Skip to content
View storaged's full-sized avatar

Highlights

  • Pro

Block or report storaged

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
storaged/README.md

Krzysztof Gogolewski

I work in computational biology, focusing on spatial data and how we can model biological structure in a way that is both statistically sound and biologically meaningful.

Recently, I have been building my own research direction around spatial omics and multimodal data integration, with a particular interest in the tumour immune microenvironment.


Research interests

Most of my work sits somewhere between statistics, machine learning, and biology. In practice, this includes:

  • modelling spatial organisation of cells in tissue
  • probabilistic approaches to biological systems
  • learning representations from multiplex imaging data (IMC, mIF)
  • combining imaging with other modalities (e.g. transcriptomics)

What I care about most is that the models we build are not only predictive, but also interpretable and usable in real biological settings.


Research trajectory

My background is in statistical modelling and computational genomics. Earlier in my work I focused on:

  • modelling epidemic dynamics (COVID-19)
  • inference problems in population genetics and genome structure
  • analysis of genomic variation and structural rearrangements

Over time, my interests shifted towards spatially resolved data, where classical statistical approaches meet challenges related to structure, scale, and heterogeneity.

My current work builds on this foundation, combining probabilistic modelling with modern machine learning to better understand spatial organisation in biological systems.


Current work

SpaceLet

A probabilistic framework for describing spatial patterns of immune infiltration in tumours.

I have been involved in shaping the modelling approach and supervising the work.

(manuscript in preparation)


ImmuVis

Work on representation learning for multiplex imaging data, with a focus on uncertainty-aware models.

My role here is mostly around the methodological direction and overall modelling ideas.

(manuscript in preparation)


Ongoing activities

I am also building a small research group around spatial and multimodal data analysis.


Publications

List of my works is up-to-date at Google Scholar


Collaboration

I am always happy to talk to people working on related problems — especially around spatial data, imaging, and probabilistic modelling.

I also supervise students (BSc/MSc) and am gradually building a team in this area.


Contact

University of Warsaw Faculty of Mathematics, Informatics and Mechanics

ORCID: https://orcid.org/0000-0001-5523-5198

Popular repositories Loading

  1. UW-SysBiol-Project1 UW-SysBiol-Project1 Public

    Geometric Fisher Model

    Python 3 3

  2. ZBD1 ZBD1 Public

    task 1 - Hibernate basics

    1

  3. metabolic-landscape metabolic-landscape Public

    R 1

  4. WBO WBO Public

    Introduction to Computational-Biology

  5. Minisatelite Minisatelite Public

    Mini-script mapping minisatelite sequence onto color-coded stripes

    Python

  6. ASM-zadanie-2 ASM-zadanie-2 Public

    2. zadanie zaliczeniowe, programowanie w asemblerze

    C