Mohamed Awadalla

AI/ML Engineer & Computer Science Student

Brooklyn, NY
917-436-9873
Mohamedawadalla75@gmail.com
2026
Graduation
AI/ML
Specialization

About Me

I am a Computer Science student at Long Island University's Honors College with a strong focus on Artificial Intelligence, Machine Learning, and Cybersecurity. My technical expertise spans across modern AI frameworks, neural networks, and large language models, with hands-on experience in fine-tuning and evaluating LLMs.

Currently serving as a Legal Intern at NYC Emergency Management, I'm developing full-stack applications and intelligent document processing systems using AI/ML technologies. My passion lies in leveraging cutting-edge AI to solve real-world problems and create innovative solutions.

I actively engage in machine learning projects, from fine-tuning LLaMA models for specialized knowledge bases to building neural networks for financial forecasting. My goal is to contribute meaningfully to the AI/ML field and help organizations harness the power of artificial intelligence.

Education

Long Island University
Honors College
Brooklyn, NY
Bachelor of Science in Computer Science
Anticipated 2026
Dean's List, Dean Scholar

Skills

AI & Machine Learning

  • Natural Language Processing (NLP)
  • Neural Networks & Deep Learning
  • PyTorch Framework
  • Large Language Models (LLMs)
  • Fine-tuning & Evaluating LLMs
  • Prompt Engineering
  • Machine Learning Fundamentals
  • Data Analysis & Visualization
  • Process Automation (Python)
  • Scikit-learn, Pandas, NumPy

Languages & Databases

  • Python (Advanced)
  • C++
  • MySQL
  • JavaScript/HTML/CSS
  • SQL & Database Design

Developer Tools & Platforms

  • Operating Systems (Windows, MacOS, Linux)
  • Version Control (Git)
  • AI Coding Agents
  • Full-Stack Development
  • VMware & Virtualization
  • Splunk & ELK Stack
  • Cloud Platforms (AWS)

Product & Communication

  • Rapid Prototyping
  • Cross-Functional Collaboration
  • Technical Communication
  • MS Office Suite
  • Project Coordination
  • Time Management
  • Problem-Solving

Relevant Experience

Legal Intern - Development

New York City Emergency Management
Brooklyn, NY
June 2025 – Present

• Developed a full-stack web application for a Disaster Law Symposium, enabling 1000+ participants to register and attend both online and in-person sessions, demonstrating scalable system design and user experience optimization

• Built an intelligent Document Processing Suite that automated the sorting and renaming of 16,000+ procurement contracts and supporting documents using Python, implementing machine learning-based document classification, OCR technology for scanned documents, and intelligent vendor name standardization

• Engineered automated workflow solutions that reduced manual contract processing time by implementing smart document classification (MSA, SOW, NDA, Purchase Orders) and metadata extraction for large-scale document management systems

Honors College Assistant

Long Island University Brooklyn
Brooklyn, NY
Sep 2022 - Present

• Led engaging campus tours for 100+ prospective students and their families, effectively showcasing university programs and campus life while providing exceptional support throughout the admissions process

• Assist in coordinating and executing 15+ Honors College events annually, programs, and activities, ensuring an engaging community for 200+ students and leveraging data-driven insights to optimize event planning and student engagement strategies

• Collaborate with staff to manage communications and outreach efforts across 5+ digital platforms, enhancing visibility and engagement through promotional materials, and automated workflow solutions to streamline administrative processes

Projects

NBA Analytics Conversational AI - Fine-tuned LLaMA 3.2

Fine-tuned LLaMA 3.2 model using LoRA techniques to create a specialized New York Knicks knowledge base, implementing custom tokenization and data preprocessing pipelines for sports analytics applications.

Developed automated data collection system for NBA Twitter content, creating text cleaning algorithms and sentiment analysis tools to extract meaningful basketball insights and performance metrics from social media data.

LLaMA 3.2 LoRA NLP Python Sentiment Analysis

Automated Log Analysis

Developed Python-based data processing pipeline for parsing and analyzing large-scale security logs, implementing statistical analysis and anomaly detection algorithms for real-time threat intelligence.

Integrated Splunk and ELK Stack for distributed data processing, creating automated alert systems that reduced incident response time by 40% through intelligent pattern recognition.

Built comprehensive monitoring dashboard with data visualization components, enabling real-time analysis of system performance metrics and security event correlation.

Python Splunk ELK Stack Anomaly Detection Data Visualization

Stock Price Prediction Neural Network

Developed LSTM neural network using PyTorch to predict stock price movements, implementing time series analysis and feature engineering techniques for financial market data processing.

Built comprehensive data pipeline integrating multiple financial APIs, creating automated preprocessing workflows for handling missing data, normalization, and sequential feature extraction.

Achieved predictive accuracy improvements through hyperparameter optimization and ensemble methods, demonstrating practical application of deep learning for financial forecasting and risk analysis.

PyTorch LSTM Time Series Financial APIs Deep Learning

Contact Information

I'm happy to discuss AI/ML, Cybersecurity, research opportunities, and professional collaborations. Feel free to reach out for with any inquiries or potential opportunities.