NCUR 2025 Conference Presentation
National Conference on Undergraduate Research
Attendees Engaged During Poster Session
Dedicated Research Presentation Session
Emergency Response Systems Research
NCUR 2025 Research Presentation
🚨 Proud to present my research at NCUR 2025! 🚨 Presented "Using Large Language Models to Enhance Emergency Response Systems: A Context Awareness Approach" to over 60 attendees during a dedicated two-hour poster session at the premier national undergraduate research conference in Pittsburgh, Pennsylvania.
About NCUR
Premier annual event celebrating undergraduate scholarship across all academic disciplines, organized by the Council on Undergraduate Research.
- National Platform: Students from universities nationwide
- Diverse Formats: Posters, oral presentations, performances
- Intellectual Exchange: Thousands of undergraduate researchers
- Academic Excellence: Showcasing research breadth and depth
Research Focus
AI-Powered Emergency Response using Large Language Models to revolutionize 911 systems and support human dispatchers.
- LLM Integration: LLaMA 2 for intelligent assistance
- Context Awareness: Real-time situation understanding
- Human Support: Reducing mental pressure on operators
- System Enhancement: Improving response efficiency
Key Performance Results
Measurable accuracy achievements in Named Entity Recognition and emergency classification systems.
- Address Extraction: 76.5% accuracy from 911 call datasets
- Name Recognition: 48.3% accuracy from voice calls
- Emergency Classification: Accurate categorization system
- Real-time Processing: Live call transcription capability
Technical Innovations
Five core technical components creating a comprehensive AI-powered emergency response enhancement system.
- Named Entity Recognition: Automated caller information extraction
- Emergency Classification: Intelligent emergency type detection
- Modular LLM Architecture: Specialized models per emergency type
- Context-Aware Recommendations: Personalized response protocols
- Sentiment Analysis: Operator stress level monitoring
Conference Networking
Exceptional engagement with diverse academic and industry professionals during the two-hour poster session.
- Academic Discussions: CS faculty on fine-tuning vs. prompt engineering
- Industry Perspectives: Emergency services professionals insights
- Interdisciplinary Connections: Psychology and public health researchers
- Technical Deep-dives: Privacy, HIPAA compliance, data protection
Mentorship Recognition
Exceptional support from research mentors at The American University in Cairo enabling this achievement.
- Dr. Sherif G. Aly Ahmed: Research guidance and expertise
- Dr. Amr El Mougy: Technical mentorship and support
- AUC Research Environment: Resources and opportunities
- Undergraduate Excellence: Fostering ambitious research projects
System Architecture & Implementation
| Component | Technology | Purpose |
|---|---|---|
| Speech-to-Text | OpenAI Whisper | Real-time call transcription with noise robustness |
| Named Entity Recognition | BERT-large-cased | Extract caller information and emergency location |
| Emergency Classification | Custom LLM Classifier | Categorize emergency types for proper resource allocation |
| Medical LLM | LLaMA 2 (13B parameters) | Specialized medical emergency assistance and procedures |
| Sentiment Analysis | Custom emotion detection | Monitor stress levels for operator wellbeing |
| System Integration | Modular Architecture | Real-time emergency response enhancement |
Research Innovations & Future Directions
Comparative Studies
Privacy & Security
Disaster Response
Multilingual Support
Research Poster Presentation
My research poster presented at NCUR 2025, detailing the modular LLM architecture and system implementation for emergency response enhancement.
Conference Networking & Impact
Presenting at NCUR 2025 has been a transformative experience that has strengthened my commitment to pursuing research in AI applications for social good. The enthusiastic reception and valuable feedback will undoubtedly influence the next phases of this research project.
This experience has reinforced my passion for developing technology solutions that make a real difference in people's lives, particularly in critical situations where every second counts. The future is bright for AI-powered emergency response systems! 🚀