Background:
I am a Research Associate at the SciBiome Institute, where my research focuses on the application of computational methods, including artificial intelligence (AI) and machine learning, to biomedical data for advancing personalized and predictive medicine. A central focus of my work is the P4D project, which aims to improve early detection, diagnosis, and treatment of depression through individualized medical approaches. As part of my research, I am exploring the use of large language models (LLMs) and retrieval-augmented generation (RAG) to enable intelligent text recognition and support the automation of systematic reviews. I also work on the analysis and integration of multi-omics data to reveal molecular disease mechanisms, and apply Next-Generation Sequencing (NGS) technologies for high-throughput biomedical data. Ultimately, my goal is to bridge advanced computational methods with real-world biomedical challenges to support more precise and effective healthcare solutions.

Interests:

• Large Language Models (LLMs) and Agentic AI in Biomedical Research
• Image Analysis
• Multi-Omics Data Integration
• Microbiome Analysis
• Immunology
• Computational Network Analysis
• Immunogenicity Prediction for Cancer Precision
• Cancer Subtyping using Computational Methods

Projects:

• P4D

Contact:

• Room: 118
• E-mail: roya.shiasi-sardoabi[a.t_))tu-braunschweig.de