Aryan Golzaryan

I am a PhD student at Eawag and ETH Zurich, working on developing automated text mining approaches to extract pharmacodynamic parameters from scientific literature. My research focuses on leveraging natural language processing (NLP), Machine Learning (ML), and Deep Learning (DL) techniques, to streamline the extraction of drug resistance data and ensure continuous updates for pharmacodynamic databases. In addition to mining scientific texts, I will extract relevant data from existing structured datasets to enhance information retrieval and knowledge discovery in biomedical research using DL/ML methods. 

Before starting my PhD, I worked on computational modeling and simulation of biological systems using multi-scale mathematical modeling. During my master's thesis, I developed a physiologically based pharmacokinetic (PBPK) model to simulate drug distribution in the human body. By modeling the tumor microenvironment through the angiogenesis process, I coupled the PBPK model with convection-diffusion-reaction equations to simulate drug distribution in tumors. Additionally, I have experience implementing ML/DL algorithms for image processing tasks, including image-to-image translation in medical imaging, feature extraction, and data analysis.