Andrew Janowczyk
Assistant Professor at CHUV | Lausanne university hospital
Geneva, Geneva, Switzerland
Summary
👤
Senior🎓
Top SchoolAndrew Janowczyk is an assistant professor and computational scientist who blends 11 years of enterprise software engineering with a decade of domain-focused research in digital histopathology and cancer. He builds scalable, GPU-enabled deep learning pipelines and cloud/HPC integrations that have been deployed across multiple clinical challenges—nuclei, epithelium, tubule and mitosis segmentation, lymphocyte detection and cancer subtype classification—often matching or surpassing state-of-the-art results. As a former start-up co-founder and Chief Science Officer, he has operationalized semantic search and large-scale analytics for production environments and helped steer a company to a multi-million CHF valuation. His work spans the full stack from algorithms (Matlab, Python, C/C++) to distributed systems (Solr, AWS, CUDA), and he routinely bridges clinical collaboration with reproducible, high-performance workflows. Trained at IIT Bombay and RPI, he combines rigorous academic methods with practical software craftsmanship to turn complex biomedical data into actionable clinical insight.
11 years of coding experience
16 years of employment as a software developer
Indian Institute of Technology BombayMasters, Computer Science, Masters, Computer Science at Rensselaer Polytechnic Institute
English, Greek, Chinese, French
Github Skills (148)
parallel10
python10
hyperparameter-optimization10
deep-learning10
digital-pathology10
ray10
optimization10
image-annotation-tool10
reinforcement-learning10
pytorch10
machine-learning10
large-language-models10
segmentation10
caffe9
llm-inference9
Programming languages (13)
Github contributions (5)
choosehappy/HistoQC
Oct 2017 - Apr 2022
HistoQC is an open-source quality control tool for digital pathology slides
Contributions:7 releases, 51 reviews, 143 commits in 4 years 6 months
digital-pathology
choosehappy/PytorchDigitalPathology
Oct 2018 - Aug 2022
An implementation of Unet for pytorch designed for digital pathology segmentation
Contributions:36 commits, 10 PRs, 31 pushes in 3 years 10 months
digital-pathologypytorchsegmentation
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