Research & Publications

I. Statistical Methodology

- Peer-reviewed journal articles

1. psvmSDR: An R package for a unified algorithm for sufficient dimension reduction via principal machines
   J. Shin, S. J. Shin, A. Artemiou (2026). The R Journal, in press. arXiv · CRAN
2. A least distance estimator for a multivariate regression model using deep neural networks
   J. Shin, S. J. Shin, S. Bang (2025). Journal of Statistical Computation and Simulation, 95(10), 2308–2325. DOI
3. Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural network
   J. Shin, S. Kwak, S. J. Shin, S. Bang (2024). Statistics and Computing, 34, 102. DOI
4. Concise overview of principal support vector machine
   J. Shin, S. J. Shin (2024). Communications for Statistical Applications and Methods, 31(2), 235–246. DOI

- Peer-reviewed conference proceeding

1. Privacy-preserving face redaction using crowdsourcing
   A. B. Alshaibani, S. T. Carrell, L.-H. Tseng, J. Shin, A. Quinn (2020). Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 8, 13–22. DOI

- Book

1. Introduction to Statistics and Its Application with R
   J. Shin, J. Kang, Y. Lee, S. Bang (2022). Kyowoo. ISBN 979-11-251-0339-4. Book page

- Submitted or under review

1. Penalized principal machines for sufficient dimension reduction and its efficient computation
   J. Shin, S. J. Shin (2025). Revision submitted to Computational Statistics & Data Analysis. ppmSDR on CRAN
2. SpaDesign: Simulation-based framework for determining sequencing depth for spatial transcriptomics experiments
   J. Xie†, J. Shin†, H. Jeon, W. Chang, K. J. Jung, Y. Jeon, Z. Li, Q. Ma, D. Chung (2026). Revision invited from PLOS Computational Biology. †Equal contribution.
3. Penalized deep support vector machines for nonlinear classification and variable selection
   J. Shin, D. Chung, S. Bang (2026). Under review.
4. A unified framework of penalized deep composite quantile regression for simultaneous function estimation and variable selection
   J. Shin, D. Chung, S. J. Shin, S. Bang (2025). Under review.

- In preparation

1. spaCraft: Calibrated power analysis and sample-size planning for multi-sample spatial transcriptomics
   J. Shin, D. Chung (2026). In preparation. GitHub
2. Circular data analysis in spatial omics
   J. Shin, A. Gupta, P.-H. Mao, K. Thakkar, J. Y. Kim, Y. Cho, J. Yoo, T. Amireddy, K. J. Jung, H. Jeon, J. Xie*, D. Chung* (2026). In preparation.
3. CellPacman: An interpretable machine-learning pipeline for phenotypic discovery and dose-response characterization of Cell Painting assays
   M. Kotian†, J. Shin†, et al., D. Chung (2026). In preparation. Co-first author.

II. Biomedical and Collaborative Research

- Peer-reviewed conference abstracts

1. Biomarker-driven exploratory clustering of cytokine and hematologic profiles in a Phase II trial of metronomic chemotherapy plus cemiplimab in R/M HNSCC
   M. R. Bonomi, J. Shin, et al. ESMO 2026 Congress, Madrid, Oct. 2026. Accepted e-Poster, Abstract No. 4631.
   Contribution: Lead biostatistician; UMAP-HDBSCAN clustering, cluster characterization, and biomarker-survival analyses.
2. Cytokine analysis in a Phase II trial of metronomic carboplatin/paclitaxel plus cemiplimab for recurrent/metastatic head and neck squamous cell carcinoma
   M. R. Bonomi, J. Shin, et al. 2026 ASCO Annual Meeting, Chicago, May 2026. Abstract No. 6044. DOI
   Contribution: Lead biostatistician; longitudinal cytokine analyses, response-group comparisons, multiplicity-adjusted testing, and survival analyses.
3. Safety and immunomodulatory effects of siltuximab prophylaxis prior to standard-of-care CD19-directed CAR T-cell therapy for B-cell lymphomas: Final Phase I trial results
   N. Denlinger, N. Song, et al., J. Shin, et al., T. Voorhees. 67th ASH Annual Meeting, Dec. 2025. Published abstract in Blood, 146, 2385. DOI
   Contribution: Lead biostatistician; time-matched cohort comparisons of spectral flow cytometry, cytokine, response, and survival data.
4. Decoding immune suppression in Merkel cell carcinoma through integrated spatial transcriptomics and multiplex proteomics
   S. Priya, Y. Koguchi, R. Teodorescu, K. J. Jung, J. Shin, et al., M. P. Rubinstein. SITC 40th Annual Meeting, Houston, Nov. 2025. Publication No. A106. Publication
   Contribution: Lead biostatistician; integrated spatial transcriptomics and multiplex proteomics analysis.

- Clinical manuscripts in preparation

1. Phase I study assessing the safety and immunomodulatory effects of prophylactic siltuximab prior to standard-of-care CD19-directed chimeric antigen receptor therapy
   N. Denlinger†, J. Shin†, et al. (2026). In preparation. Co-first author.
   Contribution: Lead statistician; all statistical analyses including mixed models, survival analysis, multivariable regression, and longitudinal analysis.
2. Clinical and genomic predictors of hyperprogression in recurrent/metastatic head and neck cancer: Discovery and validation
   N. Mladkova-Suchy†, K. Dibs†, J. Shin, et al. (2026). In preparation.
   Contribution: Lead biostatistician responsible for all statistical analyses.

* Corresponding author. † Equal contribution where indicated. Publication status and wording follow the attached CV.

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