Nicola Pellicanò

Senior Machine Learning Engineer at Meta

Greater Paris Metropolitan Region

About

I am a Senior ML Engineer at Meta in London, working remotely from Paris. I previously worked a Senior ML Engineer and Tech Lead at Wefox in Paris, conducting R&D on insurance digitalization and risk prevention. My first industry experience has been as Applied Scientist at Samsung AI Labs in Paris, conducting applied research into Machine Learning (ML), Computer Vision (CV) and Natural Language Processing (NLP). I have received a PhD in CV/ML at Paris-Saclay University (France), working on pedestrian detection and tracking in high density crowds. My PhD experience has formed my expertise around the CV/ML domains while improving my problem solving skills, my methodological approach to science and stimulating my continuous learning attitude. I have obtained my bachelor and master diplomas with honors in Computer Engineering at University of Pavia (Italy). Such period has been crucial for developing my skills in programming, agile software development, and algorithms.

Experience

  • Senior Machine Learning Engineer at Meta
    Oct 2022 - Present · 3 yrs 9 mos

  • Senior Machine Learning Engineer, Tech Lead at wefox
    Mar 2021 - Oct 2022 · 1 yr 8 mos

    Part of the new Wefox Innovation team located in Paris, responsible of applied research in ML. Our main focus is to design and develop solutions for client risk prevention, while also backing Wefox towards the goal of 100% insurance digitalization. Topics of interest: - Multilingual NLP on text and structured documents. - Risk assessment and forecasting with transformer models.

  • Applied Machine Learning Scientist - Samsung AI Labs at Samsung Electronics
    Nov 2018 - Mar 2021 · 2 yrs 5 mos

    Applied research in several CV and NLP projects around multiple innovative products. Projects: - 3D lines detection for autonomous driving (non-linear 3D modeling of road, road line segmentation models) - Chatbot for assistance on Samsung products: automatic construction assistance knowledge graph, NLU of user queries to guide the conversation through the graph - Research study on exploiting transformer pertaining to provide strong baselines in zero-shot and few shot conditions. Publication as first co-author at ACL 2020: Pre-training Is (Almost) All You Need: An Application to Commonsense Reasoning (https://arxiv.org/abs/2004.14074) - Design and training of transformer model for topic segmentation of meetings (per-sentence classification of topic switch with context sentence window). - Person (re)-identification for meetings - Supervised internship on super-resolution of text on whiteboard images Participated to a study around quantum computing technology, which led Samsung Catalyst Fund to invest in IonQ company. Implemented and tested quantum circuits to report return on experience to IonQ.

  • Université Paris-Saclay (Orsay, France)
    • PHD Student
      Oct 2015 - Oct 2018 · 3 yrs 1 mo

      Subject de thèse: [MOHICANS] Analyse de foules denses pour la modélisation, la planification et la sécurité. [MOHICANS] Towards Modeling High-Density Crowds for Assisting Planning and Safety. Group: SATIE (Systèmes et Applications des Technologies de l’Information et de l’Energie) - ENS Cachan Ecole Doctorale: STIC - Sciences et Technologies de l'Information et de la communication.

    • Teaching Assistant
      Oct 2015 - Oct 2018 · 3 yrs 1 mo

      C/C++ laboratories and software projects assistant

  • Intern at Institut d'Electronique Fondamentale
    Mar 2015 - Jul 2015 · 5 mos

    Dense motion detection from a moving camera by multiview constraints