---
title: ULM Data Science Lab
emoji: 🌿
colorFrom: blue
colorTo: green
sdk: static
pinned: false
---

# ULM Data Science Lab

**ULM Data Science Lab** is an applied machine learning and data science research group based at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Lambung Mangkurat, Indonesia.

Our work focuses on building practical machine learning resources, datasets, benchmarks, and educational materials for Indonesian and tropical-context problems, especially in domains where public datasets and reproducible baselines are still limited.

## Research Areas

We are interested in applied AI and machine learning for:

- Health data science and prediction
- Agriculture and oil palm monitoring
- Indonesian food image understanding
- Environmental sound classification and forest monitoring
- Indonesian natural language processing
- Multimodal learning for local scientific datasets
- Data mining and applied deep learning education
- Food computing and nutrition-aware AI


## What We Share Here

This Hugging Face organization is used to host research and teaching resources developed by the lab, including:

- Curated datasets
- Benchmark datasets
- Dataset cards and documentation
- Baseline-ready data splits
- Educational datasets for machine learning courses
- Future model checkpoints and demo spaces

We aim to make our resources useful for students, researchers, and practitioners working on applied machine learning in Indonesia and other low-resource or underrepresented settings.

## Current Dataset Themes

Our current and planned datasets include resources related to:

- Indonesian food and food composition data
- Postprandial glucose prediction
- Forest and environmental sound classification
- Oil palm image analysis
- Local-language and local-context machine learning tasks

## Principles

We prioritize:

- Clear dataset documentation
- Reproducible machine learning workflows
- Responsible data sharing
- Local relevance
- Educational usability
- Open research collaboration

Some datasets may have restricted redistribution depending on source licensing, privacy, or institutional constraints. When full data release is not possible, we aim to share metadata schemas, preprocessing scripts, benchmark protocols, or legally shareable subsets.

## Affiliation

**Department of Computer Science**  
Faculty of Mathematics and Natural Sciences  
Universitas Lambung Mangkurat  
Banjarbaru, South Kalimantan, Indonesia

Website: https://ilkom.ulm.ac.id/

## Contact

For research collaboration or dataset-related questions, please contact:

**Fatma Indriani**  
Department of Computer Science, Universitas Lambung Mangkurat  
Email: f.indriani@ulm.ac.id

## Team

**Lab Coordinator**
- Fatma Indriani

**Faculty Members**
- Irwan Budiman
- Dodon Turianto Nugrahadi
- Dwi Kartini
- Andi Farmadi
- Muliadi
- Itqan Mazdadi
- Triando Hamonangan Saragih
- Annisa Rizqiana

**Research Assistants and Students**
- Muhammad Zainal Muttaqin

Individual dataset cards may include more specific contributor roles.