Marziyeh Arabhejad Khanouki: Computer Science

The department of electrical and computer engineering offers programs leading to the Master of Science degree in Engineering, Master of Engineering, and Ph.D. degree in computer engineering. Students study computer circuitry, parallel computing, software system design, information theory, digital image processing and much, much more. Marziyeh Arabhejad Khanouki is a computer science student in The University of Tulsa’s Graduate Program who has interest with

Research Interests

My main research interest is applying machine learning methods in human Genome-Wide Association Studies (GWAS). In the second semester of my master studies, I took “Bioinformatics” with Dr. Brett McKinney where I learned about developing computational tools to understand biological data. While regression models are being used in many GWA studies, they ignore the genomic and environmental interactions in finding genes associated with diseases or quantifying the heritability. Modern machine algorithms such as k-nearest neighbor (knn) and random forest have been shown to work well compared to classic regression models especially in the case of incomplete and noisy data. There are many sides to the modern approaches that need to be researched, e.g. the distance metric in the knn algorithm, before making them a generalized approach for GWA studies.

Where have you presented?

• “Comparison of Relief-F Nucleotide Differences For GWAS Data With Application to Bipolar Disorder”, presented at 14th Annual Rocky Mountain Bioinformatics Conference held in November 2016. In this work, I have implemented various distance metrics in the classification algorithm to identify the genes associated with Bipolar Disorder.
• The 20th Annual Student Research Colloquium, February 2017

Why did you choose TU for your graduate studies?

I was passionate about continuing my undergraduate study at the graduate level and I found TU a good place to attend advanced courses, learn from well-respected professors and graduate studies to be a key stepping-stone to my career in computational research in academia or industry. The environment at TU suits my research interests because of its advanced academic curriculum and world-class research groups. I believe that it is an ideal environment for me to achieve my goals while gaining experience and exposure to a diverse student body and faculty.

Your TU experience?

I started my graduate degree at The University of Tulsa in 2014, where I took graduate courses and conducted research in the field of bioinformatics. The In silico bioinformatics lab, directed by Dr. Brett McKinney in the Tandy School of Computer
Science is a well-known research center in bioinformatics and I had the opportunity to accomplish my research on the application of machine learning methods in human Genome-Wide Association Studies (GWAS) under his supervision.

What are your future career plans?

This past summer, I had the opportunity to collaborate with the Oklahoma Medical Research Foundation (OMRF) on the analysis of genome data. Moreover, there are many research institutes and universities around the world that are working
toward developing computational tools for biological studies. I hope that I can use the experience and knowledge that I have obtained during the course of my study at TU in my professional career in academia or research laboratories.

Educational Background

Ph.D. student, Computer Science (in the field of Bioinformatics), The University of Tulsa (expected 2019)
M.S., Computer Science, The University of Tulsa, 2016 B.Sc.,
Computer Science, Bahonar University of Kerman (Iran), 2011