Liam Moore, Developer in Leuven, Belgium
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Liam Moore

Verified Expert  in Engineering

Data Scientist and Developer

Location
Leuven, Belgium
Toptal Member Since
July 11, 2022

Liam is a machine learning scientist and engineer from a particle physics research background with experience leading various industry projects. He specializes in building bespoke statistical models, either using modern deep learning algorithms or classical machine learning combined with domain knowledge. Liam focuses on applying, developing, and keeping up to date with modern research while working with clients who care about creating social value.

Portfolio

SONY
Python, Adversarial Machine Learning, Machine Learning, Penetration Testing...
CARE Fertility
Python, TensorFlow, Azure, Computer Vision, Deep Learning, Time Series Analysis...
Unilever
Azure, TensorFlow, Keras, FastAPI, OpenCV, Object Detection...

Experience

Availability

Part-time

Preferred Environment

Linux, Python 3

The most amazing...

...thing I've improved is the selection of viable embryos in fertility clinics using AI.

Work Experience

Senior AI Scientist

2022 - PRESENT
SONY
  • Developed web security penetration tools using large language models.
  • Analyzed academic research trends across adversarial machine learning and kept stakeholders abreast of essential developments affecting key areas of their activity.
  • Investigated applications of AI across relevant market segments and co-designed mitigation protocols for adversarial threats.
Technologies: Python, Adversarial Machine Learning, Machine Learning, Penetration Testing, Language Models, Jupyter Notebook, Chatbots, Chatbot Conversation Design, ChatGPT, Generative Pre-trained Transformer 4 (GPT-4), App Development, Statistical Analysis, Predictive Analytics, Natural Language Processing (NLP), Data Cleaning, Data Cleansing, Random Forests, Supervised Machine Learning, OpenAI GPT-4 API, Leadership, Programming

Lead Data Scientist

2021 - 2022
CARE Fertility
  • Designed and developed a bespoke deep computer vision and time series analysis solution for producing expert human-level time-lapse video annotations in the context of embryo incubation.
  • Supervised the junior and mid-level data scientists and assisted engineers in productionizing and deploying the models in a user-facing cloud-native application.
  • Beat the previous state-of-the-art product on the market for solving the same task.
  • Co-published an abstract for work presented at the conference of the European Society of Human Reproduction and Embryology.
Technologies: Python, TensorFlow, Azure, Computer Vision, Deep Learning, Time Series Analysis, SQL, Machine Learning, Docker, Data Science, Data Engineering, Image Processing, Medical Imaging, Amazon Web Services (AWS), Predictive Modeling, Convolutional Neural Networks (CNN), Object Detection, Keras, FastAPI, OpenCV, SciPy, NumPy, Linux, Semantic Segmentation, Anomaly Detection, Algorithms, Artificial Intelligence (AI), Computer Vision Algorithms, Pandas, Team Leadership, Data Analysis, Data Visualization, Data Analytics, Time Series, JSON, CSV, Amazon SageMaker, JSTransformers, Statistical Modeling, Azure Machine Learning, Cloud, Machine Vision, Neural Networks, AI Design, Software Engineering, DevOps, Cloud Services, Machine Learning Operations (MLOps), Code Review, Source Code Review, Technical Hiring, Task Analysis, Interviewing, Team Management, APIs, Modeling, Interviews, Jupyter Notebook, App Development, Full-stack Development, Statistical Analysis, Predictive Analytics, Data Cleaning, Data Cleansing, Supervised Machine Learning, Leadership, Programming, Software Architecture, MySQL

Senior Data Scientist

2021 - 2021
Unilever
  • Developed a real-time anomaly detection model running on an Azure Stack Edge device in a factory.
  • Trialled a combination of supervised/unsupervised modeling approaches using anomaly detection, object detection, and transfer learning.
  • Worked with the staff on the ground on camera positioning, data acquisition, and efficient labeling strategies to maximize performance.
Technologies: Azure, TensorFlow, Keras, FastAPI, OpenCV, Object Detection, Convolutional Neural Networks (CNN), Anomaly Detection, Docker, NumPy, Linux, Algorithms, Artificial Intelligence (AI), Computer Vision Algorithms, Object Tracking, Pandas, Data Analysis, Data Visualization, Data Analytics, Time Series, JSON, CSV, Word2Vec, Statistical Modeling, Azure Machine Learning, Cloud, Machine Vision, Neural Networks, AI Design, Software Engineering, DevOps, Cloud Services, Machine Learning Operations (MLOps), Code Review, Source Code Review, Task Analysis, APIs, Modeling, Jupyter Notebook, Flask, App Development, Full-stack Development, Statistical Analysis, Real-time Data, Predictive Analytics, Data Cleaning, Data Cleansing, Supervised Machine Learning, Leadership, Programming, User Interface (UI)

Senior Data Scientist

2019 - 2021
GIM
  • Applied computer vision and time series analysis to remote sensing, earth observation raster, and vector data.
  • Built and deployed a cutting-edge deep semantic segmentation model that identified buildings and objects from public orthophotographs across the Benelux region.
  • Published a report for the cartographical administration of Luxembourg, detailing the algorithms and pioneering methods of quantifying the quality of the results when vectorized and used for constructing a database of buildings.
Technologies: Python 3, TensorFlow, Computer Vision, Deep Learning, GIS, Time Series Analysis, Geodesy, SQL, Machine Learning, Docker, PyTorch, Python, Scikit-learn, Data Science, Data Engineering, BERT, Image Processing, Amazon Web Services (AWS), Predictive Modeling, Convolutional Neural Networks (CNN), Object Detection, Keras, Scrapy, Sphinx Documentation Generator, GeoPandas, GDAL/OGR, OpenCV, SciPy, NumPy, Remote Sensing, Linux, Semantic Segmentation, Algorithms, Artificial Intelligence (AI), Computer Vision Algorithms, Pandas, Team Leadership, Data Analysis, Data Visualization, Data Analytics, Time Series, JSON, CSV, JSTransformers, Statistical Modeling, Tableau, Cloud, Machine Vision, Neural Networks, Drone Photography & Videography, AI Design, Voice Recognition, Speech Recognition, Software Engineering, DevOps, Cloud Services, Code Review, Source Code Review, Technical Hiring, Task Analysis, Interviewing, Team Management, APIs, Modeling, Interviews, Jupyter Notebook, Flask, XGBoost, JavaScript, App Development, Full-stack Development, Statistical Analysis, Predictive Analytics, Data Cleaning, Data Cleansing, Point Cloud Data, Random Forests, Supervised Machine Learning, Leadership, Programming, User Interface (UI), MySQL

Postdoctoral Researcher

2016 - 2018
Université Catholique de Louvain
  • Developed and compared computer vision and physics-aware deep learning models applied to radiation jet tagging.
  • Performed statistical analyses of novel physical phenomena affecting the spin of top quarks to estimate the values of unknown physical parameters.
  • Developed a tool for automatically simplifying effective quantum field theories in Mathematica.
  • Supervised the PhD students on several research projects.
Technologies: Python 3, Mathematica, C++11, SciPy, Statistics, Computer Vision, Deep Learning, Mathematical Modeling, Advanced Physics, Machine Learning, Docker, Python, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Scikit-learn, Data Science, Image Processing, Predictive Modeling, Convolutional Neural Networks (CNN), Keras, Sphinx Documentation Generator, OpenCV, Scientific Data Analysis, Scientific Computing, Linux, Mathematics, Physics, Algorithms, Artificial Intelligence (AI), Computer Vision Algorithms, Pandas, Data Analysis, Data Visualization, Data Analytics, JSON, CSV, MongoDB, Statistical Modeling, Cloud, Machine Vision, Neural Networks, AI Design, Software Engineering, Generative Adversarial Networks (GANs), Code Review, Source Code Review, Technical Hiring, Task Analysis, Interviewing, Team Management, Modeling, Interviews, Jupyter Notebook, XGBoost, Statistical Analysis, Predictive Analytics, Data Cleaning, Random Forests, Supervised Machine Learning, Programming, MySQL

Marie Curie Early-stage Research Fellow

2016 - 2016
Cern
  • Developed a Mathematica application that simplifies effective quantum field theories by removing operator redundancies.
  • Performed statistical sensitivity analyses to novel spin correlations in measurements of top-quark pair production at the LHC.
  • Collaborated with the experimental physicists, organizing the self-annihilation working group.
Technologies: Mathematica, Python 3, Advanced Physics, Statistics, C++11, Python, Data Science, Predictive Modeling, NumPy, Scientific Data Analysis, Scientific Computing, Linux, Mathematics, Physics, Software Engineering, Code Review, Source Code Review, Modeling, Jupyter Notebook, Statistical Analysis, Predictive Analytics, Supervised Machine Learning, Programming

PhD Researcher

2012 - 2016
University of Glasgow
  • Performed the research on constraining the parameters of the standard model effective field theory (SMEFT).
  • Co-founded the TopFitter collaboration, publishing a series of papers performing the first global fit of SMEFT parameters to top-quark measurements at the LHC and Tevatron.
  • Developed the Mathematica model-building tools used by the community.
Technologies: Python 3, C++11, Advanced Physics, Mathematica, Statistics, Sphinx Documentation Generator, NumPy, Scientific Data Analysis, Scientific Computing, Mathematics, Physics, Software Engineering, Code Review, Source Code Review, Modeling, Jupyter Notebook, XGBoost, Statistical Analysis, Predictive Analytics, Programming

AI-assisted Embryo Selection

https://www.eshre.eu/ESHRE2022/Programme/Searchable#!abstractdetails/0000694000
A deep computer vision and time series modeling solution to generating the expert human-level assessment of embryo quality from time-lapse images collected in embryo incubators.

I was the lead data scientist from the initial literature review through modeling on AzureML to productionization and deployment on AWS. I led a small team designing a solution that used multiple models with auxiliary objectives and custom loss functions accounting for subjectivity to tame a dataset of 450 million images.

Enriching Digital Maps with AI

https://business.esa.int/projects/eo4belmap
It was an ESA-funded project to build a suite of tools for extracting building metadata from historical analysis of earth observation data.

We determined the approximate years of construction of all buildings in Belgium using deep computer vision and time series analysis on public orthophoto and satellite data. We also obtained high-quality building footprints, which populated a database used in user-facing map products.

Datamining Objects from Public Earth Observation Imagery

https://data.public.lu/en/datasets/extopia-extraction-dojects-topographiques-par-intelligence-artificielle/
A deep computer vision and time series modeling solution to generating the expert human-level assessment of embryo quality from time-lapse images collected in embryo incubators.

I was the lead data scientist from the initial literature review through modeling on Azure ML to productionization and deployment on AWS. I led a small team designing a solution that used multiple models with auxiliary objectives and custom loss functions accounting for subjectivity to tame a dataset of 450 million images.

Production Line Fault Detection with Computer Vision

An application processing production line video streams in real time to detect manufacturing faults. Used anomaly and object detection to identify general and specific flaws. Deployed on an Azure Stack Edge device and accessible via a REST API to interface with monitoring dashboards.
2012 - 2016

PhD in Physics

University of Glasgow - Glasgow, Scotland, UK

2011 - 2012

Master's Degree in Physics

University of Glasgow - Glasgow, Scotland, UK

2007 - 2011

Bachelor's Degree in Physics

University of Glasgow - Glasgow, Scotland, UK

Libraries/APIs

TensorFlow, Keras, Pandas, PyTorch, Scikit-learn, OpenCV, GDAL/OGR, XGBoost, NumPy, SciPy

Tools

ChatGPT, Mathematica, GIS, Azure Machine Learning, Amazon SageMaker, Tableau

Frameworks

LlamaIndex, Sphinx Documentation Generator, Scrapy, Flask

Languages

Python 3, Python, SQL, C++11, C++, Fortran, JavaScript

Paradigms

Data Science, App Development, Anomaly Detection, DevOps, Penetration Testing

Platforms

Jupyter Notebook, Linux, Docker, Amazon Web Services (AWS), Azure, AWS Lambda

Storage

JSON, Data Pipelines, MySQL, MongoDB

Other

Statistics, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), Image Processing, Predictive Modeling, Convolutional Neural Networks (CNN), Semantic Segmentation, Artificial Intelligence (AI), Computer Vision Algorithms, Data Analysis, Data Analytics, CSV, Statistical Modeling, Machine Vision, Neural Networks, AI Design, Software Engineering, Code Review, Source Code Review, Technical Hiring, Task Analysis, Modeling, Chatbots, OpenAI GPT-3 API, Generative Pre-trained Transformer 4 (GPT-4), Full-stack Development, Statistical Analysis, Predictive Analytics, Data Cleaning, Data Cleansing, LangChain, Random Forests, Supervised Machine Learning, OpenAI GPT-4 API, Programming, Scientific Computing, Scientific Data Analysis, Mathematical Modeling, Time Series Analysis, Geodesy, Physics, GeoPandas, FastAPI, Data Engineering, BERT, Medical Imaging, Object Detection, Algorithms, Object Tracking, Data Visualization, Time Series, Word2Vec, JSTransformers, Transformers, Cloud, Drone Photography & Videography, Cloud Services, Interviews, Interviewing, Team Management, APIs, Chatbot Conversation Design, Generative Pre-trained Transformers (GPT), Real-time Data, Point Cloud Data, Leadership, Remote Sensing, Advanced Physics, Numerical Modeling, Mathematics, Team Leadership, Voice Recognition, Speech Recognition, Generative Adversarial Networks (GANs), Machine Learning Operations (MLOps), Adversarial Machine Learning, Language Models, User Interface (UI), Software Architecture

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