Skip to content
View pozapas's full-sized avatar
⚽
⚽
12 followers · 9 following

Achievements

Achievement: StarstruckAchievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: YOLOAchievement: Pull Shark

Achievements

Achievement: StarstruckAchievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: YOLOAchievement: Pull Shark

Highlights

  • Pro

Block or report pozapas

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
pozapas/README.md

Who I Am ( 👨‍💻 + 🍕 + ☕)

Human Behavior | ML & Applied AI | Causality in Engineering | Evacuation

I am a transportation engineer and researcher specializing in pedestrian dynamics, human behavior modeling, and AI applications in urban environments. My work focuses on developing mathematical models, agent-based simulations, and AI-driven frameworks to better understand and improve crowd movement, safety, and emergency evacuation processes.

I am passionate about advancing research at the intersection of complexity science, transportation systems, and artificial intelligence. My goal is to contribute to the design of smarter, safer, and more resilient urban environments.

Advancing pedestrian safety and crowd resilience through data-driven research and AI-powered modeling.

  • 📍 Based in San Marcos, Texas
  • 📧 Contact: amir.rafe@txstate.edu
  • 📂 Projects and Publications: See pinned repositories below

Skills

Python R VS Code Vim MySQL PostgreSQL Heroku Flask Django Docker PyTorch TensorFlow

Socials

Support Me

Buy Me A Coffee

Pinned Loading

  1. awesome-causal-ai awesome-causal-ai Public

    A meticulously curated collection of cutting-edge research, frameworks, and methodologies in Causal Artificial Intelligence.

    10

  2. awesome-crowdynamics awesome-crowdynamics Public

    A curated collection of open-source tools and resources for studying and analyzing crowd dynamics, pedestrian flow, and evacuation strategies.

    31 5

  3. pAIper pAIper Public

    pAIper - AI-Powered Research Paper Discovery

    Python

  4. Crowd-Analyzer Crowd-Analyzer Public

    Crowd Analyzer is a Python application for analyzing pedestrian and crowd mobility patterns using computer vision and machine learning techniques.

    Python 13 6

  5. PEDAT PEDAT Public

    Pedestrian data visualization dashboard

    Python 2 1

  6. crowdskills crowdskills Public

    Advanced AI skills for crowd, pedestrian, evacuation, and mobility simulation workflows, including model setup, scenario design, automation, validation, and results analysis.

    Python 1 1