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Hello World 👋

Something brief about me

🐥 in 🇸🇪 | 🏠 in 🇺🇸 | ❤️ with 🏃

  • Who: I'm Alma Andersson, a Sr. AI Scientist at Genentech, working in the AI/ML Department as a part of the spatially focused team. I completed my PhD in 2019 after 2.5 amazing years in the Lundeberg lab focusing on computational method development for analysis of spatial-omics data.
  • Work: Currently, a lot of my work focuses on designing and implementing computational models designed to capture the fundamental elements of tissue biology. This results in a mixture of probabilistic, dynamic, generative, and standard ML models. The main data modalities is spatial data and images.
  • Interests:
    • Technical: generative learning, uncertainty estimates, foundational models, dynamical systems, programming
    • Non-technical: running (my big passion), sports science, mountain climbing/hiking, video editing, modern and ancient history

Where to find me

  • 🏠 I reside in the beautiful Bay Area. I'm always down for a f2f chat.
  • 🌐 Website: differentiable[dot]net
  • 📧 You can also reach out on email at alma.andersson[at]differentiable[dot]net
  • 🔥 I used to post frequently on twitter, but given the dumpster fire it's turned into, I'm not very active. However, my account is 👉 Twitter URL

Alma Andersson's Projects

breast_dge icon breast_dge

Breast Cancer Differential Gene Expression Analysis Project

celery icon celery

CeLEry: cell location recovery in single-cell RNA sequencing

celltracker icon celltracker

Implementation of the Gaussian Mixture Particle Hypothesis Density (GM-PHD) filter for cell tracking in brightfield images

cluster-vae icon cluster-vae

Clustering of Single Cell or ST-data using a Variational Autoencoder for dimensionality reduction followed by a Dirichlet Process based unsupervised clustering

gameoflife icon gameoflife

C++ Toy implementation of Conway's Game of Life

genetech icon genetech

material related to the genetech courses

glm_tumor icon glm_tumor

Logistic Regression For tumor prediction in spatial data

scanpy icon scanpy

Single-Cell Analysis in Python. Scales to >1M cells.

sctransform icon sctransform

R package for modeling single cell UMI expression data using regularized negative binomial regression

sepal icon sepal

sepal : Spatial Expression PAttern Locator

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