion University, Norfolk, VA, 2015

Biography

Courses Taught

• MENG 3309 - Mechanical Systems Design
• MENG 5328 - Advanced Finite Element Method
• MENG 5333 - Mechanics of Composite Materials
• MENG 4215 – Senior Capstone Design I
• MENG 4216 – Senior Capstone Design II

Research Interests

I am interested in developing mathematical models and numerical methods for wave propagation analyses as well as evolutionary optimization.  I have developed both accurate and efficient methods to perform single- and multiple-scattering analyses utilizing high order absorbing boundary conditions and On Surface Radiation Conditions. These developments were employed to design and tune acoustic metamaterials for sensing and focusing applications and to generate accurate ultrasound images while accounting for highly heterogenous biological media. My research has been supported by National Science Foundation (NSF), National Institute of Health (NIH) and U.S Department of Agriculture (USDA). I also worked in industry for more than a decade prior to joining University of Texas at Tyler.

Research Page

Awards & Honors

• President’s Scholarly Achievement Award, 2025
• Teaching & Learning Award, UT Tyler, 2020
• ASEE-GSW Outstanding Young Faculty Award, 2019 
• Crystal Quill Award, 2019

Selected Publications

1. Öğüç, M., Okyar, A.F., Khajah, T. (2025) FeVAcS: A package for visualizing acoustic scattering from 1D periodic obstacles, Software Impacts, 24, 100756, https://doi.org/10.1016/j.simpa.2025.100756
2. Acosta, S., Palacios, B., Khajah, T. (2025). A new interpolated pseudodifferential preconditioner for the Helmholtz equation in heterogeneous media. SIAM Journal on Scientific Computing, 47 (2), A1017-A1039, https://doi.org/10.1137/24M1642184 
3. Khajah, T. (2024). Iterative On Surface Radiation Conditions for fast and reliable single and multiple scattering analyses of arbitrarily shaped obstacles. Computer Methods in Applied Mechanics and Engineering, 420, 116715, ISSN 0045-7825, https://doi.org/10.1016/j.cma.2023.116715
4. Khajah, T. & Acosta, S. (2024). Method of virtual sources using on-surface radiation conditions for the Helmholtz equation. Engineering Analysis with Boundary Elements, 159, 342-351, ISSN 0955-7997, https://doi.org/10.1016/j.enganabound.2023.12.008
5. Khajah, T. & Natarajan, S. (2023). Layup optimization of tow-steered composite laminates for maximum fundamental frequency and flutter speed using differential evolution. Composite Structures, 310,116748,ISSN 02638223, https://doi.org/10.1016/j.compstruct.2023.116748
6. Antoine X. & Khajah, T. (2022). Standard and Phase Reduced Isogeometric On-Surface Radiation Conditions for acoustic scattering analyses. Computer Methods in Applied Mechanics and Engineering, 392,114700, ISSN 0045-7825,  https://doi.org/10.1016/j.cma.2022.114700
7. Atroshchenko, E., Hurtado, A. C., Anitescu, C., Khajah, T. (2022). Isogeometric collocation for acoustic problems with higher-order boundary conditions. Journal of Wave Motion, 110,102861, ISSN 0165-2125, https://doi.org/10.1016/j.wavemoti.2021.102861
8. Dsouza, S. M., Khajah, T., Antoine, X., Bordas, S. P., Natarajan, S. (2022). NURBS and Lagrange approximations for time-harmonic acoustic scattering: convergence, accuracy, absorbing boundary conditions. Mathematics and Computer Modeling of Dynamical Systems, 27(1), 263-294, https://doi.org/10.1080/13873954.2021.1902355
9. Khajah, T., Liu, L., Song, C., Gravenkamp, H. (2021). Shape Optimization of Acoustic Devices using the Scaled Boundary Finite Element Method. Wave Motion, 104, 102732, https://doi.org/10.1016/j.wavemoti.2021.102732
10. Ummidivarapua, V. K., Vorugantia, H. K., Khajah, T., Bordas, S. P. A. (2020). Isogeometric shape optimization using Teaching Learning-Based Optimization (TLBO) algorithm. Computer Aided Geometric Design, 80, 101881, https://doi.org/10.1016/j.cagd.2020.101881

Google Scholar

My research is driven by a deep desire to model and manipulate wave propagation in complex, heterogeneous media. I have focused on improving the accuracy of numerical methods, reducing their computational cost, and enhancing their flexibility for the design and development of metamaterials. These efforts have led to the development of cutting-edge numerical methods and novel algorithms that significantly improve the accuracy and speed of analyses and optimization for problems involving wave propagation.

It is now possible to model ultrasound wave propagation in the human body without relying on unrealistic assumptions that previously limited their accuracy and applicability. We can determine the optimal, patient-specific insonation profile for targeting tumors or stimulating the brain within minutes using personal computer. My current research interests span a broad range of topics in Computational Mechanics, including but not limited to:

• Computational Acoustics: We developed novel high-order methods that reduce geometric, pollution, and domain truncation errors, resulting in a highly accurate platform for wave propagation analysis. This method was later extended to perform multiple scattering analyses, offering unmatched flexibility necessary for accurate shape and topology optimization. Additionally, we developed low-cost methods for performing analyses in reduced spatial dimensions and eliminated the need for meshing between scatterers, significantly enhancing both flexibility and speed. This patented technology enables us to perform reliable analyses and optimization at a fraction of the cost of methods in use today.

Figure 1- Fast multiple scattering analyses using Iterative On Surface Radiation Conditions (ITOSRC) which reduces the computational time and cost to fraction of methods in use today.

• Metamaterials: Metamaterials enable the manipulation of waves in ways that go beyond what occurs naturally. These materials can function as lenses, black holes, energy harvesters, sensors, and more. They enhance the performance of devices that rely on wave propagation, such as ultrasound imaging and focusing, sonar, and sensors. The challenge in developing metamaterials lies in the design phase, as the original concept must be customized for a specific practical application. This customization is complex and requires optimization processes that involve running analyses thousands of times, each time adjusting the metamaterial design. Therefore, fast, flexible, and reliable analysis methods are crucial to making this customization possible, beyond what is available commercially. At UT Tyler, we have developed the necessary methods and paired them with optimization techniques to design and test customized metamaterials successfully.

Figure 2 Novel methods developed to facilitate metamaterial customization.

• Ultrasound imaging and focusing: We have developed a novel method to simulate ultrasound wave propagation inside the human body accounting for variation of wave speed. By using a new and untapped set of mathematical and computational tools, we have improved the speed and automation of ultrasound simulations, particularly in the presence of highly heterogeneous biological media, such as those encountered in ribcage and skull imaging and focusing. This development has the potential to transform the use of ultrasound in both imaging and therapeutic applications, significantly enhancing its usability and affordability. Preliminary results are shown in the figure below.

Figure 3 - Transmission ultrasound tomography using pseudo-differential sweeping method capable of inverting diffraction effects.

We have received funding from the USDA (PI - $65,598), NSF (Co-PI - $828,570), and NIH (PI - $481,400) to develop and utilize innovative computational methods and metamaterials. I currently have two pending proposals, NIFA (PI - $750,000) and NIH R21 (PI - $524,000). 

Future Research Directions

Looking ahead, my future research will focus on several key areas:

1. Metamaterial design for transcranial ultrasound treatment: The ultrafast and flexible methods we developed for ultrasound imaging and focusing enable patient-specific metamaterial development to overcome the challenges posed by the presence of the skull. These metamaterials eliminate the blocking effect of the skull, allowing ultrasound waves to pass through as if the skull were not there. This innovation facilitates various therapeutic procedures, such as tumor ablation and brain stimulation.
2. Develop novel sensing technologies: The flexibility of the methods we developed allows us to optimize and improve various devices that rely on wave propagation, including sensors. We can now decouple wave energy at specific frequencies and detect it using low-cost equipment. This capability enables the development of affordable sensing modalities that were previously not possible.
3. Mathematical and computations method:  The development of cutting-edge mathematical models and efficient, accurate computational platforms is the foundation of my research. This work will continue to provide us with the essential tools needed for future advancements.

Curriculum Vitae