David Froelicher

David Froelicher

Postdoctoral researcher

Massachusetts Institute of Technology & The Broad Institute of MIT and Harvard

Hi, I am a postdoctoral researcher collaborating with Prof. B. Berger at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT), as well as with Dr. H. Cho at Yale University (and previously at the Broad Institute of MIT and Harvard). Currently, my research focuses on privacy-preserving federated analytics and genomic privacy. I am designing new secure and distributed solutions, leveraging applied cryptography techniques such as homomorphic encryption and secure multiparty computation.

I received my PhD from EPFL for my work with Prof. J-P. Hubaux at the Laboratory for Data Security (LDS) and B. Ford at the Decentralized and Distributed Systems Laboratory (DeDiS). I earned my MSc and BSc in Computer Science with a specialisation in IT Security from EPFL in 2016. In 2015, I did a master thesis internship in the NEC research laboratory in Heidelberg, Germany, where I have been involved in the design and implementation of a system enabling proofs of retrievability on deduplicated data.

  • dfroelic@mit.edu

  • G-574 CSAIL MIT, 77 Massachusetts Avenue, Cambridge 02139, MA, United States

  • Ph.D. in Computer Science, 2016-2021

    École Polytechnique Fédérale de Lausanne (EPFL)

  • Master of Science in Communication Systems, 2016

    École Polytechnique Fédérale de Lausanne (EPFL)

  • Bachelor of Science in Communication Systems, 2014

    École Polytechnique Fédérale de Lausanne (EPFL)









January 2021 – Present California

Responsibilities include:

  • Analysing
  • Modelling
  • Deploying
University X
Professor of Semiconductor Physics
University X
January 2016 – December 2020 California
Taught electronic engineering and researched semiconductor physics.


Neural Networks and Deep Learning
See certificate
Formulated informed blockchain models, hypotheses, and use cases.
See certificate
Object-Oriented Programming in R
See certificate


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Recent Publications

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(2023). Privacy-Enhancing Technologies in Biomedical Data Science. Under Revision at Annual Review of Biomedical Data Science.

(2023). Secure Discovery of Genetic Relatives across Large-Scale and Distributed Genomic Datasets. Recomb 2024 (M.H. received best student paper award) & Under Revision at Genome Research.

Code bioRxiv

(2023). Secure and Federated Genome-Wide Association Studies for Biobank-Scale Datasets. Under review.

PDF Cite Code Link

(2023). Scalable and Privacy-Preserving Federated Principal Component Analysis. IEEE Symposium on Security & Privacy 2023.

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(2023). sfkit: A Web-Based Toolkit for Secure and Federated Genomic Analysis. Nucleic Acids Research 2023.

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