Evolve your OpenCV Image Processing filters using Cartesian Genetic Programming

Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.

Language Model Learning a Dataset for Data-Augmented Prediction

This article reframes pricing as a negotiation rather than a prediction, showing how price emerges from tensions between product reality, market dynamics, and buyer behavior. It introduces negotiation-aware ML, value decomposition, and equilibrium modeling to build transparent, human-aligned pricing systems.

This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.

A complete end-to-end fraud detection system for financial transactions, featuring data pipelines, cost-sensitive ML modeling, explainability with SHAP, threshold optimization, batch scoring, and an interactive Streamlit dashboard. Designed to simulate real-world fintech fraud-risk workflows.

Self-Evolving RAG System with ChromaDB for continuous knowledge updates (6x daily), designed to overcome Large Language Model data cutoff limitations.

Holistic Multimodel Domain Analysis: A New Paradigm for Robust, Transparent, And Reliable Exploratory Machine Learning that Considers Cross-Model Variability in Feature Importance Assessment

The Conscience Layer Prototype, created by Aleksandar Rodić in 2025, establishes a research foundation for ethical artificial intelligence. It brings moral awareness into computation through principles of truth, human autonomy, and societal responsibility, defining a transparent and accountable form of intelligence.

🌐 Information-Oriented Sphere System: From Data to Information Paradigm Shift | 信息导向球面系统 - Lossless reconstruction (MSE=0), Full interpretability, 2.28x optimized

Git-native desktop tool for crafting context-aware LLM prompts from local codebases with full transparency and control

Modular prompt system for transparent, multi-perspective, non-human AI reasoning.