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.

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

H. Cho, David Froelicher, N. Dokmai, A. Nandi, S. Sadhuka, M. Man-Hou Hong, B. Berger (2023). Privacy-Enhancing Technologies in Biomedical Data Science. Under Revision at Annual Reviews.

M. Hong, David Froelicher, R. Magner, V. Popic, B. Berger, H. Cho (2023). Secure Discovery of Genetic Relatives across Large-Scale and Distributed Genomic Datasets. Accepted at Recomb 2024 & Under Revision at Genome Research.

Code bioRxiv

H. Cho, David Froelicher, J. Chen, M. Edupalli, A. Pyrgelis, J. R. Troncoso-Pastoriza, J.-P. Hubaux, B. Berger (2023). Secure and Federated Genome-Wide Association Studies for Biobank-Scale Datasets. Under review.

PDF Cite Code Link

David Froelicher, H. Cho, M. Edupalli, J. S. Sousa, J.-P. Bossuat, A. Pyrgelis, J. R. Troncoso-Pastoriza, J.-P. Hubaux, B. Berger (2023). Scalable and Privacy-Preserving Federated Principal Component Analysis. IEEE Symposium on Security & Privacy 2023.

PDF Cite Link Trailer Video Video

S. Mendelsohn, David Froelicher, D. Loginov, D. Bernick, B. Berger, H. Cho (2023). sfkit: A Web-Based Toolkit for Secure and Federated Genomic Analysis. Nucleic Acids Research 2023.

PDF Cite Link

See all publications

Talks

Invited Talk in the Translational Medical Informatics track at ISMB 2023

Enabling collaborative analysis of genomic data silos with privacy

Jul 22, 2023 Lyon, France

Seminar Lecture at the Topics in Computational Biology Class at MIT

Privacy-Preserving Federated Genomics with Multi-party Homomorphic Encryption

Mar 12, 2023 MIT, Cambridge, MA

Seminar Lecture at the Institute for IT Security at Lübeck University

Privacy-Preserving Federated Analytics with Multiparty Homomorphic Encryption

Feb 15, 2023 Online - Lübeck University

Flash Talk in 2022 Annual NHGRI Centers of Excellence in Genomic Science Meeting

Secure and Federated Genome-Wide Association Studies

Oct 18, 2022 Online - Durham, NC

Invited Talk in Genomic Privacy & Security Special Session at ISMB 2022

Privacy-Preserving Federated Biomedical Analysis with Multiparty Homomorphic Encryption

Jul 12, 2022 Madison, Wisconsin

See all events

Awards & Press Articles

Runner-up Team for Finale Phase of the U.S. PETS Prize Challenge, Winning Team for Phase 1

Privacy-preserving federated learning for pandemic forecasting

Mar 15, 2023

Work Featured in a Joint Press Article by MIT, EPFL and CHUV - A cryptography game-changer for biomedical research at scale

This federated analytics system enables different healthcare providers to collaboratively perform statistical analyses and develop machine learning models, all without exchanging the underlying datasets.

Oct 11, 2021

Selected for Microsoft Private AI Bootcamp 2019

The Private AI Bootcamp offered by Microsoft Research (MSR) focuses on tutorials of building privacy-preserving machine learning services and applications with homomorphic encryption (HE).

Nov 15, 2019

Thesis

Privacy-Preserving Federated Analytics using Multiparty Homomorphic Encryption

PhD Thesis at EPFL

Oct 15, 2021

Experience

Post-Doctoral Researcher

MIT & The Broad Institute of MIT and Harvard

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

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)

Research Assistant

EPFL

March 2016 – September 2016 Lausanne, Switzerland

Working in the laboratory for data security (LDS), led by Prof. Jean-Pierre Hubaux)

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 two graduate students.
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

Academic Service

I have served on the program committee or editorial board of the following journals, conferences and workshops:

RECOMB-PRIEQ 2024
International Society for Molecular Biology (ISMB) 2024

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