Fidan Hasanova
I am a Responsible AI Engineer with a Master’s degree in Computer Science from the University of Saarland.
About
I am a Responsible AI Engineer with a Master’s degree in Computer Science from the University of Saarland. I have hands-on experience building language models and computer vision systems, and I’m passionate about creating safe, scalable AI solutions for real-world problems.
I have developed Retrieval-Augmented Generation (RAG) chatbots and semantic search systems for automotive and enterprise use, improved multimodal retrieval with CLIP and BLIP approaches, and built tools for adversarial robustness testing of RAG chatbots. I’m proficient in Python and SQL, comfortable with Azure and cloud workflows, and I communicate fluently in English, native Russian and Azerbaijani, while continuing to study German at the B1 level.
- 3 years' experience
- Joined October 2025
Industry experience
- Software & Internet
- Professional Services
- Manufacturing
- Education
- Financial Services
Work experience
Designed and implemented Retrieval-Augmented Generation (RAG) chatbots to enhance QA capabilities, improving answer accuracy from 65% to 90% and reducing retrieval latency from 1.2s to 0.8s. Worked on a semantic search project, improving information retrieval accuracy from 70% to 88% and doubling performance. Implemented an Azure Assistant to streamline user interactions and automate processes, supporting sustainability initiatives across departments.
Built and deployed AI-driven reconciliation pipelines for fraud detection in financial ledgers, improving detection accuracy from 72% to 89%. Implemented anomaly detection models on high-volume account receivable data, reducing false positives in fraud alerts by 30% and cutting manual review time by 40%. Designed hybrid matching algorithms (embeddings, clustering, and heuristics), raising reconciliation coverage from 68% to 92% across multiple client datasets.
Contributed to the development of motion capture systems capable of tracking humans, props, and animals using commodity video cameras without markers or suits.
Education
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