Python library for parallel multiobjective simulation optimization
Pareto Front Estimation Using Unit Hyperplane
Solver for Blackbox Multiobjective Optimization Problems
Response Surface Analysis Interactive Panel
A few ML algorithms and Data Analysis
Analyse designed experiments with response-surface models, matched response comparisons, and traceable candidate settings.
A/B/n Experiment Project using Response Surface Methodology
The project focuses on the analysis of experimental data regarding the continuous biomass production of a cyanobacterium of the genus Nostoc. The primary objective is to understand how different cultivation factors influence biological growth over time, monitored through optical density (OD).
ML surface-roughness (Ra) prediction for CFRP milling — TUSAŞ Lift Up graduation project (MACHINOVA): RSM regression, desktop app & REST API.
Fast, benchmarked data-fit (surrogate) models (Kriging, RBF, response surfaces, ensembles) for surrogate-assisted and multidisciplinary design optimization (MDO). Analytic gradients, uncertainty, NumPy/SciPy.
Two-phase evaluation framework for the OpenAI Realtime API: VAD parameter optimisation via CCD/RSM and LLM-as-a-Judge scoring of medical simulation transcripts.
Sequential design-of-experiments and response-surface optimization study in R.
Validation harness and curated case datasets for the FORMULA-Sigma pharmaceutical formulation platform. Reproducibility package for the methods paper (harness: MIT; datasets: CC-BY-4.0). Platform engine is proprietary.
An agentic Design-of-Experiments and analysis assistant: plans experiments, runs sandboxed analysis code, fits response-surface models, and recommends the next run via Bayesian optimization.
A Dynamic Pricing framework integrating Monte Carlo simulations for demand uncertainty analysis and Response Surface Methodology (RSM) to optimize pricing strategies and maximize revenue.
DOE, RSM, regression, and multi-objective optimization of 3D printing parameters for lightweight and high-strength UAV parts
Multi-Objective Optimization of 3 output functions based on 5 input variables using epsilon-constraint method in Pyomo. [developed using ChatGPT July 20 Version]
Open-source Design of Experiments in your browser. Factorial designs, ANOVA, response surfaces, optimization, and a publication-ready PDF report — without the $1,995 license.
Lagrangian simulation of ascorbic acid retention during spray drying of Myrciaria dubia extract. Box-Behnken RSM, Monte Carlo uncertainty, glass transition analysis. UNSA Arequipa, Peru.
Compound-agnostic Design of Experiments (DOE) & Response Surface Methodology toolkit in Python. Config-driven factor/response setup with covariate (ANCOVA) and blocking support, Box-Behnken/CCD/factorial designs, ANOVA, desirability optimization, robust operating windows, publication-ready figures, and automated PDF reports. CLI + library
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