About me

Who Am I?

Hi, I'm Michele. I was born in Parma, a city in the North of Italy.
I studied Computer Engineering and I obtained a Bachelor's degree (2013) and a Master's degree (2015) from Univeristy of Parma. Then I continued my studies abroad and I moved to Paris. Here, I was hired on a Marie Curie grant and completed a Ph.D. in Computer Science with specialization in Cryptography (2018) at École normale supérieure. My main research topic was homomorphic encryption and I graduated with a thesis on "Fully homomorphic encryption for machine learning".

I am fluent in Italian, English, and French. I am extremely passionate about technology and innovation, always willing to learn new things and improve myself. I am also an avid reader, fond of classical music, and a former competitive golf player. Oh and I love playing chess!

Over the years, I have been lucky enough to travel a lot, both for work and for holidays.
I attended and gave talks to several conferences and workshops, including events in Europe and the US.
I also visited numerous countries, especially in Asia, which I find extremely fascinating and enriching.

If you want to know more, you can have a look at

What I do

Here are some of my favorite topics


Software Development




Institution: École normale supérieure, Paris

I worked on Fully Homomorphic Encryption for Machine Learning, with a special focus on lattice-based cryptography.
Homomorphic encryption is a cryptographic technique that allows for computing on encrypted data, without needing to decrypt or have any secret key. Sometimes, it is also called "blind computing", in the sense that it allows for the computation of a result even without being able to access the input.
Such a technique is extremely useful in the scenario of computation outsourcing, where a party (e.g., a user) uploads sensitive data in an encrypted form, and another party (e.g., a remote untrusted server) performs a computation on this encrypted data. The result of this computation is an encryption of the output, which is sent back to the encryptor (i.e., the user). This party can now decrypt and obtain the computation's result.

I was a member of the ENS Crypto Team (INRIA Project - Team CASCADE), and I worked under the supervision of Michel Abdalla and Hoeteck Wee. I was recruited as a fellow of ECRYPT-NET, a EU-financed project within the "Horizon 2020" programme, thanks to one of the Marie Skłodowska-Curie actions. I also interned at CryptoExperts under the supervision of Pascal Pailler and Louis Goubin.

If you want to know more, here is a link to my thesis.

Institution: University of Parma

The topic of my thesis was "Deep learning techniques for recognizing emotions in face images", and I developed a system based on deep learning for identifying which emotion is expressed by a human face.

Institution: University of Parma

Institution: Liceo Scientifico Giacomo Ulivi, Parma


Work Experience

Sony Europe Oct. 2019 -

Position: Software Architect (Master Software Engineer)
Location: Brussels, Belgium

Amadeus IT Group Nov. 2018 - Oct. 2019

Position: C++ Software Engineer
Location: Nice, France
Note: Consultant from ALTEN Group

CryptoExperts Feb. 2017 - Jul. 2017 (during Ph.D.)

Position: Intern
Location: Paris, France


Some of my Skills

There are several things that I can do, and a lot of things that I can learn.








Microsoft Office




Languages I speak




Full professional proficiency


Professional proficiency
Academic Research


During the course of my doctoral studies, I had the opportunity to collaborate with some brillant researchers from a number of different institutions. This enriching experience resulted in the publication of several academic papers in renowned conferences.

Processing Encrypted Data Using Homomorphic Encryption
Workshop on Data Mining with Secure Computation, SODA project, 2017

with Anthony Barnett, Charlotte Bonte, Carl Bootland, Joppe W. Bos, Wouter Castryck, Anamaria Costache, Louis Goubin, Ilia Iliashenko, Tancrède Lepoint, Pascal Paillier, Nigel P. Smart, Frederik Vercauteren, Srinivas Vivek, and Adrian Waller

Get in Touch