David Froelicher

David Froelicher

Postdoctoral researcher

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

Hi, I am a postdoctoral researcher working with Prof. B. Berger in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT) and with Dr. H. Cho at the Broad Institute of MIT and Harvard. I am currently working on privacy-preserving federated analytics and genomic privacy. I am designing new secure and distributed solutions by building on top of applied cryptography, using 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.

Contact
  • dfroelic@mit.edu

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

Education
  • 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)

Publications

(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.

PDF Cite Link Trailer Video

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

Cite

(2021). Truly Privacy-Preserving Federated Analytics for Precision Medicine with Multiparty Homomorphic Encryption. Nature Communications.

PDF Cite DOI Link

(2021). POSEIDON: Privacy-Preserving Federated Neural Network Learning”. NDSS 2021.

PDF Cite DOI Link

Experience

 
 
 
 
 
MIT & The Broad Institute of MIT and Harvard
Post-Doctoral Researcher
February 2022 – Present Cambridge, MA
Working with Prof. B. Berger’s group in Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT) and with Dr. H. Cho’s group at the Broad Institute of MIT and Harvard
 
 
 
 
 
EPFL
PhD Student
EPFL
September 2016 – November 2021 Lausanne, Switzerland
Working in the laboratory for data security (LDS), led by Prof. Jean-Pierre Hubaux) and the Decentralized and Distributed Systems Lab (DeDiS), led by Prof. Bryan Ford)
 
 
 
 
 
EPFL
Research Assistant
EPFL
March 2016 – September 2016 Lausanne, Switzerland
Working in the laboratory for data security (LDS), led by Prof. Jean-Pierre Hubaux)
 
 
 
 
 
NEC
Master Thesis
NEC
March 2016 – September 2016 Heidelberg, Germany
Working in the laboratory for data security (LDS), led by Prof. Jean-Pierre Hubaux)

Teaching

I am now supervising one graduate student.
I have supervised two master’s theses, twelve master’s semester projects, two bachelor’s semester projects, and 2 master’s level summer internships. I was a teaching assistant for the following courses at EPFL:

  • Mobile Network, Master
  • Information Security & Privacy, Master
  • Advanced Topics on Privacy Enhancing Technologies, Master
  • Introduction to Object-oriented Programming, Bachelor

Reviewer & sub-reviewer

I have served as a reviewer (and sub-reviewer) for the following conferences and journals:

  • IEEE S&P
  • PLOS Genetics
  • Nature Communications
  • Genome Research
  • Recomb
  • Bioinformatics
  • International Society for Molecular Biology (ISMB)
  • Privacy Enhancing Technologies Symposium
  • Digital Signal Processing Journal
  • EURASIP Journal on Information Security
  • Journal of Visual Communication and Image Representation -International Conference on Information Systems Security and Privacy