Research group · Universitas Riau

Machine learning for knowledge that matters.

We study learning systems, pattern discovery, language, vision, and decision support. Our work connects rigorous methods with problems that matter.

4Selected projects
6Research themes
2026–30Shared roadmap
MLKD research mapActive programme
ApproachRigorous methods
OutcomeUseful evidence
5Members
4Active projects
39Publications
7News & activities
What we study

Strong methods. Clear purpose.

We connect algorithms, data, and responsible deployment with questions that have scientific and practical value.

01

Machine Learning

Predictive, adaptive, and robust models for structured and unstructured data.

02

Knowledge Discovery

Patterns, relationships, and insights that support better understanding.

03

Language and Vision

Text, images, and multimodal data for real-world analysis.

04

Responsible AI

Explainability, validation, and human oversight in applied intelligent systems.

05

Spatial Intelligence

Machine learning for environmental, geographic, and public-sector challenges.

06

Decision Support

Evidence that helps people assess risk, set priorities, and act with confidence.

Featured work

Research in context

Selected projects show how MLKD connects technical work with environmental, social, and institutional needs.

Kampar Karhutla Watch
Machine Learning, Spatial Intelligence, and Disaster Risk Management

Kampar Karhutla Watch

Kampar Karhutla Watch is a data-driven system developed to support early monitoring and mitigation of forest and land fires in Kampar Regency. Funded by Universitas Riau through the 2026 DIPA research program, the project is being developed in partnership with BPBD Kampar.

Kampar Fuel Intelligence
Traffic Intelligence, Spatial Analytics, and Decision Support Systems

Kampar Fuel Intelligence

Kampar Fuel Intelligence is a data-driven system that estimates queue potential at fuel stations in Kampar Regency based on traffic conditions around each location. It provides risk levels, station rankings, and map-based recommendations to help users identify more suitable refuelling locations.

Peta Dakwah Cerdas (Intelligent Da’wah Mapping System)
Artificial Intelligence, Geospatial Analytics, Machine Learning, and Decision Support Systems

Peta Dakwah Cerdas (Intelligent Da’wah Mapping System)

Peta Dakwah Cerdas (PDC) is an intelligent mapping system developed to support preacher assignments and the preparation of relevant da’wah content. It connects mosque locations, preacher profiles, local social issues, and weather information to help plan more targeted da’wah activities.

News and activities

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Our people

A focused group built for collaboration.

MLKD brings together faculty, students, and partners around well-defined questions, shared research practices, and useful outcomes.

5members currently listedMeet the group