I lead Machine Learning at General Sense, where I architect models to read out brain activity for chemical detection. I have a PhD in this sort of thing from the University of Washington, where I developed computational models of targeted brain stimulation and brain signal analysis. Before my PhD I worked as a machine learning engineer for multiple startups. I have built a couple apps and websites of my own which use LLM applications and enjoy continuing to learn about them. I also hold degrees in Physics and Cognitive Science from UC Berkeley. Lifelong computer nerd.

Wanting to learn more about building agentic programs. Wanting to connect with others on any technical topic. I do BCI decoding but thats rare so probably wont meet too many people about that specific topic.

Leading the development of a real-time neural decoding stack at General Sense to translate olfactory neural activity into chemical intelligence. This involves designing and deploying machine learning algorithms for signal processing and decoding complex neural data. In addition to algorithms I spend a lot of time thinking about and designing scaffolding and frameworks to serve as the backbone of AI systems.

I’m Maxwell Chandler, a senior frontend and UX/product engineer with 7+ years of experience building production software across React, Next.js, TypeScript, AI-assisted UX, design systems, and platform architecture. I’ve shipped work for companies including Rapid7, SelectQuote, Bolt, Kargo, Coach Training EDU, and others, often turning complex content or product systems into faster, more maintainable user experiences. I’m currently at MasteryPrep building an AI-powered LMS and helping shape how AI tutors, educators, students, and coding agents fit into real workflows. I care about interfaces that are clear, fast, accessible, and polished enough to earn trust.

Across my work, I’m drawn to products where complex systems need to feel usable: education tools, developer workflows, design systems, and expressive interfaces. I want to learn more about AI inside real product workflows: how tutors, teachers, students, and engineers can stay in control while software handles more of the busywork. I’d love to meet people building learning tools, creative frontends, and systems that make teams faster.

At MasteryPrep, I’m building the next generation of our AI-powered LMS: React 19 architecture, educator/student workflows, design-system primitives, and Cap, our AI tutor with tool-calling and teacher oversight. Outside work, I’m tinkering on Excaliber.ai, an agentic developer assessment platform for evaluating how engineers plan, prompt, review, and ship with coding agents.

I’m a Software Engineer at Jeavio, with over 2 years of experience. I’m currently pursuing an MS in Computer Science at Northeastern University, with a previous education in Computer Engineering from Dharmsinh Desai University. My expertise lies in technical architecture, with a focus on AI. My current projects include building an LLM-powered knowledge platform and architecting microservices for video transcription systems.

Technical architecture, AI architecture, LLM-powered knowledge platforms, Retrieval-Augmented Generation (RAG), vector databases, hybrid search, microservices, async ingestion pipelines, ML model deployment, speech-to-text systems, full-stack development.

My most recent project was an automation pipeline built on n8n using gemini apis. I love developing full-stack applications with Django, React, and MongoDB, alongside Java Spring Boot services.