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

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.

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.

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.

Language Model Learning a Dataset for Data-Augmented Prediction

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

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

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

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

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

Conceptual Intelligence System - Building genuine intelligence through concepts, not neural networks

🚗 Decode car values using a transparent machine learning system that enhances price understanding through explainable methods.

🔍 Analyze and score transaction risk in real-time, enhancing fraud detection and operational insight with this full-stack machine learning engine.

Moria Grendel - Open-source AI influencer experiment for theaivideocreator.ai

🤝 Explore negotiation-driven pricing with a simulation engine that applies behavioral economics for smarter, real-world pricing strategies.