About

Seongmin Park is an Assistant Professor in the Department of Psychology, the School of Neuroscience, and the Department of Biomedical Engineering at Virginia Tech. He is the Principal Investigator of the Computational Cognitive Neuroscience Lab. His research focuses on neural mechanisms of learning and decision-making, exploring how the brain learns from past experiences to improve future decisions. He investigates how the brain extracts the underlying structure of events to build map-like representations of the world, which aid in generalization and making novel decisions. Additionally, his work examines neural computations underlying social decision-making, specifically how the brain determines what to learn, whom to learn from, and how to utilize that information for decision-making with others. Dr. Park earned his Ph.D. from the Korea Advanced Institute of Science & Technology (KAIST) in 2012. His research aims to understand the neural basis of cognition and social behavior through computational approaches.

Research topics

• Internal medicine
• Materials science
• Medicine
• Biology
• Nanotechnology
• Physics
• Gastroenterology
• Microbiology
• Bioinformatics
• Chemistry
• Cancer research
• Photochemistry
• Optics
• Immunology
• Biomedical engineering
• Engineering
• Biochemistry

Selected publications

• Tumor-targeted redox-regulating and antiangiogenic phototherapeutics nanoassemblies for self-boosting phototherapy

  Biomaterials · 2023 · 19 citations

  • Cancer research
  • Materials science
  • Chemistry
  DOI

• Recent advances in optical imaging through deep tissue: imaging probes and techniques

  Biomaterials Research · 2022 · 124 citations

  • Nanotechnology
  • Biomedical engineering
  • Materials science

  Optical imaging has been essential for scientific observations to date, however its biomedical applications has been restricted due to its poor penetration through tissues. In living tissue, signal attenuation and limited imaging depth caused by the wave distortion occur because of scattering and absorption of light by various molecules including hemoglobin, pigments, and water. To overcome this, methodologies have been proposed in the various fields, which can be mainly categorized into two stategies: developing new imaging probes and optical techniques. For example, imaging probes with long wavelength like NIR-II region are advantageous in tissue penetration. Bioluminescence and chemiluminescence can generate light without excitation, minimizing background signals. Afterglow imaging also has high a signal-to-background ratio because excitation light is off during imaging. Methodologies of adaptive optics (AO) and studies of complex media have been established and have produced various techniques such as direct wavefront sensing to rapidly measure and correct the wave distortion and indirect wavefront sensing involving modal and zonal methods to correct complex aberrations. Matrix-based approaches have been used to correct the high-order optical modes by numerical post-processing without any hardware feedback. These newly developed imaging probes and optical techniques enable successful optical imaging through deep tissue. In this review, we discuss recent advances for multi-scale optical imaging within deep tissue, which can provide reseachers multi-disciplinary understanding and broad perspectives in diverse fields including biophotonics for the purpose of translational medicine and convergence science. Methodologies for multi-scale optical imaging within deep tissues are discussed in diverse fields including biophotonics for the purpose of translational medicine and convergence science. Recent imaging probes have tried deep tissue imaging by NIR-II imaging, bioluminescence, chemiluminescence, and afterglow imaging. Optical techniques including direct/indirect and coherence-gated wavefront sensing also can increase imaging depth.

  DOI

• Influence of proton pump inhibitor or rebamipide use on gut microbiota of rheumatoid arthritis patients

  Lara D. Veeken · 2020 · 33 citations

  • Medicine
  • Microbiology
  • Gastroenterology

  OBJECTIVE: Patients with RA commonly use gastrointestinal (GI) protective drugs for treatment and prevention of drug-associated GI injuries. However, how these drugs affect the gut microbiota in RA patients remains unknown. The objective of this study was to examine the gut microbiota of RA patients according to use of GI protective drugs such as proton pump inhibitors (PPIs), histamine 2-receptor antagonists and rebamipide. METHODS: Faecal samples were obtained from 15 healthy controls and 32 RA patients who were receiving PPI, histamine 2-receptor antagonist or rebamipide. Bacterial DNA was extracted from the faecal samples and 16S rRNA sequencing was performed. Microbial composition and function were analysed using Quantitative Insights Into Microbial Ecology and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States. RESULTS: RA patients exhibited reduced diversity and altered composition of the gut microbiota compared with healthy controls. The gut microbiota of RA patients receiving acid-suppressing drugs, particularly PPIs, was distinct from that of RA patients receiving rebamipide (PPI vs rebamipide, P = 0.005). Streptococcus was enriched in RA patients receiving PPI, while Clostridium bolteae was enriched in RA patients receiving rebamipide. The gut microbiota of PPI users was abundant with microbial functional pathway involved in the production of virulence factors. This featured microbial function was positively correlated with relative abundance of Streptococcus, the differentially abundant taxa of PPI users. CONCLUSION: The gut microbiota of RA patients receiving PPIs was distinguishable from that of those receiving rebamipide. The enriched virulent function in the gut microbiota of PPI users suggests that inappropriate PPI use may be harmful in RA patients.

  DOI

Frequent coauthors

• Hesham Rakha

  Virginia Tech

  57 shared

• Kyoungho Ahn

  Virginia Tech

  29 shared

• Je‐Wook Yu

  Yonsei University

  20 shared

• Sujeong Hong

  16 shared

• Inhwa Hwang

  Yonsei University

  13 shared

• Kevin Moran

  H3D (United States)

  8 shared

• Jungmin Yang

  Yonsei University

  7 shared

• Eunju Lee

  National Institutes of Health

  7 shared

Education

• Ph.D.

  Korea Advanced Institute of Science & Technology (KAIST)

  2012

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