Nadeem Lab aims to analyze, interpret, and infer novel insights from biomedical data at multiple scales (macro: radiology/ surgery, meso: pathology, micro: genomics/ transcriptomics/ proteomics/ metabolomics) for improving patient outcomes. We use advanced mathematical and machine learning techniques to drive this analysis. The lab focuses on building user-friendly tools that seamlessly fit into the clinical workflow and facilitate accurate and timely diagnosis/ prognosis/ decision making while aiding in novel biomarker discovery.
Physics-ArX library is now public on our GitHub. It provides (smart) physics-based data augmentation tools for robust quantification of CT and CBCT images during radiotherapy, as shown in our PMB'21 (generalizable cross-modality esophagus segmentation) and Medical Physics'21 (multitask CBCT-to-CT translation and OAR segmentation) papers.
Joseph Marino
(senior data scientist)
joins the lab.
James Mathews (senior data scientist), Rami Vanguri (senior data scientist), Gunjan Shrivastava (data scientist), and Eliram Nof (postdoc) join the lab.
Awarded $4.2M MSKCC DigITs funding for research and development of "institutional multiplex image analysis pipelines for biomarker quantification".
Invited MSK Hospital Research Forum talk on "Spatial Profiling for Quantitative and Predictive Biomarkers".
(Principal investigator)
(Senior Data Scientist)
(Senior Data Scientist)
(Senior Data Scientist)
(Data Scientist)
(Postdoc)