Data Scientist

Researcher & Professor in Machine Learning

Dakar Institute of Technology
Liberté 6 extension, Dakar, Sénégal
abdoul.w.m.diallo@aims-senegal.org
+221 33 864 56 22 / 78 121 41 21

Professional Profile

Highly motivated data scientist with six months of working experience as a researcher at the CEDRIC laboratory in CNAM where my job was to implement a new method of clustering for high-dimensional data. Extensive experience working at IPAR on a deforestation modeling project using machine learning models. Currently a machine learning professor at DIT (Dakar Institute of Technology), and in parallel, conducting research on sparse subspace clustering methods at the S3D research group.

Research Interests

  • Machine Learning & Deep Learning
  • High-Dimensional Data Clustering
  • Sparse Subspace Clustering
  • Natural Language Processing
  • Environmental Data Modeling

Languages

  • French (Fluent)
  • English (Proficient)
  • Arabic (Proficient)
  • Wolof (Native)
  • Poular (Native)

Education

Master of Science in Mathematical Sciences

African Institute for Mathematical Sciences (AIMS), Senegal | 2019–2021

Specialization in Big Data

Master in Mathematics

Cheikh Anta Diop University of Dakar, Senegal | 2017–2019

Specialization in Geometry and Applications

Bachelor's Degree

Cheikh Anta Diop University of Dakar, Senegal | 2014–2017

Specialization in Mathematics and Computer Science

Professional Experience

Machine Learning Professor

Dakar Institute of Technology (DIT) | February 2022 - Present

  • Teaching Python programming, data collection, and exploration
  • Supervised and unsupervised machine learning methods
  • Deep learning and Natural Language Processing (NLP)
  • Conducting research on sparse subspace clustering methods at S3D research group

Data Scientist

IPAR, Dakar | May 2021 - January 2022

  • Modeled the risk of deforestation in Senegal using machine learning models
  • Analyzed agricultural, forestry, and urbanization data
  • Developed predictive models for environmental impact assessment

Speaker

21st IEEE International Conference on Data Mining (ICDM) | December 2021

Presented our new method on high dimensional clustering called Sparse Subspace K-means (SSKM) in Auckland, New Zealand

Speaker

52nd Days of Statistics of the French Statistical Society (SFdS) | June 2021

Presented our new method on high dimensional clustering called Sparse Subspace K-means (SSKM) in Nice, France

Research Intern

CEDRIC-CNAM Laboratory, France | July 2020–January 2021

  • Implemented a new method of Clustering for High Dimensional Data
  • Developed Sparse Subspace K-means (SSKM) algorithm
  • Conducted performance analysis on benchmark datasets

Technical Skills

Programming Languages

Python 95%
R 85%
Scala 70%

Machine Learning

Scikit-learn TensorFlow PyTorch Keras NLTK Spacy

Data Engineering

Hadoop Spark MongoDB MySQL Elasticsearch

Certifications

Machine Learning Specialization

Coursera

Deep Learning Specialization

Coursera

Natural Language Processing Specialization

Coursera

Machine Learning Engineering for Production (MLOps)

Coursera

Excel Skills for Data Analytics and Visualization

Coursera

BI Data Engineer | Analyst

Udemy

Publications & Research

Sparse Subspace KMeans

2021

Journal Article

A novel clustering method for high-dimensional data that operates in sparse subspaces, addressing the curse of dimensionality. The algorithm was presented at both the 21st IEEE International Conference on Data Mining (ICDM) and the 52nd Days of Statistics of the French Statistical Society (SFdS).

Clustering High-Dimensional Data Sparse Subspaces

Deforestation Modeling in Senegal Using Machine Learning

2022

Research Project

Developed machine learning models to predict deforestation risks in Senegal by analyzing agricultural, forestry, and urbanization data. The project provided valuable insights for environmental policy and conservation efforts.

Environmental Modeling Supervised Learning Geospatial Analysis

Conference Presentations

21st IEEE International Conference on Data Mining (ICDM)

Auckland, New Zealand | December 2021

Presented our new method on high dimensional clustering called Sparse Subspace K-means (SSKM).

52nd Days of Statistics of the French Statistical Society (SFdS)

Nice, France | June 2021

Presented our new method on high dimensional clustering called Sparse Subspace K-means (SSKM).

Contact Me

I'm open to research collaborations, consulting opportunities, and academic discussions.

abdoul.w.m.diallo@aims-senegal.org
+221 33 864 56 22 / 78 121 41 21
Liberté 6 extension, Dakar, Sénégal

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