Indra Gunawan - Lecturer and Researcher in Geophysics

My research focuses on the development and application of geophysical methods for investigating subsurface structures and understanding geological processes. My work combines geophysical theory, numerical computation, field observations, data science, and quantitative analysis.

I am particularly interested in computational approaches, potential-field methods, geophysical data processing, subsurface characterization, and the application of emerging computational techniques to geophysical problems.

Research Areas

Computational Geophysics

Development and application of numerical and computational approaches for geophysical modeling, numerical analysis, large-scale data processing, big data, and parallel computation.

Gravity & Geomagnetic Methods

Application and development of gravity and geomagnetic methods for investigating subsurface structures, geological processes, and variations in physical properties.

Potential Field Modeling

Potential-field modeling and analysis, including gravity forward modeling, anomaly analysis, regional-residual separation, derivative analysis, and quantitative interpretation.

Electrical & Electromagnetic Methods

Application of electrical and electromagnetic methods, including electrical resistivity and induced polarization (IP), for subsurface characterization and geological investigation.

Geophysical Data Processing & Data Science

Processing, quantitative analysis, and interpretation of geophysical data, with emphasis on data quality, anomaly extraction, data-driven analysis, and computational workflows.

Subsurface Characterization & Modeling

Development of subsurface models to characterize geological structures and physical-property variations using geophysical observations and numerical modeling.

Artificial Intelligence & Machine Learning

Exploration of artificial intelligence and machine learning approaches for geophysical data analysis, pattern recognition, modeling, and interpretation.