Virtual Scientists leverages GPT-based language models to create specialized AI Agents that replicate expert scientists across various fields. Each virtual researcher is configured with tailored prompt engineering to provide accurate, context-aware answers, propose experimental protocols, interpret scientific data, and generate insights. Users select a scientific persona, input their questions or project details, and receive detailed, discipline-specific guidance supported by references and reasoning for educational or research purposes. The platform is hosted on GitHub Pages and is fully open-source. The codebase supports easy customization and extension of new scientific personas by modifying JSON configuration files. Ideal for collaborative research, teaching demonstrations, or personal study, Virtual Scientists bridges the gap between AI language models and practical scientific problem-solving by offering a dynamic, interactive environment for exploring complex topics with expert-like guidance.

arXiv Viz provides a visual method for exploring and understanding the comprehensive database of research papers available on arXiv. This tool aims to make it easier for researchers, students, and enthusiasts to quickly grasp the key ideas, trends, and connections in academic literature across various fields such as physics, mathematics, computer science, and more. By transforming the traditional text-based search and browsing experience into an intuitive visual interface, arXiv Viz enhances the way users interact with and comprehend scholarly articles.