Large Language Models on Mohammad Movahedi

Agentic AI as a Research Tool

Sat, 30 May 2026 00:00:00 +0000

This scratchpad explores how agentic AI can be used as a practical research tool. It focuses on understanding how AI agents can support literature review, data analysis, writing, coding, workflow automation, and knowledge organization.

Local LLMs

Thu, 28 May 2026 00:00:00 +0000

This scratchpad collects my notes on running and working with local large language models. It is meant to better understand model deployment, inference tools, hardware requirements, quantization, fine-tuning, evaluation, and practical workflows for using LLMs outside cloud-based platforms.

Persona-Based Hurricane Evacuation Travel Demand Analysis

Fri, 15 May 2026 00:00:00 +0000

🌀 The Challenge of Rural Evacuation Planning

Florida continues to be the most hurricane-prone state in the United States. While evacuation orders play a significant role in reducing casualties, their effectiveness relies heavily on household decision-making. In rural communities, such as the Florida Panhandle, this is complicated by limited infrastructure, longer travel distances, and resource constraints. Current evacuation demand models often rely on oversimplified assumptions of rational decision-making, failing to capture the stress, urgency, and irrationality inherent in disaster scenarios.

Introduction to LLM

Fri, 01 May 2026 00:00:00 +0000

This scratchpad collects the LLM introduction series, an eight-part walkthrough from transformer basics to responsible deployment. Many examples use evacuation and transportation planning as a running case, but the concepts apply broadly.

Simulating Community Behaviors with LLMs

Thu, 16 Apr 2026 00:00:00 +0000

🚧 The Challenge of Debris Management

Following catastrophic events like Hurricane Ian, post-disaster debris management becomes a critical, time-sensitive logistical challenge. Traditional planning relies heavily on volume estimation and routing, treating communities as passive entities. However, emergent human behaviors—such as illegal debris dumping—introduce highly stochastic burdens that derail recovery efficiency, amplify health risks, and drastically increase municipal costs.

The Crossroads of LLMs and Traffic Control

Mon, 16 Dec 2024 00:00:00 +0000

🚦 The Urban Gridlock Challenge

Urban traffic congestion has severe economic and environmental impacts. Traditional Adaptive Traffic Control Systems (ATCS)—which rely on fixed-time, gap-based, or delay-based logic—often struggle to adapt to dynamic, complex, and unpredictable real-world traffic flows. Designing a truly responsive traffic controller requires a system capable of human-like reasoning and planning.