Vaha Akbary Moghaddam

Program: Computational and Systems Biology

Current advisor: Michael A. Province, PhD

Undergraduate university: University of Guilan, 2022

Enrollment year: 2022

Research summary
Statistical Machine Learning, Applied Data Science, Applied Statistics, Statistical Genetics, Human Evolution

My research is mostly centered around developing AI-based methods (namely DL algorithms) for “Omics” and big-data studies. My main focus is on the mathematical & statistical basis behind the ML algorithms for the adjustment and implementation of algorithms to different fields and problems:

Statistical & Population genetics: Development of deep learning classification approaches for improving significance tests and polygenic risk scores for cohort studies (Project: The genetic basis of losing insulin sensitivity through aging -> Ongoing)

Omics: Using deep neural networks for combination methods of Omics levels to understand the functional impacts of genetic variations on cellular pathways, gene regulatory networks, and treatment procedures. (Project: A sequence to function deep learning framework for identification of miRNA regulatory networks based on the RNA-seq data -> ongoing)

Biosystem engineering: Development of signal processing approaches for the optimization of biosystem. Creating “Artificial Sensors” for remote monitoring of environmental and biological systems (Development of multiple convolutional neural networks for data prediction of faulty greenhouse sensors of a novel IoT-platform -> Under review)

(My mind is full of weird ideas and I would always love to learn more about different fields and sciences. AND I LOVE ANIME)

Graduate publications