Kristiina Ausmees
Data Scientist
Uppsala, Sweden
Summary
👤
Senior🎓
Top SchoolKristiina Ausmees is a data scientist with 11 years of experience blending academic rigor in scientific computing and genomics with practical industry work in analytics and AI. She completed a PhD applying and developing statistical and machine learning methods for challenging, sparse ancient DNA data—building HMM-based models and convolutional autoencoders for genotype analysis. Kristiina has translated that research into production-facing roles at Handelsbanken and now helps launch an AI Center at Region Uppsala to create data-driven solutions for public services. Comfortable across cloud-based, compute-intensive workflows and distributed execution, she brings both hands-on modelling and engineering experience. Her background in software development and formal assurance practices gives her an uncommon combination of statistical depth and systems-minded reliability.
11 years of coding experience
4 years of employment as a software developer
Master's Degree Computer Science, Master's Degree Computer Science at The University of QueenslandMaster's degree Computer Science, Master's degree Computer Science at Uppsala University
English, Swedish, Estonian, French
Github Skills (11)
autoencoder9
imputation9
bioinformatics7
probabilistic6
converting5
pmml5
python3
data-science2
machine-learning2
scikit2
scikit-learn1
Programming languages (3)
Github contributions (5)
kausmees/GenoCAE
Sep 2020 - Feb 2022
Convolutional autoencoder for genotype data
Contributions:1 release, 25 commits, 8 PRs in 1 year 5 months
autoencoderconvolutional-autoencoderconvolutionalgenotypegenotype-data
scicompuu/prophaser
Mar 2017 - May 2022
Imputation of genotype data based on the full probabilistic Li and Stephens model
Contributions:89 commits, 1 push in 5 years 3 months
imputationgenotypebioinformaticsprobabilisticgenotype-data
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