Resume

Basics

Name Gaël Van der Lee
Label PhD Candidate
Email gael.vanderlee@univ-lille.fr
Url https://gael-vanderlee.github.io/
Summary Programmer, Brain Researcher, tech-enthusiast, aspiring climber

Work

  • PhD Candidate
    2022.10 - 2025.10
    University of Lille

    Lille, France

    The European GENESIS project aims to find neural signals associated with the user experience in VR.
    • Research focuses on neural signals associated with cybersickness and vection at the intersection of BCIs and VR.
    • Designed, obtained ethics approval for, and ran a full user study (software in Unity & Python, EEG acquisition, VR synchronisation via LSL) from proposal to publication.
    • Performed comprehensive literature reviews on BCI and cybersickness; wrote and published multiple peer-reviewed papers.
    • Handled participant recruitment, experimental hardware (OpenBCI, ANTNeuro, GTec) and software development in Unity/OpenVibe.
    • Presented research at international conferences; created posters and defended results to multidisciplinary audiences.
    • Taught master-level classes at Centrale Lille (Machine Learning and Signal Processing in English).
  • Machine Learning Intern
    2022.03 - 2022.10
    Amazon

    Luxembourg, Luxembourg

    The Amazon ATS team is responsible for the transportation of packages from the fulfillment center to the customer's doorstep.
    • Created a machine-learning pipeline using boosted trees (XGBoost/LightGBM) to predict package-loss root cause.
    • Extensively used AWS (S3, SageMaker, Lambda, Step Functions, EC2) and Data Lake for scalable training and inference.
    • Applied test-driven development, version control and thorough documentation to ensure long-term maintainability and smooth hand-off to the owning team.
  • Applied Science Intern
    2021.03 - 2021.09
    Amazon

    Barcelona, Spain

    The Amazon ATS team is responsible for the transportation of packages from the fulfillment center to the customer's doorstep.
    • Designed an end-to-end anomaly detector and corrector for outbound-volume time-series data at global scale, delivering an estimated $7 MM annual benefit in NA alone.
    • Implemented hybrid anomaly-detection strategies using ARIMA, Exponential Smoothing, Prophet, LSTMs and Transformer models on both synthetic and real data.
    • Presented results and advised on the Y3R scientific roadmap for anomaly-detection approaches.
  • Machine Learning Intern
    2018.06 - 2018.09
    Neurala

    Boston, MA

    Neurala develops lightweight models for use on portable devices.
    • Built a plug-and-play vision toolkit (published as a pip package) enabling Neurala’s proprietary few-shot classifier to interface with multiple CNN/segmentation backbones.
    • Achieved 0.396 AP / 0.371 AR on COCO while working with very-large image datasets; included custom annotation, training and benchmarking pipelines.
  • Co-Founder
    2018.01 - 2019.12
    Vericrypt

    San Diego, CA

    Vericrypt helps users make informed decisions by aggregating and analyzing millions of news articles, autonomously giving them bias and trustworthiness ratings.
    • Developed, deployed and maintained an NLP pipeline (summarisation, sentiment & bias analysis) processing hundreds of articles daily on AWS.
    • Introduced a novel emotional-manipulation-detection technique by benchmarking against an objective baseline from scientific articles.
    • Secured acceptance into UCSD’s “The Basement” incubator and pitched technical vision to angel investors.
  • Lead Machine Learning Scientist
    2018.01 - 2020.11
    Lofty AI

    San Francisco, CA

    Lofty AI is a startup that aims to use a wide range of publicly available data in order to predict the evolution of the real-estate market.
    • Created scalable end-to-end data and ML pipelines handling social-media, satellite imagery, demographics and time-series data under tight startup timelines.
    • Developed hybrid deep-learning models (LSTMs & CNNs) and internal Python tooling that accelerated team experimentation.
    • Mentored new hires in Python best practices & Git, and communicated technical progress to investors during the Y-Combinator program.
  • Research Assistant – Algorithm Development for Brain-Computer Interfaces
    2017.09 - 2018.12
    University of California, San Diego – de Sa Lab

    San Diego, CA

    Worked in Prof. de Sa’s lab on advanced signal processing for EEG-based BCIs.
    • Developed a novel deep-learning architecture for CSP-like time-series feature extraction, improving accuracy by 2–4 % on benchmark datasets.
    • Designed experimental protocols and validated models on real EEG BCI datasets.
    • Collaborated in an academic research environment and contributed to internal presentations and publications.

Volunteer

  • App Developer
    2020.06 - 2020.12
    SFBA
    Volunteered to help develop an app to teach immigrants in the US to speak French.
  • Python Instructor
    2020.01 - 2020.06
    Technovation Girls
    Helped teach young girls how to code with the aim of helping them solve a problem in their community.
  • Data Science Instructor Assistant
    2018.01 - 2018.03
    University of California, San Diego
    Assisted the head of the UCSD Data Science department in teaching undergraduate data-science courses.
    • Helped design and grade programming assignments and data-visualisation projects.
    • Provided coding assistance and conceptual explanations during labs and office hours.

Education

  • PhD
    2022.10 - 2025.10
    Lille University

    Lille, France

    Brain-Computer Interfaces & VR
    • Neuroscience
    • Signal Processing
    • Virtual Reality
    • Machine Learning (teaching)
    • Signal Processing (teaching)
    • Brain-Computer Interfaces
    • Scientific Reading & Writing
    • Scientific Communication
  • Masters
    2020.09 - 2022.09
    Polytechnique

    Paris, France

    Artificial Intelligence and Visual Computing
    • Machine Learning
    • Deep Learning
    • Reinforcement Learning
    • Computer Vision
    • Natural Language/Speech Processing
    • High Dimensional Data Analysis
    • Computer Animation
    • Image Analysis
    • Statistics
    • Advanced 3D Graphics
    • Socio-emotional Embodied Conversational Agents
    • Ethics of AI
  • Bachelor of Science
    2015.09 - 2018.09
    University of California, San Diego

    San Diego, CA

    Cognitive Science – Machine Learning & Neural Computation
    • Brain-Computer Interfaces
    • Machine Learning
    • Data Processing
    • Computer Science
    • Natural Language Processing
    • Probabilities & Statistics
    • Research Methods
    • Cognitive Science
    • Neuroscience
    • Language, Learning, Memory & Attention
    • Psychology

Certificates

Skills

Programming
Python
Data Science
Machine Learning
Deep Learning
Computer Vision
Natural Language Processing
Java
C++
Lua
Packages
TensorFlow
Keras
Jupyter
Scipy
Mxnet
Caffe
PyTorch
Scikit-learn
Pandas
Numpy
Matplotlib
Seaborn
MNE
Unity
OpenBCI
ANTNeuro
GTec
OpenVibe
LSL
Software
PyCharm
SSH
Git
Matlab
Linux
CUDA
CuDNN
AWS
S3
GCP
SQL
Docker
Latex
Unity
AWS Lambda
AWS Step Functions

Languages

French
Native speaker
English
Native speaker
German
Proficient
Dutch
Proficient
Spanish
Intermediate

Interests

Sports
Bouldering
Sport Climbing
Jiu Jitsu
Pole Vaulting
Music
Trumpet player
EDM
Metal
Hobbies
Photography
Woodworking
Home Labbing
Local Generative AI
Ham Radio

Projects