Research

Research Areas

IUS developed 3 research areas with 10 sub-areas based on decarbonization and digitalization to build resilient, inclusive, and smart urban futures.

Urban Planning and Analytics

Urban Planning and Analytics focuses on the use of urban data, spatial intelligence, digital documentation, and analytical methods to support evidence-based urban and regional planning. It covers planning-oriented research related to remote sensing, urban analytics, data engineering, decision support, and historic urban landscape studies. 

Sub-areas:

  • Infrastructure and Built Assets
  • Digital Intelligence and Data
  • Spatial Planning
  • Transportation and Mobility
  • Heritage and Cultural Preservation

Sustainable Infrastructure and Technology System

Sustainable Infrastructure and Technology Systems focuses on the development, assessment, and management of sustainable physical infrastructure and technology systems. It covers energy, water, infrastructure, vehicle technology, electrification, mobility-related technologies, asset management, and engineering systems that support resilient and low-carbon urban development. 

Sub-areas:

  • Infrastructure and Built Assets
  • Decision Management
  • Environment
  • Energy
  • Transportation and Mobility
  • Heritage and Cultural Preservation
  • Digital Intelligence and Data

Smart Urban Living

This theme focuses on the integration of technology, intelligent systems, social dimensions, and cultural values to improve quality of life in urban areas. It covers digital urban services, intelligent systems, health and social well-being, cultural heritage, museum and public experiences, and technology-enabled urban living. 

Sub-areas:

  • Urban Living and Social Well-being
  • Digital intelligence and Data
  • Decision Management
  • Heritage and Cultural Preservation

EXPLORE OUR RESEARCH

Center for Sustainable Infrastructure Development (CSID)

Center for Sustainable Infrastructure Development (CSID)

Centre for Sustainable Infrastructure Development (CSID) is an entreprenurial environment which researchers, skilled professionals and potential stakeholders from both academia and business can work side-by-side, ensuring that infrastructure in Indonesia can be successfully developed and accelerated to achieve the targeted national economic growth.

Research Areas

  • Sustainable Energy Clusters
  • Finance and Asset Management Clusters
  • Sustainable Water Management Clusters
  • Sustainable Mobility Clusters

Selected Publication

  • Khalil, M., Jan, B. M., Tong, C. W., & Berawi, M. A. (2017). Advanced nanomaterials in oil and gas industry: Design, application and challenges. Applied Energy, 191, 287–310. https://doi.org/10.1016/j.apenergy.2017.01.074
  • Khalil, M., Berawi, M. A., Heryanto, R., & Rizalie, A. (2019). Waste to energy technology: The potential of sustainable biogas production from animal waste in Indonesia. Renewable and Sustainable Energy Reviews, 105, 323–331. https://doi.org/10.1016/j.rser.2019.02.011
  • Berawi, M. A., Miraj, P., Windrayani, R., & Berawi, A. R. (2019). Stakeholders’ Perspectives on green building rating: A case study in Indonesia. Heliyon, 5(3). https://doi.org/10.1016/j.heliyon.2019.e01328
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Associate Director for Research Center (RCAVe)

The RCAVe offers a multi-disciplinary collective approach to understanding the impact of electrification on the future of vehicle and mobility. The RCAVe addresses this complex challenge by conducting fundamental research, working with industry and other stakeholders.

Research Areas

  • Mechanical and Driving system
  • Thermal Management System
  • Electric Motor and Propulsion System
  • Intelligent and Autonomous System
  • Research Battery Charging and Energy Management System
  • Research Battery System and Materials

Selected Publication

  • Salsabila, H. T., Baskoro, A. S., & Kiswanto, G. (2026). Investigation of plunge depth and tool geometry effects on the mechanical properties and microstructure of dissimilar AZ31B-AA1100 micro friction stir spot welding (MFSSW). Journal of Engineering and Applied Science, 73(1). https://doi.org/10.1186/s44147-026-00979-8
  • Amin, A., Yusivar, F., Husnayain, F., & Muharam, A. (2026). Low-Cost Active Cell Balancing Battery Management System for Electric Vehicles with Cell Charger as Cell Balancer. Technologies, 14(5), 298. https://doi.org/10.3390/technologies14050298
  • Sudiarto, B., Jufri, F. H., Angkasa, F. F., Widyanto, A. N., Hudaya, C., Husnayain, F., Fitri, I. R., Aryani, D. R., Kim, J.-S., Samual, M. G., & Arifin, Z. (2026). Battery technology for utility-Scale Battery Energy Storage System Applications: A comparative review. Journal of Energy Storage, 149, 120211. https://doi.org/10.1016/j.est.2025.120211
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Smart City Universitas Indonesia

Smart City Universitas Indonesia

Scientific Modeling, Application, Research, and Training for City-centered Innovation and Technology (SMART CITY) are the Center for Collaborative Research (CCR) led by Universitas Indonesia. CCR SMART CITY encourages individual researchers to use interdisciplinary approaches in its work, collaborate on a global scale, and create scientific and technological innovations as response to facing urban challenges, including the adoption of green technology, information technology in urban administration, services, and governance; reliability of urban infrastructure; and the rapidly declining quality of life, health, and general wellbeing.

Research Areas

  • Energy & Environment
  • Infrastructure
  • Quality of Life
  • Information & Communications Technology and Mobility

Selected Publication

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Center for Interdisciplinary Heritage Engineering

The Center for Interdisciplinary Heritage Engineering (CIDHE), is a research and innovation center dedicated to advancing science, technology, and engineering-based approaches for cultural heritage preservation. CIDHE integrates architecture, civil engineering, materials engineering, geotechnics, socio-cultural studies, environmental sciences, and digital technology to develop innovative, data-driven, and sustainable conservation practices. Through interdisciplinary research and cross-institutional collaboration, CIDHE supports heritage conservation, digital documentation, structural restoration, adaptive reuse, museum studies, historic urban landscape mapping, and heritage reconstruction at national and international levels.

Research Areas

  • Heritage Conservation and Adaptive Reuse
  • Digital Heritage and Documentation
  • Structural Restoration and Heritage Building Assessment
  • Historic Urban Landscape Studies
  • Museum Studies and Design Planning
  • Intangible Heritage Preservation
  • Heritage Reconstruction and Virtual Heritage

Selected Publication

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Artificial Intelligence and Data Engineering Research Group

Artificial Intelligence (AI) and Data Engineering combine computer science, mathematics, and engineering to develop intelligent systems and manage data for informed decision-making. Advances in machine learning and deep learning have enabled AI to perform complex tasks, while data engineering ensures that large-scale data is collected, processed, and prepared for AI models. Together, they drive innovation across industries such as healthcare, finance, and transportation, while continuing to evolve with a strong focus on technology and ethics.

Research Areas

  • Intelligent Systems
  • Natural Language Processing
  • Business and Operational Intelligence for Decision Making
  • AI for Health and Medical Imaging
  • AI for Biomedical Signal Processing
  • AI for Image and Video Processing
  • AI for Remote Sensing

Selected Publication

  • Sudiana, D., Putri, S. H., Kushardono, D., Prabuwono, A. S., Sri Sumantyo, J. T., & Rizkinia, M. (2025). CNN-Random Forest Hybrid Method for Phenology-Based Paddy Rice Mapping Using Sentinel-2 and Landsat-8 Satellite Images. Computers, 14(8), 336. https://doi.org/10.3390/computers14080336
  • Amalia, S., Dhini, A., Zulkarnain, Za’in, C., & Surjandari, I. (2026). A temporal fusion transformer for multi-step forecasting of Indonesia’s strategic food commodity prices. Results in Engineering, 30, 110131. https://doi.org/10.1016/j.rineng.2026.110131
  • Puspitadewi, C. H., Dhini, A., Laoh, E., & Sudiana, D. (2026). GIS-based wildfire prediction model in Indonesia using stacking ensemble learning. Artificial Intelligence in Geosciences, 7(2), 100228. https://doi.org/10.1016/j.aiig.2026.100228
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Policy Brief AIDE RC - Block Chain

Policy Brief CSID - Smart Industry

Policy Brief CSID - Smart Building

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