🎓 Master of Science - Computer Science @ Simon Fraser University, Vancouver, BC
💼 Machine Learning Engineer @ MARZ (Monsters Aliens Robots Zombies) | AI Researcher
📍 Toronto, Canada
📫 LinkedIn | GitHub |

• Programming Languages: Python, C, Java, SQL, JavaScript (React.js, Node.js, D3.js)
• Technologies & Frameworks: PyTorch, TensorFlow, Scikit-learn, OpenCV, AWS, Docker, FastAPI, MongoDB
• Core Expertise: Machine Learning, Deep Learning, NLP, Computer Vision, Big Data, Cloud Computing

• Developed ML/DL models for predicting antibiotic resistance in Mycobacterium tuberculosis and E. coli.
• Tech Stack: Python, PyTorch, Transformers, NLP, GenAI, RAG, LLMs.

• Created a deep learning pipeline to automate de-aging, cosmetic, and prosthetic fixes in VFX.
• 300x faster than traditional methods, 80% cost reduction, no capacity constraints.
• Tech Stack: TensorFlow, PyTorch, Apache Airflow, AWS (S3, EC2, Lambda), Docker.

• Achieved 77.79% accuracy using patch embedding + transformer encoders for feature extraction.
• Tech Stack: Transformer, PyTorch, Matplotlib, Seaborn.

• Implemented a RAG-based chatbot using Langchain, Gradio, FAISS to boost query resolution by 60%.
• Tech Stack: PyPDF, Transformers, Langchain, FastAPI.

• LogicBench: Built a benchmark for LLM logical reasoning evaluation using Hugging Face Transformers.
• GridPuzzle Dataset: Scraped and structured 274 grid-based logic puzzles, improving AI puzzle-solving efficiency by 30%.
• PuzzleEval Metric: Automated reasoning chain evaluation for LLMs, boosting interpretability and task success rate by 20%.

🔗 Website/Portfolio (Coming Soon!)
📧 rezaie2114@gmail.com
🐦 Twitter: @mohrezaie

🚀 Always open to exciting AI/ML collaborations, research opportunities, and challenges!