Leif Saager
Professor Of Anesthesiology at Universitätsmedizin Göttingen
Göttingen, Lower Saxony, Germany
Summary
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Senior🎓
Top SchoolLeif Saager is a Professor of Anesthesiology and experienced clinical leader with over a decade steering perioperative quality, clinical integration, and health IT initiatives across major academic centers in Germany and the United States. He currently serves as Professor and Executive Vice Chair at Universitätsmedizin Göttingen after directing quality and research programs (ASPIRE, MPOG) at the University of Michigan and holding clinical leadership roles at the Cleveland Clinic. Trained as an MD with an MMM from USC, he blends frontline anesthesiology practice with systems-level process improvement and change management to deliver safer, data-driven perioperative care. His research affiliation with Stanford’s Enigma Project signals active engagement at the intersection of clinical medicine and computational research, reflecting a habit of translating informatics and documentation systems into measurable quality gains.
10 years of coding experience
12 years of employment as a software developer
Master of Medical Management, Business Administration and Management, General, Master of Medical Management, Business Administration and Management, General at University of Southern CaliforniaDoctor of Medicine (MD), Medicine, Doctor of Medicine (MD), Medicine at Universität zu Lübeck
German, English
Github Skills (50)
model-fitting10
datajoint9
autoencoder9
datasets9
machine-learning9
pipeline9
neuroscience9
relational-algebra9
relational-databases8
relational-model8
gradient8
responsive8
visualize8
benchmark8
relational7
Programming languages (3)
Github contributions (5)
sinzlab/sensorium
Dec 2021 - Jun 2022
Contributions:21 reviews, 159 commits, 25 PRs in 6 months
neural-predictionvisual-cortexbenchmarkneural-system-identificationbase-code
KonstantinWilleke/neuralpredictors
Oct 2020 - Aug 2024
Machine Learning Utils of Sinzlab
Contributions:54 PRs, 119 pushes, 36 branches in 3 years 10 months
utilsmachine-learning
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