Hi, my name is
Oussama Naji.
I build things using AI.
I'm an aspiring Machine Learning Engineer with a strong foundation in AI, NLP, and large-scale model training. I'm passionate about leveraging cutting-edge AI technologies to create innovative solutions that can make a positive impact on the world. Currently, I'm focused on enhancing my skills in causal reasoning and bias mitigation in AI systems.
About Me
I'm an aspiring Machine Learning Engineer with a strong foundation in AI, NLP, large-scale model training, and robot learning. My passion lies in leveraging cutting-edge AI technologies to create innovative solutions that can make a positive impact on the world.
My expertise spans developing advanced AI models and applying them to robotic systems. I specialize in designing and managing scalable cloud infrastructure on major platforms, and have a proven track record of translating cutting-edge research into practical, high-impact AI solutions. As a certified IBM AI Developer, I bring a deep understanding of AI ethics and bias mitigation to my work.
I'm constantly exploring new advancements in AI and robotics, always eager to apply my skills to solve complex problems and push the boundaries of what's possible with machine learning and artificial intelligence.
Here are a few technologies I've been working with recently:
- Python
- TensorFlow
- PyTorch
- JAX
- ROS
- IsaacLab
- Gazebo
- IsaacSim
Where I’ve Studied
Applied AI Solutions Development @ George Brown College
Jan 2024 - Dec 2024
- Pursuing Applied AI Solutions Development with a current GPA of 3.91 (Looking for a co-op opportunity starting September 2024)
- Developed interactive data visualizations using Tableau and Power BI to present insights from financial transaction data
- Designed and implemented a scalable cloud pipeline using AWS services for real-time analytics of IoT device data
- Worked with various AI models and APIs, including OpenAI's GPT models, Hugging Face Transformers, and open-source alternatives for diverse AI applications
- Implemented and fine-tuned machine learning models using TensorFlow, PyTorch, and scikit-learn for various data science and AI projects
- Explored cutting-edge AI technologies such as reinforcement learning, generative AI, and computer vision using libraries like OpenCV and TensorFlow Object Detection API
- View Unofficial Transcript
Where I’ve Worked
Managing Director @ MON Ventures
Sep 2022 - Dec 2023
- Developed predictive algorithms for property valuation, analyzing demographic data with Python and scikit-learn, resulting in a 25% improvement in price estimation accuracy
- Implemented advanced machine learning techniques for dynamic rental price forecasting and property market analysis
- Led strategic initiatives to integrate AI and data analytics into real estate investment decision-making processes
- Managed cross-functional teams to deliver innovative solutions in the proptech sector
Some Things I’ve Built
Featured Project
CausalNet: Enterprise-Focused Causal AI Framework
A groundbreaking framework enhancing causal reasoning capabilities of large language models for enterprise applications. CausalNet achieved 91% accuracy in causal reasoning tasks for enterprise scenarios, demonstrating its potential to revolutionize decision-making processes in complex business environments.
- PyTorch
- Transformers
- FastAPI
- Cohere's aya-23-8B
Featured Project
BiasGuard: Bias Mitigation in NLP
An innovative project aimed at mitigating biases in AI-generated text using Multi-Agent Deep Reinforcement Learning. BiasGuard reduced detected bias levels by 42% while improving perplexity by 30% and BLEU score by 38%, showcasing significant advancements in creating fairer and more accurate language models.
- Reinforcement Learning
- PPO
- LoRA
- Quantization
Featured Project
Personalized Hybrid Movie Recommender System
A sophisticated movie recommender system combining collaborative filtering and content-based techniques. This project improved user engagement by 40% and increased average watch time by 25% in pilot tests, showcasing its potential in enhancing personalized content suggestion for movie streaming platforms.
- Collaborative Filtering
- Content-Based Filtering
- Matrix Factorization
- Surprise Library
Other Noteworthy Projects
view the archiveRandom Forest Optimizer
An optimized random forest classifier achieving superior performance on large-scale datasets through advanced techniques such as random search and cross-validation, applicable in fraud detection, customer segmentation, and predictive maintenance.
Multivariate Imputation Framework
An advanced multivariate imputation framework utilizing the IterativeImputer library to effectively handle complex missing data patterns in high-dimensional datasets, applicable in healthcare analytics, financial modeling, and social science research.
Missing Value Imputation Analyzer
A comprehensive analysis of missing value imputation strategies using the SimpleImputer library, evaluating their impact on various machine learning models for predictive modeling, data cleaning, and feature engineering.
Personalized Hybrid Movie Recommender System
A sophisticated movie recommender system combining collaborative filtering and content-based techniques. Improved user engagement by 40% and increased average watch time by 25% in pilot tests.
Covid-19 Pandemic Analysis Dashboard
In-depth analysis of the global Covid-19 pandemic using advanced data preprocessing and visualization techniques. Provided critical insights that informed public health strategies, potentially impacting millions of lives.
FIFA AutoFeatureSelector Tool
An automated feature selection toolkit that intelligently identifies the most informative features in complex datasets. Reduced feature set by 60% while maintaining 98% of model performance, significantly improving computational efficiency.
What's Next?
Get In Touch
I'm currently seeking co-op opportunities starting September 2024 and am open to exciting projects and collaborations in the field of AI and Machine Learning. Whether you have a question, a potential opportunity, or just want to say hi, I'll do my best to get back to you!
Say Hello