Ben Rahman

Dr. Ben Rahman is a researcher, lecturer, and AI practitioner from Universitas Nasional, Jakarta. With a deep passion for culturally contextual AI systems, he focuses on developing large language models and agentic AI tailored for real-world impact in the Global South. He is the lead author of PPO-BR, a reinforcement learning framework introducing dual-signal entropy-reward adaptation to improve trust-region policy optimization, and HOT-FIT-BR, a localized extension of the global HOT-FIT model—adapted to Indonesia’s healthcare digital readiness assessment. Dr. Ben is currently advancing his research through SwearNet-IN, a semantic-pragmatic AI system built to detect hate speech in multilingual Indian digital communities, aligned with SDG 16 (Peace, Justice, and Strong Institutions). His work has been published in IEEE Access (Q1) and other high-impact journals, with applications ranging from medical AI to inclusive digital ecosystems. As an educator and national productivity advocate, Dr. Ben believes that AI should reflect the culture, language, and ethics of the people it serves.