Erich Bremer

Erich Bremer headshot

Erich Bremer

Director, Applied Informatics

HSC T3-119
Stony Brook University
Stony Brook, NY 11794
Phone: 631-444-3560
Erich.Bremer@stonybrook.edu

Interests

Linked Data, Artificial Intelligence and Machine Learning, Imaging, 3D graphics and modelling, Pathology Informatics

Selected References

  1. Sefton P, Ó Carragáin E, Soiland‐Reyes S, Corcho Ó, Garijo D, Palma R, et al. RO-Crate Metadata Specification 1.3.0. Publikationen an der Universität Bielefeld (Universität Bielefeld). 2026.
  2. Practical Uses of Solid for Medical and Health Data. 2026.
  3. Zhang Y, Abousamra S, Hasan M, Torre-Healy LA, Krichevsky S, Shrestha S, et al. Pathomics tumor-infiltrating lymphocytes maps in colorectal cancer for translational immuno-oncology. Zenodo (CERN European Organization for Nuclear Research). 2026. doi:10.5281/zenodo.21985178
  4. Linked Web Storage Protocol 1.0 W3C Working Draft. World Wide Web Consortium (W3C). 2026.
  5. BeakGraph: read-optimized RDF Graph store based on HDT/HDF5. 2026.
  6. Gaston SM, Zhang Y, Wallaengen V, Galvez A, Salcedo L, Breto A, et al. Abstract 691: Visualizing differential prostate cancer lesion growth in longitudinal MRIs of patients on active surveillance: Quantitative mapping by Habitat Risk Score and digital pathology. Cancer Research. 2026;86(7_Supplement):691. doi:10.1158/1538-7445.am2026-691
  7. dcm2rdf: Extracting metadata from DICOM medical-imaging files and representing it as RDF. 2025.
  8. Bhawsar PMS, Bremer E, Duggan MA, Chanock SJ, García‐Closas M, Saltz JH, et al. Tile Serving Without a Server to Traverse Whole Slide Imaging Data on the Web. Research Square. 2025. doi:10.21203/rs.3.rs-6256330/v1
  9. Zhang Y, Abousamra S, Hasan M, Torre-Healy LA, Krichevsky S, Shrestha S, et al. Pathomics Image Analysis of Tumor Infiltrating Lymphocytes (TILs) in Colon Cancer. Research Square. 2025. doi:10.21203/rs.3.rs-6173056/v1 PMID: 40235501
  10. Zhang Y, Gupta R, Saltz JH, Kurç T, Kaczmarzyk J, Bremer E, et al. Abstract 5315: Mapping tumor infiltrating lymphocytes in whole prostatectomy specimens to visualize and quantify the immune microenvironment of prostate cancer. Cancer Research. 2025;85(8_Supplement_1):5315. doi:10.1158/1538-7445.am2025-5315
  11. Baid U, Pati S, Kurç T, Gupta R, Bremer E, Abousamra S, et al. Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning. IEEE International Conference on Big Data (BigData). 2024:7640-7647. doi:10.1109/bigdata62323.2024.10825083
  12. Kaczmarzyk J, O’Callaghan A, Inglis F, Gat S, Kurç T, Gupta R, et al. Open and reusable deep learning for pathology with WSInfer and QuPath. npj Precision Oncology. 2024;8(1):9. doi:10.1038/s41698-024-00499-9 PMID: 38200147
  13. Baghal A, Saltz JH, Kurç T, Prasanna P, Baghal S, Hajagos J, et al. Linking The Cancer Imaging Archive and GenBank to the National Clinical Cohort Collaborative. Learning Health Systems. 2024;9(1):e10457. doi:10.1002/lrh2.10457 PMID: 39822917
  14. Foran DJ, Chen W, Kurç T, Gupta R, Kaczmarzyk J, Torre-Healy LA, et al. An Intelligent Search & Retrieval System (IRIS) and Clinical and Research Repository for Decision Support Based on Machine Learning and Joint Kernel-based Supervised Hashing. Cancer Informatics. 2024;23:11769351231223806. doi:10.1177/11769351231223806 PMID: 38322427
  15. Bhawsar PMS, Bremer E, Duggan MA, Chanock SJ, García‐Closas M, Saltz JH, et al. ImageBox3: No-Server Tile Serving to Traverse Whole Slide Images on the Web. Research Square. 2023. doi:10.21203/rs.3.rs-2864977/v1
  16. Bremer E, DiPrima T, Balsamo J, Almeida JS, Gupta R, Saltz JH. Halcyon -- A Pathology Imaging and Feature analysis and Management System. arXiv (Cornell University). 2023. doi:10.48550/arxiv.2304.10612
  17. Baid U, Pati S, Kurç T, Gupta R, Bremer E, Abousamra S, et al. Federated Learning for the Classification of Tumor Infiltrating Lymphocytes. arXiv (Cornell University). 2022. doi:10.48550/arxiv.2203.16622
  18. Foran DJ, Durbin EB, Chen W, Sadimin ET, Sharma A, Banerjee I, et al. An Expandable Informatics Framework for Enhancing Central Cancer Registries with Digital Pathology Specimens, Computational Imaging Tools, and Advanced Mining Capabilities. Journal of pathology informatics. 2022;13:5. doi:10.4103/jpi.jpi_31_21 PMID: 35136672