- 🎓 Senior Computer Engineering student with a strong academic background and a passion for pushing the boundaries of Artificial Intelligence.
- 💡 Deeply fascinated by Natural Language Processing (NLP), Deep Learning, and Machine Learning, with a particular interest in:
- Large Language Models (LLMs): Their architecture, fine-tuning, and application.
- AI Agents & Multi-Agent Systems: Designing autonomous and collaborative AI entities.
- Explainable AI (XAI): Making complex models transparent and interpretable.
- Retrieval-Augmented Generation (RAG): Enhancing LLMs with external knowledge.
- 💻 Junior Data Analyst with practical experience in data manipulation and insight generation.
- 🚀 Committed to advanced research and innovation in NLP, with a vision to make impactful contributions to the field.
- 🌐 Actively contributing to the open-source AI ecosystem and exploring new frontiers in AI research.
My passion lies at the intersection of theoretical advancements and practical applications in AI. I am particularly keen on exploring:
- 🧠 Advanced NLP Architectures: Diving deeper into novel transformer models, efficient attention mechanisms, and multimodal NLP.
- 🤖 Autonomous AI Agents & Multi-Agent Systems: Researching robust planning, memory management, and self-correction mechanisms for intelligent agents, especially in collaborative environments.
- 📚 Knowledge-Grounded LLMs & RAG: Enhancing Large Language Models with external knowledge bases to reduce hallucinations, improve factual accuracy, and enable complex reasoning.
- 🔍 Explainable AI (XAI) for Complex Models: Developing methods to understand and interpret the decisions of black-box deep learning models.
- 📊 Scalable Data Pipelines for AI: Optimizing data processing and feature engineering for large-scale ML/DL projects, ensuring efficiency and reliability.
- 🌐 Ethical AI & Bias Mitigation: Investigating fairness, accountability, and transparency in AI systems to build responsible technology.
- 🚀 Open-Source Contributions: Actively seeking opportunities to contribute to impactful open-source AI projects and collaborate with the wider community.
Here are some of my key projects and research explorations that highlight my interests and capabilities in NLP and AI. Each project link leads to its dedicated repository with detailed documentation.
- Date: August 2025
- Problem: Manually detecting code plagiarism among student submissions is time-consuming and error-prone, especially when students rename variables or reformat code.
- Solution: Built an advanced plagiarism detection tool that analyzes Python code structure using ASTs, TF-IDF, and multiple similarity metrics. The system normalizes variable names, extracts structural fingerprints, and generates visual reports (network graphs & dashboards) to highlight suspicious pairs with risk levels.
- Technologies: Python and it's libraries:
ast,pandas,networkx,matplotlib,seaborn,sklearn,difflib - Links:
- Date: August 2025
- Problem: Understanding the step-by-step execution and comparative efficiency of various sorting algorithms can be abstract.
- Solution: Developed an interactive web application that visually demonstrates the real-time sorting process of multiple algorithms. Features include dynamic array generation, adjustable animation speed, live performance metrics (comparisons, swaps, actual execution time), and a historical log of previous runs. This tool provides clear, actionable insights into algorithm behavior.
- Technologies: HTML, CSS (Tailwind CSS), JavaScript.
- Links:
- Date: July 2025
- Problem: Creating an interactive web-deployable TTS system with customizable voice parameters.
- Solution: Engineered the system using Coqui TTS for high-quality audio generation and Gradio for a user-friendly interface. Implemented waveform visualization and deployed successfully on Hugging Face Spaces, showcasing proficiency in audio processing and cloud deployment.
- Technologies: Python, Coqui TTS, Gradio, Hugging Face Spaces.
- Links:
- Date: July 2025
- Problem: Efficiently aggregating cutting-edge AI news, papers, and repositories from diverse sources.
- Solution: Developed a robust Python-powered Telegram bot for real-time aggregation and delivery. Utilized RSS feeds, web scraping (GitHub Trending), and Hacker News API for source integration. Implemented persistent storage (SQLite) for duplicate prevention and deployed via GitHub Actions for automated, scheduled updates.
- Technologies: Python, RSS, Web Scraping, GitHub API, SQLite, GitHub Actions, Telegram API.
- Links:
- Date: July 2025
- Problem: Building a sentiment analysis model capable of handling sarcasm, irony, and mixed opinions.
- Solution: Built a hybrid deep model combining RoBERTa embeddings with a BiLSTM and an Attention Mechanism to model subtle language signals. Tuned on IMDB and enhanced with sarcastic samples and custom error analysis. Designed for multilingual support (e.g., Persian with
xlm-roberta). - Technologies: Python, PyTorch, RoBERTa, BiLSTM, Attention, Gradio, Hugging Face Spaces.
- Links:
- Date: March 2025
- Problem: Developing a system for querying real-world course and professor reviews.
- Solution: Developed a chatbot using RAG (Retrieval-Augmented Generation). Combined FAISS, Pandas, and Hugging Face models for embeddings to build a scalable question-answering system over semi-structured data.
- Technologies: Python, RAG, FAISS, Pandas, Hugging Face Transformers, LangChain.
- Links:
- Date: Oct 2023 – Dec 2023
- Problem: Contributing to an interdisciplinary research project on AI-aided prototyping and 3D printing.
- Contribution: Developed a mobile application to present technical information for visitors and judges at a national exhibition. Project recognized among top innovations of the year in Iran's 2023 exhibition.
- Technologies: (Specifics from your side, e.g., Python, Mobile Dev Framework, 3D Modeling tools)
- Links:
This section outlines the programming languages, frameworks, libraries, and tools I utilize in my work and projects.
