Sandra Oluoch
Scientific Data Engineer
Computer Vision and Biomedical Research
About Me
I am passionate about open science and using Machine Learning and Artificial Intelligence to improve scientific understanding. My background blends bioengineering and computer science together – with over four years of work experience applying computer vision and deep learning to large-scale 3D stem cell imaging datasets.
I’ve contributed to the development of open-source tools that enhance biomedical image analysis (Allen Cell and Structure Segmenter) and to research papers exploring intracellular interactions (EMT Paper). My experience also spans immunology, neuroscience, cancer, and malaria research, reflecting a broad interest in health and discovery.
I am currently the founding engineer for the NeuroNur Research Initiative: a newly launched, volunteer-driven initiative dedicated to advancing neuroscience through collaboration, open data, and inclusive research. As a Black woman in STEM, I care deeply about building a more diverse and collaborative future for AI and computational biology.
Education
UNIVERSITY OF WASHINGTON • 2019 – 2020
MASTER OF APPLIED BIOENGINEERING, CONCENTRATION IN COMPUTATIONAL BIOLOGY
UNIVERSITY OF ROCHESTER • 2012 – 2016
BACHELOR OF SCIENCE IN BIOMEDICAL ENGINEERING, CONCENTRATION IN CELL & TISSUE ENGINEERING
MINOR IN CHEMICAL ENGINEERING
Work Experience
Scientific Data Engineer II
Allen Institute for Cell Science
Provided support in the design and implementation of machine learning algorithms and computer vision solutions for image analysis to better understand cell–cell dynamics.
The work encompassed algorithm development, open-source tool creation, large-scale data pipeline management, and the use of high-performance GPUs within a collaborative scientific environment.
Machine Learning Intern
Institute for Systems Biology
Designed and implemented supervised and unsupervised machine learning algorithms to predict gut microbiome responses to intervention within the Arivale Wellness Study, enhancing the understanding of microbiome dynamics.
Research Associate
Bristol Myers Squibb
Part of the Clinical Product Characterization team developing and testing Celgene CAR-T Cell therapies, JCAR017 and JCARH125.
Research Technician
Fred Hutch Cancer Center
Worked in a team studying pancreatic ductal adenocarcinoma (PDA) using genetically engineered mouse models to better understand the mechanism and pathogenesis of the disease.
Research Technician
Center for Infectious Disease Research
Assigned to a clinical research trial for the development of a potential malaria vaccine using the genetically attenuated parasite Plasmodium falciparum.
Skills
- Programming: Python, Git, Linux, Jupyter, Slurm
- ML/DL Frameworks: PyTorch, CUDA, Scikit-learn, Dask, OpenCV, Pandas, Matplotlib, NumPy, MONAI, Hydra
- Data Tools: Napari, ImageJ, Zen
- Cloud & DevOps: AWS, Docker
Publications and Preprints
- C. Hookway, A. Borenzstejn, L. Harris, S. Oluoch, et al., A Human Induced Pluripotent Stem (hiPS) Cell Model for the Holistic Study of Epithelial to Mesenchymal Transitions (EMTs), Under Review [Middle author]
- S. Mishra, S. Oluoch, B. Morris, A. Khan, et al., Enhancing Microscopy Image Analysis with Streamlined Deep-Learning-Based 3D Segmentation, Biophysical Journal, February 2025 [Second author]
- J. Dixon, C. Frick, C. Leveille, S. Oluoch, et al., Colony Context and Size-Dependent Compensation Mechanisms Give Rise to Variations in Nuclear Growth Trajectories, Cell Systems, May 2025 [Middle author]
- M. Viana, J. Chen, T. Knijnenburg, S. Rafelski, S. Oluoch, et al., Integrated Intracellular Organization and its Variation in Human iPS Cells, Nature, January 2023 [Middle author]
Get in touch
If you want to collaborate or have any questions, please feel free to reach out!
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