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Résumé

·3 mins

Mamady Nabé #

📧 mamady.nabe@outlook.com
🔗 linkedin.com/in/mamady
💻 github.com/mamadyonline

🧠 Professional Summary #

Machine Learning Engineer and Data Scientist with 5+ years of experience building end-to-end ML pipelines, predictive models, and data processing systems. PhD in Computer Science with expertise in natural language processing, speech recognition, and neural data analysis. Proven track record of developing innovative solutions in both research and industry settings, with skills in Python, ML frameworks, and big data technologies.

🛠️ Skills #

  • Programming Languages: Python, Java, C, Go, Rust, Julia, R, Matlab, SQL
  • Machine Learning: ScikitLearn, PyTorch, Keras, HuggingFace, SpeechBrain, LangChain, NLTK, SpaCy, MLFlow
  • Data Processing: Pandas, NumPy, MNE-Python, Kafka, InfluxDB
  • MLOps & Development: Docker, Jenkins, Google Cloud Platform, Git, CI/CD
  • Visualization: Tableau, Matplotlib, Seaborn, Plotly, Altair
  • Specialities: NLP, Speech Processing, Time Series Analysis, Predictive Modeling, Neural Data Analysis

💼 Experience #

ML Research Scientist #

Geneva University – Department of Fundamental Neuroscience, Geneva, Switzerland
Feb. 2023 – Present

  • Engineered an end-to-end AI pipeline for multi-language audio transcription and alignment using OpenAI Whisper and Montreal Forced Aligner, achieving 80% accuracy.
  • Developed advanced signal processing workflows for analyzing intracranial EEG data.
  • Built neural decoding models to extract linguistic features (words, syllables, phonemes) from brain recordings.
  • Optimized data pipelines, reducing analysis time by 40%.
  • Collaborated on coding projects in a dynamic research environment.

ML Engineer #

Bull Atos – Data Management Team, Grenoble, France
Sep. 2018 – Sep. 2019

  • Built predictive maintenance software for data centers.
  • Designed TB-scale data processing pipelines using InfluxDB, Graphite, Kafka.
  • Created explainable AI models using SHAP.
  • Successfully demonstrated PoC to enterprise partners including Météo France.

Data Science Intern #

Bull Atos – Data Management Team, Grenoble, France
Feb. 2018 – July 2018

  • Built machine learning and optimization algorithms improving HPC performance by 25%.
  • Contributed to the open-source library PySwarms.
  • Co-inventor of patent US20190392331A1 on ML optimization techniques.
  • Published at ISC High Performance 2018.

🎓 Education #

Ph.D. in Computer Science #

Grenoble Alps University – MSTII Doctoral School, Grenoble, France
Nov. 2019 – March 2023

  • Thesis: “Bayesian cognitive modeling of Speech Perception with a neurobiologically plausible temporal treatment, inspired by neural oscillations”
  • Published in peer-reviewed journals and conferences.

Engineering Diploma – Double Degree in Data Science & Embedded Systems #

Grenoble INP ENSIMAG & PHELMA, Grenoble, France
2015 – 2018

  • Thesis: “HPC IO accelerator parameter inference based on Numerical Optimization”

📚 Publications & Patents #

  • Neural encoding of syntactic structures during natural speech planning and production – Society for Neurobiology of Language, 2023
  • Isochronous is beautiful? – Interspeech, 2022
  • Cosmo-onset – Frontiers in Systems Neuroscience, 2021
  • Self-optimization strategy for IO accelerator parameterization – ISC High Performance, 2018
  • Patent: US20190392331A1 – ML Optimization Techniques

🌍 Languages #

  • French: Bilingual / Native
  • English: Fully Professional (C1)
  • Spanish: Elementary (B1)

📄 References #

Available upon request.