Smart Fabric Bellyband Featured on NSF Science Nation
Published:
The National Science Foundation (NSF) Science Nation series featured Drexel’s smart fabric Bellyband and the team.
The video can be found by clicking below:

Professor, Author, Machine Learning Researcher, Educational Consultant, and Scholar of Teaching and Learning; Host: digitalsignature.fm
less than 1 minute read
Published:
The National Science Foundation (NSF) Science Nation series featured Drexel’s smart fabric Bellyband and the team.
The video can be found by clicking below:
40 minute read
Published:
I now run nine coding agents side by side on a small always-on Ubuntu server: Claude Code, Codex, Antigravity, Grok Build, Hermes, GitHub Copilot, two separate copies of OpenCode, and pi. Herdr keeps them organized, one labelled tab per agent, and brings them back after a reboot. Most of them share one mcpproxy instance for tools. One of those tools talks to a service that needs a personal API key, and only one agent ever holds that key: a deliberately fenced-in OpenCode. The other agents can see the tool, but they can’t authenticate to the service behind it. When they need that service, they hand the task to that OpenCode through Herdr.
5 minute read
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The Model Context Protocol defines a standard way for AI clients to discover and call tools, but standing up a personal MCP server still usually means writing Python glue code, wiring up a framework, and restarting a process every time you add a tool. mcpproxy takes a different approach: every tool provider is a single YAML file, the server reloads tools at startup without any code changes to the host, and a browser-based web UI handles the full provider lifecycle — editing, secret management, and live command streaming — without leaving the browser.
11 minute read
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Most large language model interfaces are designed for developers or for a general consumer audience. Faculty who want to use an AI assistant to help with grading, research, or course preparation either accept the limitations of a consumer chat interface or invest significant time learning to run and configure a developer-grade setup. BetterWebUI is an attempt to close that gap. It is a local Python/FastAPI server with a pure-HTML front end that connects to an existing OpenWebUI instance and layers on the features that make an agentic assistant genuinely useful in a higher-education context: workspaces, skills, MCP server management, CLI shortcuts, math rendering, and a suite of integrations with sibling agentic services.
9 minute read
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Most LLM agents can read files, call APIs, and run shell commands, but they have no reliable way to operate a graphical desktop. They cannot click a button in a running application, verify that a dialog appeared, fill a form field, or observe what is currently on screen. AutoGUI is a research prototype that fills that gap. It connects any OpenAI-compatible LLM — including models served locally through OpenWebUI or directly through Ollama — to a full suite of OS-level desktop controls via a ReAct-style agentic loop.
