*: Corresponding Author, ^: Co-first author.
My research focuses on high-dimensional statistical methodology, sufficient dimension reduction (SDR), and statistical deep learning. I develop tools for spatial statistics and clinically motivated data analysis, including spatial transcriptomics, single-cell multiomics, and immuno-oncology.
[J1] Shin, J., Shin, S. J., & Bang, S. (2025). "A least distance estimator for a multivariate regression model using deep neural networks," Journal of Statistical Computation and Simulation, 95(10), 2308–2325. DOI: 10.1080/00949655.2025.2492195.
[J2] Shin, J., Kwak, S., Shin, S. J., & Bang, S. (2024). "Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural network," Statistics and Computing, 34(102). DOI: 10.1007/s11222-024-10418-4.
[J3] Shin, J., & Shin, S. J. (2024). "Concise overview of principal support vector machine," Communications for Statistical Applications and Methods, 31(2), 235–246. DOI: 10.29220/CSAM.2024.31.2.235.
[J4] Shin, J., Kang, J., & Bang, S. (2024). "Penalized least distance estimator in the multivariate regression model," The Korean Journal of Applied Statistics, 37(1), 1–12. DOI: 10.5351/KJAS.2024.37.1.001.
[J5] Kim, H., & Shin, J.* (2022). "The LSTM based algorithm for detecting vessel abnormal behaviors," Korean Journal of Military Art and Science, 78(2), 471–495. DOI: 10.31066/kjmas.2022.78.2.017.
[J6] Shin, J., Kim, H., & Shin, S. J. (2021). "A comparison study of inverse censoring probability weighting in censored regression," The Korean Journal of Applied Statistics, 34(6), 957–968. DOI: 10.5351/KJAS.2021.34.6.957.
[B1] Shin, J., Kang, J., Lee, Y., & Bang, S. (2022). Introduction to Statistics and its Application with R. Kyowoo. Link to Publisher.
[C1] Alshaibani, A. B., Carrell, S. T., Tseng, L. H., Shin, J., & Quinn, A. (2020). "Privacy-Preserving Face Redaction Using Crowdsourcing," Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 8, 13–22. DOI: 10.1609/hcomp.v8i1.7459.
[C2] Denlinger, N., Song, N., Shin, J, et al. (2025). "Safety and immunomodulatory effects of siltuximab prophylaxis prior to standard of care CD19 directed CAR T-cell therapy for B-cell lymphomas," Blood (67th ASH Annual Meeting Abstracts), 146, 2385. DOI: 10.1182/blood-2025-2385.
[S1] Shin, J., Shin, S. J., & Artemiou, A. (2024). "The R package psvmSDR: A unified Algorithm for Sufficient Dimension Reduction via Principal Machines," Revision submitted to R Journal. arXiv: 2409.01547 | Package on CRAN.
[S2] Shin, J., & Shin, S. J. (2025). "Penalized Principal Machines for Sufficient Dimension Reduction and Its Efficient Computation," Revision invited from Statistical Computation & Data Analysis.
[S3] Shin, J., Chung, D., Shin, S. J., & Bang, S. (2025). "A Unified Framework of Penalized Deep Composite Quantile Regression for Simultaneous Function Estimation and Variable Selection," Under review.
[S4] Xie, J.^, Shin, J.^, et al. (2026). "SpaDesign: Simulation Based Framework for Determining Sequencing Depth for Spatial Transcriptomics Experiments," Under review.
[S5] Cha, J., Lee, J., Cho, J., & Shin, J. (2025). "FOSSIL: Regret-minimizing weighting for robust learning under imbalance and small data," Under review. arXiv: 2509.13218.
[S6] Cha, J., Kim, Y., Shin, J., et al. (2025). "Optimization of Bregman-Variational Learning Dynamics," Under review.
[S7] Cha, J., Cho, J., Lee, J., Shin, J., & Ryu, J. (2025). "A Statistical Testing Framework with Iterative Scenario Sampling for Distributionally Robust Inverse Optimization," Under review.
[P1] Shin, J., & Chung, D. (2026). "spaDesign2: A Statistical Framework for Power Analysis in Multi-Sample Spatial Transcriptomics," In preparation.
[P2] Shin, J., Chung, D., & Bang, S. (2026). "Sparse Nonlinear Classifier via Penalized Deep Support Vector Machine," In preparation.
[P3] Denlinger, N.^, Shin, J.^, Song, N., et al. (2026). "Phase I Study Assessing The Safety and Immunomodulatory Effects of Prophylactic Siltuximab Prior to Standard of Care CD19 Directed CAR Therapy," In preparation.
2026 - Invited Participant, IMS New Researchers Conference (NRC), UMass Amherst, MA by the Institute of Mathematical Statistics (IMS).
2025 — Selected Participant (Lightning Talk Presenter), 1st IMS International New Researchers Conference (INRC), Seville, Spain.
2025 — Best Ph.D. Dissertation Award, College of Political Sciences, Korea University.
2024 — Best Student Paper Prize, The Korean Statistical Society.
2023 — Letter of Commendation for simulation support, ROK Army Chief of Staff.
[Invited Talk] "Penalized Principal Machines for Sufficient Dimension Reduction and Its Efficient Computation," 1st IMS INRC, Seville, Spain (Dec. 2025).
[Invited Talk] "Principal Machine: A Unified and Computationally Efficient Approach to SDR," Purdue University, IN, USA (Apr. 2025).
[Poster] "spaDesign2: A statistical framework for power analysis in multi-sample spatial transcriptomics," 2026 Annual Joint Biostatistics Symposium, Columbus, OH (Apr. 2026).
[Oral] "Computationally Efficient Sparse Sufficient Dimension Reduction via Least Squares Support Vector Machine and its Extensions," CFE-CMStatistics-2024, King's College London, London, UK (Dec. 2024).