Research Themes
Computational Image & Video Processing
Investigating efficient data acquisition and reconstruction using Compressed Sensing (CS) frameworks. This research focuses on multiscale block-based sampling and iterative reconstruction algorithms for high-resolution imaging and dynamic video sequences.
Featured Publications (Total: 7):
- S. Mun and J. E. Fowler, "Motion Compensated Compressed Sensing for Dynamic MRI", In Proceedings of the Internatio...
- S. Mun, "Block Compressed Sensing of Images and Video". Thesis at: Mississippi State University, 2012
- S. Mun and J. E. Fowler, "DPCM for Quantized Block-Based Compressed Sensing of Images", In Proceedings of the Euro...
Molecular Dynamic Simulations
Developing high-fidelity interatomic potentials and parallel molecular dynamics frameworks to study the interface and mechanical properties of composite materials. This work enables the predictive modeling of polymers, hydrocarbons, and complex metallic alloys at the atomic scale.
Featured Publications (Total: 13):
- Kefan Chen, Sungkwang Mun, Michael I Baskes, Mark Horstemeyer, and Bin Li, "Atomistic study of intermetallics of f...
- D. Seely, B. Huddleston, Sungkwang Mun, A. Vo, N. Lee, D. Dickel, and K. Limmer, "Atomistic study on diffusion and...
- M. S. Nitol, Sungkwang Mun, D. E. Dickel, and C. D. Barrett, "Unraveling mg< c+ a> slip using neural network...
Data-Driven Surrogate Modeling
Utilizing machine learning surrogate models to optimize additive manufacturing processes and structural designs. Our frameworks aim to reduce the computational cost of design exploration in high-dimensional spaces.
Featured Publications (Total: 1):
- Daniel Johnson, Luke Peterson, Gehendra Sharma, Sungkwang Mun, Youssef Hammi, Tonya Stone, Jesse Sherburn, and Dan...
Machine Learning in Combustion
Applying machine learning techniques, including feed forward neural networks (FFNNs), to predict spray characteristics and engine combustion performance. This research focuses on high-fidelity modeling of complex reactive flows.
Featured Publications (Total: 2):
- J. Hwang, P. Lee, Sungkwang Mun, I. K. Karathanassis, F. Koukouvinis, F. Tagliante, T. Nguyen, and L. Pickett, "A ...
- J. Hwang, P. Lee, Sungkwang Mun, I. K. Karathanassis, P. Koukouvinis, L. M. Pickett, and M. Gavaises, "Machine-lea...
Advanced Manufacturing
Focusing on the development of digital twins and physics-informed neural networks (PINNs) for real-time monitoring of additive manufacturing processes. This research enables the predictive modeling of material behavior during high-speed manufacturing cycles.
Featured Publications (Total: 4):
- Haiye Xie, Joshua Bassett, Sara Adibi, Doyl Dickel, Gehendra Sharma, Jonathan Storey, Haley Dozier, and Sungkwang ...
- Daniela F Tellkamp, Nayeon Lee, Gehendra Sharma, Sungkwang Mun, Daniel Johnson, and Luke Peterson, "Structural des...
- Gehendra Sharma, Joshua Bassett, Justin Xie, Jonathan Storey, Han-Gyu Kim, Tonya W Stone, Haley Dozier, and Sungkw...
Advanced Maintenance
Implementing Prognostics and Health Management (PHM) frameworks and predictive maintenance strategies for industrial systems. This work utilizes data-driven diagnostics to optimize the reliability and maintenance cycles of complex engineering assets.
Featured Publications (Total: 3):
- Ayantha Senanayaka, Philku Lee, Nayeon Lee, Charles Dickerson, Anton Netchaev, and Sungkwang Mun, "Enhancing the a...
- Ayantha Senanayaka Mudiyanselage, Qing Liu, Nayeon Lee, Sungkwang Mun, Amin Amirlatifi, Joseph Jabour, Thomas Arno...
- Sungkwang Mun, Joonsik Hwang, Linkan Bian, TC Falls, and W Glenn Bond, "Ensemble learning for fault condition pred...
Student Mentoring & Advising
Major Advising & Mentoring
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Justin XieMaster's Student (Major Advisor) Graduated Fall 2025Thesis: "Physics Informed Neural Networks for Additive Manufacturing"Selected as 2nd place winner in the Master’s Poster competition at the Spring 2024 Graduate Research Symposium.
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Joshua BassettMaster's Student (Co-Major Advisor) Graduated Fall 2025Thesis: "Calibration and validation of the thermal finite element model for ER-120S-G wire arc directed energy deposition using infrared cameras and thermocouples"
Undergraduate Research Mentoring
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Zijie ChenComputer Science (Undergraduate Researcher) Award WinnerProject: Autoencoder-based Data Denoising for Infrared Camera Images in Additive Manufacturing. Advised under the support of an ERDC-sponsored additive manufacturing project. Selected as Overall Winner in Data Science Research at the Spring 2024 Undergraduate Research Symposium.
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Minjae ChoMechanical Engineering (Undergraduate Researcher) Award WinnerProject: Development of Parameter Dependent conditional Generative Adversarial Network (PDcGAN) Model for Multi-Phase Flow Prediction. Selected as Overall Winner in Data Science Research at the Spring 2023 Undergraduate Research Symposium. (See MSU Data Science Undergraduate Research)
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Minjae ChoMechanical Engineering (Undergraduate Researcher)Project: Development of Generative Adversarial Network (GAN) Model for Multi-Phase Flow Prediction. Co-advised with Dr. Joonsik Hwang. Prepared a poster for the Spring 2022 Undergraduate Research Symposium, selected as a Physical Sciences and Engineering Top Rated Project.
Graduate Committee Service
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Henan ZhouPh.D. Student (Mechanical Engineering)Dissertation: "Interatomic Potential of Multiphase Materials Using Modified Embedded Atom Method (MEAM) and Artificial Neural Network (RANN)"
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Ethan HolderMaster's Student (Mechanical Engineering)Thesis: "Interactions Between Different Deformation Mechanisms in Magnesium"
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Daniela TelkampMaster's Student (Biomedical Engineering)Thesis: "Surrogate Model-based Design Optimization of a Mobile Deployable Structure for Overpressure Load and Vehicular Impact Mitigation"