resume_json_file

resume.json

{
  "basics": {
    "name": "Loic Mandine",
    "label": "Machine Learning Engineer",
    "image": "https://mdag.cyou/assets/img/cv_photo.jpg",
    "email": "loic.mandine@gmail.com",
    "phone": "+1 438-701-7027 | +33 6 85 36 16 69",
    "url": "https://mdag.cyou/",
    "summary": "Looking for an Internship for SUMMER 2024 (min. 4 months, May 2024), on-site and remote work",
    "location": {
      "address": "",
      "postalCode": "",
      "city": "Montreal",
      "countryCode": "Quebec",
      "region": "Canada"
    },
    "profiles": [
      {
        "network": "Twitter",
        "username": "MdPlopy",
        "url": "https://twitter.com/MdPlopy"
      },
      {
        "network": "LinkedIn",
        "username": "loic-mandine",
        "url": "https://www.linkedin.com/in/loic-mandine/"
      }
    ]
  },
  "work": [
    {
      "name": "MARSS Group",
      "position": "Machine Learning Engineer",
      "url": "https://marss.com/",
      "startDate": "2022-12-01",
      "endDate": "2023-07-01",
      "summary": "Develop/Implement production-ready Object Detector model (mainly one-stage CNNs) & Compress those lasts for edge low-power devices deployment",
      "highlights": [
        "Deep Learning to the edge",
        "Computer Vision - Object Detection",
        "Neural Network Compression"
      ]
    },
    {
      "name": "AzurIA",
      "position": "Data Scientist Apprenticeship",
      "url": "https://www.azuria.earth/",
      "startDate": "2021-09-01",
      "endDate": "2022-11-01",
      "summary": "Still at its very beginning, I joined AzurIA to support the R&D-team's AI projects. I had the opportunity to work on many Computer Vision-related projects.",
      "highlights": [
        "Life of the creation of a startup",
        "Computer Vision - Satellite Imagery/Remote Sensing, Cloud Segmentation (Custom U-Net), Boat Detection (YOLOvx model series)",
        "Literature Survey, State-of-the-art of DL datasets/algorithms applied to multi-spectral images",
        "Anomaly Detection - Defect detection manufactured pieces, Disease Segmentation on vign leafs",
        "DevOps/MLOps - Self-hosted ML workspace & GPU cluster maintenance, Gitlab CI/CD, PoC of ML projects",
        "TinyML - Deployment ML models on edge devices (several nvidia jetsons, raspberry pi/pico, intel Movidius/OpenVino toolkit)"
      ]
    },
    {
      "name": "Center Antoine Lacassagne, CHU Nice - Department of Epidemiology, Biostatistics and Health Data",
      "position": "Data Scientist Intern",
      "url": "https://www.centreantoinelacassagne.org/qui-sommes-nous/les-poles/departement-depidemiologiede-biostatistiques-etdes-donnees-de-santedebds/",
      "startDate": "2021-06-01",
      "endDate": "2021-08-01",
      "summary": "This internship was to develop and validate a machine learning model to help in the decision of malignancy of a thyroid nodule. Then, the performance of several machine learning methods were compared.",
      "highlights": [
        "Machine learning for medical diagnosis in oncology",
        "Publication of a scientific article in a peer-reviewed journal"
      ]
    }
  ],  
  "volunteer": [
    {
      "organization": "University of Montreal - DIRO Department",
      "position": "Tutor",
      "url": "https://diro.umontreal.ca/ressources-services/soutien-pedagogique/les-services-de-tutorat-au-diro-et-a-ludem/",
      "startDate": "2023-09-01",
      "endDate": "2024-01-01",
      "summary": "Animator of weekly seminar on 'Learning Linux' for students. I also help (undergrad) students with their homeworks and projects.",
      "highlights": [
        "Linux Seminar for students",
        "Projects/Homework assistance, tutoring"
      ]
    }],
  "education": [
    {
      "institution": "MILA Institute / University of Montreal",
      "location": "Montreal, Canada",
      "url": "https://mila.quebec/en/",
      "area": "Master in Machine Learning",
      "studyType": "Deep Learning Master",
      "startDate": "2023-09-01",
      "endDate": "2024-09-01",
      "score": "",
      "courses": [
        "Representation Learning",
        "Machine Learning Fundings",
        "Data Science",
        "Advanced Deep Learning projects"
      ]
    },
    {
      "institution": "Polytech Nice Sophia-Antipolis",
      "location": "Sophia Antipolis, French",
      "url": "https://univ-cotedazur.fr/formation/offre-de-formation/ingenieur-mathematiques-appliquees-et-modelisation",
      "area": "Applied Mathematics and Modeling - Data Science",
      "studyType": "Baccalaureate + Master's degree",
      "startDate": "2022-09-01",
      "endDate": "2017-09-01",
      "score": "",
      "courses": [
      ]
    }
  ],
  "awards": [
    {
      "title": "Hackaton - 2nd place",
      "date": "2022-04-01",
      "awarder": "BonsAPPs/BonsEyes european organization",
      "url": "https://bonsapps.eu/",
      "summary": "AzurIA R&D team has successfully participated in Stage 1 of the 1st support programme of BonsAPPs. Throughout a two-month program, we developed a structured datatool and an AI Asset workflow for the training and deployment of deep neural network on the edge for a Defect Detection usecase."
    }
  ],
  "certificates": [
    {
      "name": "Master in Machine Learning (In Progress)",
      "date": "2024-09-01",
      "issuer": "University of Montreal - MILA Institute",
      "url": "https://mila.quebec/en/professional-programs/",
      "icon": "fa-solid fa-location-dot"
    },
    {
      "name": "Engineering Degree - Applied Mathematics and Modeling",
      "date": "2022-09-01",
      "issuer": "Polytech Nice Sophia",
      "url": "https://univ-cotedazur.fr/formation/offre-de-formation/ingenieur-mathematiques-appliquees-et-modelisation",
      "icon": "fa-solid fa-location-dot"
    },
    {
      "name": "General Preparatory Cycle for Engineering schools - P.E.I.P. Polytech Nice",
      "date": "2019-09-01",
      "issuer": "Polytech Nice Sophia",
      "url": "https://polytech.univ-cotedazur.fr/formations/cycle-preparatoire-integre",
      "icon": "fa-solid fa-tag"
    }
  ],
  "publications": [
    {
      "name": "Application of machine learning methods to guide patient management by predicting the risk of malignancy of Bethesda III-V thyroid nodules",
      "publisher": "European Journal of Endocrinology",
      "releaseDate": "2023-01-30",
      "url": "https://pubmed.ncbi.nlm.nih.gov/36799885/",
      "summary": "Indeterminate thyroid nodules (ITN) are common and often lead to (sometimes unnecessary) diagnostic surgery. We aimed to evaluate the performance of two machine learning methods (ML), based on routinely available features to predict the risk of malignancy (RM) of ITN"
    }
  ],
  "skills": [
    {
      "name": "Machine Learning",
      "level": "",
      "icon": "fa-solid fa-hashtag",
      "keywords": [
        "Pytorch","Pytorch Lightning","OpenMMLab libs", "Wandb/Comet/ClearML"
      ]
    },
    {
      "name": "Software Engineering",
      "level": "",
      "icon": "fa-solid fa-hashtag",
      "keywords": [
        "Git", "Docker", "Remote Development", "Wandb/Comet/ClearML", "Pandas/ScikitLearn"
      ]
    }
  ],
  "languages": [
    {
      "language": "French",
      "fluency": "Native speaker",
      "icon":""
    },
    {
      "language": "English",
      "fluency": "Fluent",
      "icon":""
    }
  ],
  "interests": [
    {
      "name": "Biomimicry",
      "icon": "fa-solid fa-tag",
      "keywords": [
        "Biomimetism","Bio-inspired innovation"
      ]
    }
  ],
  "references": [
  ],
  "projects": [
  ]
}