Introduction
This page outlines the vision, structure, and ongoing progress of my research on AI-assisted reasoning and human-centered knowledge tools. The goal is to support high-stakes decision-making by enhancing how people interact with information, collaborate, and think.
Research Vision
My research explores the intersection of knowledge reasoning, AI-augmented documentation, and causal modeling, with a focus on:
- Supporting human decision-making under uncertainty
- Enabling AI systems to reason alongside humans
- Designing explainable, collaborative, and intuitive tools
The ultimate aim is to build a system that can bridge the gap between human thinking and machine inference, especially in real-world, high-stakes environments such as remote teamwork, project planning, and knowledge transfer.
Milestones
| Phase | Title | Status | Description |
|---|---|---|---|
| 1 | UX & Summarization Design | ✅ Completed | Designed user flow and interface for summarizing team discussions. |
| 2 | Causal Modeling Integration | 🔄 In Progress | Building and evaluating causal graphs using DoWhy and custom data. |
| 3 | AI-Augmented Documentation | ⏳ Planned | Creating a GPT-powered framework for iterative documentation. |
| 4 | Knowledge Graph & Dashboard | ⏳ Planned | Structuring and visualizing domain knowledge with Weaviate or Neo4j. |
| 5 | Final Integration & Testing | ⏳ Planned | Connecting all modules into a unified product (PoC). |
Demos / Prototypes
Writings
Research Tools & Stack
Programming: Python, JavaScript, Jupyter Notebooks
AI Libraries: LangChain, GPT-4o, Weaviate, DoWhy, NetworkX
Contact & Collaboration
I welcome opportunities to discuss related topics or collaborate on similar projects.