Manuel Burger is a PhD candidate at ETH Zurich specializing in foundation models for healthcare, translating advanced ML research into clinical deployments such as a leading study at Inselspital Bern. With a decade of experience and a background in computer science and data science from ETH, he focuses on making AI accessible across settings from ICUs to consumer health devices. He combines research rigor with hands-on engineering, contributing to open-source projects like DaCe where he improved FPGA code generation and Xilinx support. His teaching assistant roles reflect strong communication and mentoring skills, helping train the next generation of ML practitioners. Fluent in a cross-disciplinary environment that includes Chinese studies, he brings cultural agility to international collaborations. Colleagues describe him as pragmatic and detail-oriented, able to bridge prototype models and real-world clinical constraints.
11 years of coding experience
Master's degree, Data Science, Master's degree, Data Science at ETH Zürich
Bachelor's degree, Chinese Studies, Bachelor's degree, Chinese Studies at Shanghai Jiao Tong University
English, Italian, French, Spanish, Chinese, German
Contributions:9 reviews, 111 commits, 17 PRs in 1 year
Contributions summary:Manuel contributed to the DaCe project by fixing issues in the FPGA code generation, particularly related to Xilinx. Their work included correcting file paths and improving error messages within the FPGA code generator. They also added support for additional math functions, such as fabs, for Xilinx and optimized related vector operations.
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