Curriculum Vitae

GPA: 17.38/20. Thesis: Scoring Augmented Sentences Using Autoencoder and Semantic Textual Similarity (STS) with Siamese BERT. Courses: Advanced AI, Computational Data Mining, Advanced Data Mining, Machine Learning, Text Mining, Web Mining, Advanced Databases, Big Data (PySpark), Expert Systems, Distributed Systems.

GPA: 14.69/20. Founded and led the Computer Science Association, organizing inter-university workshops. Government Scholarship recipient (Bachelor's and Master's).

Built and evaluated a local PDF RAG system; building a ReAct agent from scratch, a LangChain rebuild and a GraphRAG project in public repositories; studying German (B2 course).

Engineered RAG pipelines with LangChain and served them via API endpoints for industrial clients, cutting design-iteration time by ~15% through automated prompt optimization; built AI agent systems on MCP Server to standardize how LLMs access enterprise data sources; designed reproducible end-to-end AI pipelines, packaging select services with FastAPI and Docker.

Built consent-based data-collection pipelines (Google Forms/Workspace to GCP) where users voluntarily shared professional profile data (e.g., from LinkedIn) with explicit permission, and applied LLMs to analyze it; architected Neo4j graph databases for semantic search in LLM applications, improving relevant data-insight retrieval by ~30%; raised LLM output accuracy by ~15% with few-shot and structured prompting.

Delivered fraud-detection and sentiment-analysis models for unstructured text (95% precision); built and validated time-series forecasting frameworks (LSTM, XGBoost); developed Django-based APIs that improved pricing efficiency by ~30%, plus web-scraping pipelines for market intelligence; shipped multilingual (English/Persian) NLP solutions that cut manual processing time by ~40%.

Built automated web-scraping and data pipelines that kept e-commerce datasets current; analyzed e-commerce data trends to optimize marketing strategies and pricing decisions.

Supported virtualization servers and network services; built an internal management dashboard for decision-making.

Researched NLP with a focus on Transformers and autoencoder models; designed Siamese BERT architectures for semantic scoring of augmented sentences, benchmarked against SBERT and Augmented SBERT baselines; built LSTM/XGBoost-based predictive models for traffic flow.

Certificate of Achievement.

Introduction to Python, Intermediate Python, Intermediate Importing Data in Python, Introduction to SQL, Intermediate SQL.

Course certificate, verifiable online.

Networking fundamentals, from my early IT and network administration years.

Self-paced courses supporting my graph-retrieval work.

10–20 September 2020.

24–29 February 2016.

Organized workshops introducing computer science concepts and career roadmaps; mentored students with academic guidance and motivational talks; partnered with industry professionals to secure resources and discounts.