AI Engineer | Machine Learning Specialist | Inventor in Biomedical and Computational Technologies

As an AI engineer and inventor, I specialize in developing sophisticated machine learning solutions that integrate computer vision, reinforcement learning, natural language processing, and numerical simulations. My work emphasizes practical applications in biomedical signal processing, engineering tools, and AI-driven automation. With a foundation in brain-computer interfaces and EEG analysis, I bridge theoretical AI with real-world engineering challenges, creating tools that enhance decision-making and efficiency across domains.

Core Focus Areas:

• Brain-Computer Interfaces and EEG Signal Processing
• Machine Learning for Biomedical and Time-Series Data
• Computer Vision and Image Classification
• Reinforcement Learning and Algorithmic Optimization
• Natural Language Processing, including ASR and Sentiment Analysis
• Prompt Engineering and LLM Automation
• Numerical Simulations in Engineering (e.g., Heat Transfer, Material Processing)

Technical Specializations:

• Deep Learning Architectures for Signal Decoding
• Real-Time Data Analysis and Feature Extraction
• Automated AI Tool Development for Interactive Systems
• Multilingual AI Applications (e.g., Persian Language Processing)

• Gold Medal - International Invention Competition (2024)
• Silver Medals - International Invention Competitions (2021, 2023)
• Innovation Award Winner - For contributions to AI and neurotechnology

• Active open-source developer in AI and machine learning repositories
• Research in EEG-based BCI systems and neural data analysis
• Development of novel algorithms for signal processing and AI automation

Python ████████████ Advanced
C █████████ Proficient
Java ████████ Proficient
C++ ████████ Proficient
Fortran ██████ Intermediate

• Deep Learning: PyTorch, TensorFlow, Scikit-learn
• Computer Vision: OpenCV, Vision Transformers
• NLP and LLMs: OpenAI API, Prompt Engineering Tools
• Signal Processing: SciPy, MNE-Python (for EEG), NumPy, Pandas
• Reinforcement Learning: Q-Learning, Graph Algorithms (BFS)

• Version Control: Git, GitHub
• Containerization: Docker
• Cloud Services: AWS
• Environments: Jupyter Notebook, VS Code, PyCharm

My repositories showcase a diverse portfolio of AI and engineering innovations. Below is a curated selection:

Repository Link
Focused on EEG analysis using Jupyter Notebooks, including EEG-BCI implementations and transformer models for neural data. Demonstrates expertise in biomedical signal processing and machine learning applications in neuroscience.

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A Python-based project integrating automatic speech recognition (ASR) and sentiment analysis for Persian language data. Highlights multilingual NLP capabilities and audio processing techniques.

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Jupyter Notebook workshop on prompt engineering for large language models (LLMs), featuring math-related LLM applications. Emphasizes interactive AI design and optimization.

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An interactive tool for automating prompt generation and evaluation using LLMs. Includes features for template customization, scoring, and task-specific optimization. Built with Python and OpenAI integration, ideal for efficient AI prompt design.

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Exploration of chatbot systems, including RAG-based legal QA implementations in Jupyter Notebooks. Focuses on conversational AI, NLP, and knowledge retrieval.

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Implementation of Vision Transformers for classifying Persian handwritten digits. Showcases advanced computer vision techniques for specialized datasets.

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Python simulation using Q-Learning and BFS for gameplay optimization. Illustrates reinforcement learning and graph-based AI in interactive environments.

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A practical Python calculator for selecting laser parameters in material welding and cutting. Integrates engineering simulations with material science.

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C-based program solving heat transfer equations iteratively. Demonstrates numerical methods for physical simulations.

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Forked and enhanced Python project for backend AI solutions, including prompt handling and interactive applications.

"Driven by a commitment to innovation and excellence, I approach complex problems with rigorous analysis and creative solutions. My goal is to advance AI technologies that empower human capabilities, particularly in neuroscience and engineering, while fostering collaborative progress in the field."

Professional Networks:

• LinkedIn: inv-alizare
• Kaggle: invalizare
• Telegram: @baaabaei

Open to Opportunities:

• Collaborations in AI, machine learning, and neurotechnology projects
• Discussions on BCI development and signal processing
• Contributions to open-source initiatives in NLP and engineering simulations
• Knowledge exchange in prompt engineering and LLM applications