activity
20172026
most citedOn efficient global optimization via universal Kriging surrogate models

53 citations · 68 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CE2026

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences

Ghifari Adam Faza, Kemas Zakaria, Pramudita Satria Palar +4

Solving PDE-governed physical problems is computationally expensive, limiting the availability of high-fidelity (HF) data for training neural operators, which typically require lar…

cs.AI2026

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

Pramudita Satria Palar, Paul Saves, Muhammad Daffa Robani +6

The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models play a central role in reducing…

cs.LG2025★ 2 cited

Global Sensitivity Analysis for Engineering Design Based on Individual Conditional Expectations

Pramudita Satria Palar, Paul Saves, Rommel G. Regis +4

Explainable machine learning techniques have gained increasing attention in engineering applications, especially in aerospace design and analysis, where understanding how input var…

cs.AI2025★ 1 cited

Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration

Paul Saves, Pramudita Satria Palar, Muhammad Daffa Robani +6

Complex systems are increasingly explored through simulation-driven engineering workflows that combine physics-based and empirical models with optimization and analytics. Despite t…

cs.LG2025

SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration

Mohammad Daffa Robani, Paul Saves, Pramudita Satria Palar +2

Surrogate models are of high interest for many engineering applications, serving as cheap-to-evaluate time-efficient approximations of black-box functions to help engineers and pra…

stat.ML2018★ 53 cited

On efficient global optimization via universal Kriging surrogate models

Pramudita Satria Palar, Koji Shimoyama

In this paper, we investigate the capability of the universal Kriging (UK) model for single-objective global optimization applied within an efficient global optimization (EGO) fram…