Hello, I'mJérémie N. Mabiala
AI Researcher & Mathematical Scientist
Exploring the intersection of Mathematics, Deep Learning, and Explainable AI to build transparent and ethical AI systems.
Who I Am
AI researcher and mathematician passionate about the intersection of theoretical mathematics and practical AI applications.
Jérémie N. Mabiala
AI Researcher & Mathematical Scientist
Welcome! I am Jérémie N. Mabiala. If you're from an English-speaking culture, you can call me Jeremy. I am currently a resident tutor in Artificial Intelligence at the African Masters in Machine Intelligence (AMMI), a pan-African flagship master's program in Artificial Intelligence founded by Google and Meta, hosted at the African Institute for Mathematical Sciences,(AIMS) Senegal. I am an AI enthusiast and math lover.
Before that, I graduated from Stellenbosch University and AIMS South Africa in February 2024 with a Master's degree in Mathematical Sciences. I worked on Mathematical Statistics, specifically Functional Data Analysis. My master's thesis is titled Gaussian Processes for Multivariate Functional Data, and it is available at the AIMS Archive.
I also hold a Bachelor's degree (equivalent to Bac +5) in Mathematics from the University of Kinshasa, the Congo's leading university. There I graduated in the top 5% in my department with "Grande Distinction" (the Congolese equivalent of Summa Cum Laude). During my time there, I worked on Functional Analysis, which was my early math interest, and I served as a teaching assistant and subsidiary lecturer for two years.
I am passionate about teaching, gaining knowledge, and sharing it with others. I am particularly interested in Mathematics, Theoretical Aspects of Machine Learning and/or Deep Learning and their applications. My interests also extend to Mathematical Modeling, Functional Data Analysis, Large Language Models, and Reinforcement Learning.
I am a hobbyist developer and an apprentice writer.
Research Interests
Theoretical Machine Learning
Mathematical foundations of machine learning algorithms and their theoretical guarantees
Deep Learning
Neural network architectures, optimization methods, and generalization properties
Functional Data Analysis
Statistical methods for analyzing and modeling functional data
Explainable AI
Methods for making AI systems more transparent and interpretable
Languages
I am currently updating this website. Please, feel free to reach out to firstname(in french) at aims.ac.za or firstname (in english) at aimsammi.org for any inquiries.
News & Announcements
Stay updated with my latest activities, achievements, and upcoming events
Current Projects
Exploring the frontiers of AI research through innovative projects and collaborations
Key Objectives:
- Evaluate performance in optimizing electric vehicle routes
- Analyze how well each model explains its decisions
- Provide a transparent decision-making process
- Compare various DRL architectures with GNN integration
Collaborators:
Researchers from Tunisia, Senegal, and DR Congo
My master's thesis focused on developing novel statistical methods for analyzing multivariate functional data using Gaussian processes. This research contributes to the field of Functional Data Analysis with applications in various domains.
Methodologies:
- Gaussian Process Regression
- Functional Principal Component Analysis
- Multivariate Statistical Analysis
- Bayesian Inference
Applications:
- Environmental Data Analysis
- Biomedical Signal Processing
- Economic Time Series
- Climate Data Modeling
Publications & Preprints
Academic papers, conference proceedings, and research contributions
This thesis explores novel statistical methods for analyzing multivariate functional data using Gaussian processes. The work contributes to the field of Functional Data Analysis with applications in various domains including environmental monitoring, biomedical signal processing, and economic time series analysis.
This research paper presents a comparative study of various Deep Reinforcement Learning (DRL) models combined with Graph Neural Networks (GNN) and Explainable AI (XAI) techniques for electric vehicle routing optimization. The study evaluates the performance of different models in optimizing routes and their ability to explain decision-making processes.
This review paper explores the application of functional analysis techniques in mathematical modeling across various domains. The paper provides a comprehensive overview of how functional analysis can be used to develop more accurate and efficient mathematical models for complex systems.
Education
My academic journey in mathematics and artificial intelligence
African Masters in Machine Intelligence (AMMI)
AIMS Senegal
A pan-African master's program in Artificial Intelligence founded by Google and Meta, hosted at AIMS Senegal.
Currently focusing on advanced AI techniques and their applications in solving African and global challenges.
Completed Master's thesis on "Gaussian Processes for Multivariate Functional Data" with a focus on statistical methods for analyzing multivariate functional data.
Master's in Mathematical Sciences
Stellenbosch University & AIMS South Africa
Graduated in February 2024 with a Master's degree in Mathematical Sciences, specializing in Mathematical Statistics and Functional Data Analysis.
Bachelor's in Mathematics
University of Kinshasa
Graduated with "Grande Distinction" (Summa Cum Laude) in the top 5% of my department. Served as a teaching assistant and subsidiary lecturer for two years.
Developed a strong foundation in mathematics with a focus on functional analysis. Gained teaching experience as an assistant and lecturer.
Skills & Technologies
A comprehensive overview of my technical skills and proficiencies
Programming Languages
Machine Learning
Data Science
Motivations in Life
The core principles and aspirations that guide my personal and professional journey
Passion for Knowledge
My insatiable curiosity and love for learning drive me to continuously explore new concepts and ideas. I believe that knowledge is the foundation of innovation and progress.
Excellence in Research
I strive for excellence in all my research endeavors, pushing the boundaries of what's possible and contributing meaningful advancements to the scientific community.
Education as Empowerment
Following in the footsteps of my father and grandfather who were teachers, I believe in the transformative power of education to empower individuals and communities.
Collaborative Innovation
I'm motivated by the power of collaboration across disciplines and cultures. By working together with diverse minds, we can solve complex problems and create innovative solutions.
Ethical AI Development
I'm driven by the vision of creating AI systems that are not only powerful but also transparent, fair, and beneficial to humanity. Ethical considerations are at the core of my research.
African Innovation
I'm passionate about contributing to the growth of AI research and innovation in Africa. I believe in building local capacity and addressing unique challenges through technology.
"My ultimate motivation is to use my knowledge and skills to create positive impact, bridging the gap between theoretical research and practical applications that improve lives."
Favorite Citations
Quotes that inspire my thinking and approach to research, education, and life
"The most beautiful thing we can experience is the mysterious. It is the source of all true art and science."
Albert Einstein
Living Philosophies
Personal Reflection
This quote reminds me that curiosity and wonder are at the heart of scientific discovery. The unknown isn't something to fear but to embrace.
Blog & Tutorials
Educational content, tutorials, and insights on mathematics, AI, and data science
Featured Tutorials
A comprehensive tutorial on understanding Gaussian Processes with interactive visualizations and practical examples.
A step-by-step video tutorial series on implementing Deep Reinforcement Learning algorithms from scratch.
A comprehensive tutorial on understanding Gaussian Processes with interactive visualizations and practical examples.
A step-by-step video tutorial series on implementing Deep Reinforcement Learning algorithms from scratch.
Learn the fundamentals of Functional Data Analysis and how to implement key techniques using R.
A comprehensive video guide on using PyTorch for implementing mathematical models in research.
Explore various techniques for making AI models more interpretable and transparent.
A visual explanation of Graph Neural Networks with code examples and applications.
A deep dive into the essential mathematical concepts behind modern machine learning algorithms.
Learn how to apply Bayesian methods to machine learning problems with practical examples.
Learn how to analyze and model time series data using Python and its libraries.
A step-by-step video series on implementing NLP models using transformer architectures.
Contact Me
Feel free to reach out for collaborations, research opportunities, or just to say hello
firstname(in french) at aims.ac.za
firstname(in english) at aimsammi.org
I typically respond within 24-48 hours
Location
AIMS Senegal
KM 2, Route de Joal
Mbour, Senegal
Currently based in Senegal for my studies
Social Media
Connect with me on LinkedIn, Twitter, and GitHub for updates on my research and projects.
I'm most active on LinkedIn for professional networking
Send Me a Message
I am currently updating this website. Please, feel free to reach out to firstname(in french) at aims.ac.za or firstname (in english) at aimsammi.org for any inquiries.