Meelad Dashti
About Me
I’m an AI/ML Engineer currently working at Zirak srl in Turin, Italy, where I architect and develop production-grade AI systems. I specialize in building real-time transcription pipelines, RAG systems, and LLM-powered applications that solve real-world problems.
Currently pursuing my Master’s thesis at the University of Twente on Hyperbolic Compositionality in Vision-Language Models, while completing my M.Sc. in Computer Engineering (AI & Data Analytics) at Politecnico di Torino.
What I Do
My work focuses on cutting-edge AI technologies:
- Real-time AI Systems: Built a meeting platform with <2s latency using WhisperX and Faster-Whisper
- RAG & Vector Search: End-to-end pipelines with ChromaDB, semantic search, and cross-encoder reranking
- LLM Applications: Agentic workflows with LangGraph, fine-tuning LLaMA models with LoRA/QLoRA
- Multimodal AI: Research in vision-language models and hyperbolic embeddings
Research & Publications
- Master Thesis (Ongoing): Hyperbolic Compositionality in Vision-Language Models at University of Twente
- PROFES 2025: “Enhancing Software Maintainability through LLM-Assisted Code Refactoring” (Accepted)
Background
I started as a software engineer working in Android and web development, but my passion for AI led me to specialize in machine learning, NLP, and computer vision. I enjoy the challenge of taking research concepts and turning them into production systems that people can use.
Open to: Industry opportunities, research collaborations, and PhD positions in AI/ML.