Jean Lucien Randrianantenaina

Thanks for stopping by. I am currently pursuing a PhD in Computer Science at the University of Bath and enjoy building AI/ML and backend systems. If you would like to connect, feel free to reach out on LinkedIn or by email.

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Jean Lucien Randrianantenaina portrait
Bath, United Kingdom

Skills

Python logo Python
JavaScript logo JavaScript
SQL
Bash
HTML5 logo HTML5
CSS logo CSS
PyTorch logo PyTorch
TensorFlow logo TensorFlow
JAX Light Stroke JAX
Scikit-learn logo Scikit-learn
LangChain
Hugging Face
Django logo Django
Flask logo Flask
FastAPI logo FastAPI
Node.js logo Node.js
Vue.js logo Vue.js
Selenium logo Selenium
MySQL logo MySQL
PostgreSQL logo PostgreSQL
MongoDB logo MongoDB
ChromaDB
Docker logo Docker
Git logo Git
LaTeX

Professional Experience

A snapshot of recent roles focused on AI, backend systems, and teaching.

  • ML/AI and Backend Developer

    Arato, Fianarantsoa, Madagascar
    • Designed and deployed retrieval-augmented generation pipelines and chatbot systems.
    • Built automation workflows with Selenium and n8n for large-scale data collection and operational support.
    • Developed backend services and REST APIs.
  • Part-time Lecturer

    University of Fianarantsoa, Madagascar
    • Delivered teaching in Linear Algebra and Mathematics for AI to undergraduate and postgraduate students.
    • Prepared lecture materials, coursework, and assessments.

Education

My academic path across mathematics, machine learning, and computer science.

Publications & Talks

Research outputs and talks presented through concise, readable summaries.

Publications

HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces

Nasib Ullah, Jinbin Zhang, Jean Lucien Randrianantenaina, Erik Schultheis, and Rohit Babbar

Forty-third International Conference on Machine Learning (ICML 2026)

Extreme multi-label classification requires learning over output spaces with millions of labels, making the output layer a memory and compute bottleneck. We introduce group-shared fixed fan-in sparsity with hardware-aware CUDA kernels, achieving up to 4.4x and 25x speedups in the forward and backward passes while matching dense-model accuracy.

There Is No Carmichael Number of the Form $2^np^2+1$

Florian Luca and Jean Lucien Randrianantenaina

INTEGERS, Volume 23

In this paper, we prove that there is no Carmichael number of the form $2^np^2+1$ with some integer…

Talks

2023

Fermat’s Last Theorem, with $n=4$

AIMS Cameroon

A presentation of the $n=4$ case of Fermat’s Last Theorem, centered on the classical infinite descent argument and the way it rules out non-trivial integer solutions.

Projects

Selected work that reflects my current research and engineering interests.

Gym Management Web Application

Built a full-stack gym management web application for GI-Fitness using Django REST Framework for the backend and React for the frontend.

Django logo React logo

Conditional Flow Matching in Feature Space

MSc research project on simulation-free training of continuous normalising flows in latent feature space under the supervision of Dr Shane Josias and Prof. Willie Brink.

PyTorch logo

Reinforcement Learning Suite

Implemented Q-Learning, SARSA, and DQN variants and benchmarked them on MiniGrid using Gymnasium, PyTorch, and Weights & Biases.

Python logo PyTorch logo

Neural Machine Translation (English--Afrikaans)

Fine-tuned Transformer-based models for technical translation, improved tokenisation choices, and evaluated performance with BLEU.

Python logo PyTorch logo

Recommender System

Developed a probabilistic matrix factorisation model for the MovieLens 25M dataset and accelerated training with NumPy and Numba.

Python logo NumPy logo

Optimisation of UNet for Brain Tumour Segmentation

MSc research project on architecture optimisation for brain tumour segmentation using genetic algorithms under the supervision of Dr Aurelle Tchagna Kuanou and Dr Joelson Randriamparany.

Python logo

Contact me

If you'd like to collaborate, discuss research, or say hello, I'd be glad to hear from you.