Research output per year
Research output per year
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Dive into the research topics where Jungho Kim is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Meta pseudo label tabular-related regression model for surrogate modeling
Kim, S. & Kim, J., 1 Feb 2025, In: Expert Systems with Applications. 261, 125520.Research output: Contribution to journal › Article › peer-review
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Deep-learning-based inverse design of colloidal quantum dots
Jang, D., Kim, S. & Kim, J., 15 May 2024, In: Optics Communications. 559, 130384.Research output: Contribution to journal › Article › peer-review
2 Citations (Scopus) -
Integrating the strengths of cVAE and cGAN into cAAE for advanced inverse design of colloidal quantum dots
Jang, D. & Kim, J., Sept 2024, In: Journal of the Korean Physical Society. 85, 5, p. 437-447 11 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Efficient strain-modified improved nonparabolic-band energy dispersion model that considers the effect of conduction band nonparabolicity in mid-infrared quantum cascade lasers
Kim, S. & Kim, J., 11 Sept 2023, In: Optics Express. 31, 19, p. 31267-31283 17 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
Numerical comparison of quantum-confined Stark effect on emission spectra between InP- and CdSe-based colloidal quantum dots
Jang, D. & Kim, J., Nov 2023, In: Journal of the Korean Physical Society. 83, 10, p. 769-779 11 p.Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus)
Press/Media
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Researchers from Kyung Hee University Detail Findings in Technology (Meta Pseudo Label Tabular-related Regression Model for Surrogate Modeling)
3/02/25
1 item of Media coverage
Press/Media
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Maryland Industrial Partnerships (MIPS) program supports 16 technology development projects teaming Maryland companies, USM faculty
2/09/24
1 item of Media coverage
Press/Media
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Investigators from Kyung Hee University Target Quantum Dots (Deep-learning-based Inverse Design of Colloidal Quantum Dots)
29/05/24
1 item of Media coverage
Press/Media