MSc in Applied Immunology by Advanced Study | University of Toronto
Immunology | Computational Biology | Inflammatory Bowel Disease | Liver Transplantation
Using multi-omics, machine learning, and computational biology to study immune disease.
Pediatric IBD, immune profiling, patient-derived organoids, microbiome platforms, and computational biology.
About
Joseph Katz is a current MSc student in Applied Immunology by Advanced Standing at the University of Toronto and SickKids, supervised by Dr. Eytan Wine. His work sits at the intersection of pediatric inflammatory bowel disease, computational immunology, multi-omics, microbiome platforms, metabolomics, proteomics, machine learning, and translational research. He is interested in connecting immune mechanisms, patient-derived models, and clinical data to better understand inflammatory disease.
Experience
Causal and mechanistic dissection of ultra-processed food-driven gastrointestinal inflammation using patient-derived organoids, microbiome platforms, barrier physiology, immune profiling, and integrative in vivo models.
Developed a workflow for human liver IMC preprocessing, single-cell segmentation, immune-cell phenotyping, and dimensional analysis including UMAP and t-SNE.
Designed a Python-based multi-agent system simulating a liver-transplant selection committee, using retrieval augmented generation and clinical donor data to support decision-making.
Studied genetic and molecular risk factors for IBD through DNA extraction, DNA quantification, ELISA assays, cohort tables, visualization tools, and comparative/regression analyses in Excel and R.
Projects
Integrative research direction connecting immune profiling, microbiome platforms, patient-derived organoids, and computational modeling for pediatric inflammatory disease.
Python workflow for IMC preprocessing, segmentation, phenotyping, dimensional analysis, and immune-environment comparison in liver allograft fibrosis.
Exploratory project space for microbiome, metabolomics, and proteomics datasets connected to gut inflammation and translational immunology.
Biomedical AI tools including multi-agent clinical reasoning prototypes, retrieval augmented generation, and structured evaluation workflows for research settings.
Skills
Python, R, RStudio, numpy, pandas, Excel
Data cleaning, visualization, regression analysis, statistical modeling, dimensionality reduction, t-SNE, UMAP
Single-cell segmentation, Mesmer, immune-cell phenotyping, multi-omics exploration, cohort analysis
IBD, immunogenetics, immune profiling, ELISA, pediatric inflammatory disease, barrier physiology
CrewAI, retrieval augmented generation, PowerPoint, ggplot2, tidyverse, GitHub Pages
Education
University of Toronto and SickKids, Division of Gastroenterology, Hepatology and Nutrition; Cell and Systems Biology. Supervisor: Dr. Eytan Wine.
University of Toronto. Double major in Physiology and Immunology. Graduated with High Distinction. Immunology Honours Thesis.
Upper Canada College. Advanced specialization in Physics, Math, and Economics.
Presentations / Research Outputs
First-author poster presentation for the Donor Agent project, United Health Network ORT Summer Student Research Program, 2025.
University of Toronto IMM450 Honours Thesis. Add final title, supervisor, and abstract details here.
Placeholder for internal lab talks, journal clubs, and project updates.
No publications listed in the CV yet. Add peer-reviewed manuscripts, preprints, or abstracts here when available.
Achievements
Recognized for achieving a cumulative GPA of 3.50 or higher.
Honored for academic achievement during the 2021-2022 school year.
Awarded to students in the top 10% of academic standing.
Recognized for research comparing naturopathic remedies and antibiotics against E. coli and Staphylococcus aureus growth.
Placeholder for future conferences, fellowships, or presentation awards.
Contact
I am open to research collaborations, computational biology projects, and academic opportunities in immunology, multi-omics, machine learning, and translational medicine.