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Ali Heydari

Ali Heydari
Office: 
ACS 358C
Research Interests: 

Deep Learning, Bioinformatics, Computer Vision

Bio: 
Ali Heydari is an Applied Mathematics Ph.D. student and a graduate research assistant at UC Merced. My research lies at the intersection of deep learning, computer vision, and bioinformatics, but I am also very interested in natural language processing and machine learning in general. The goal of my research is to develop computational methods for better downstream analysis of treatments (and personalized treatments). To achieve this, we have used a deep generative model to generate realistic synthetic single-cell data. Creating realistic in-silico data will help scientists with more robust analysis and more reproducible research. The next aspect of my research focuses on developing large-scale deep learning models for predicting the absorption, distribution, metabolism, excretion, and toxicity (ADME-Tox) of drugs in patients. We plan to help researchers predict the ADME-Tox of treatments by developing a large-scale pre-trained deep learning model that can be fine-tuned with a limited amount of data to meet the needs of specific tasks.