Mr. Khalid Mater H M Kunji

Research interests include bioinformatics, genome-wide association studies (GWAS), protein property (e.g. solubility) prediction, and machine learning. 

Research Associate
Qatar Computing Research Institute
Date: 2015 – 2018
Location: Doha, Qatar

Member of Mani Murali’s Research Group
University of Michigan-Flint
Date: 2013 – 2014
Location: Flint, MI, USA
• Event Stream processing using a single deterministic finite state
machine (FSM) with buffers to make it possible to run queries
to identify what events contributed to satisfying the search pat-
terns. Using the single deterministic FSM instead of many non-
deterministic FSMs and joining the results allows for better per-
formance even with the overhead for the buffers.

Systems Administrator
Red Cedar Solutions Group
Date: Summer 2011
Location: Okemos, MI, USA
• Internship doing system administration for Linux and a few Windows servers along with other IT tasks.

Undergraduate Researcher in Michal Zochowski’s Lab
University of Michigan
Date: 2008 – 2010
Location: Ann Arbor, MI, USA
• Ran simulations of systems of Neurons using Matlab. This in-
volved numerical solving of systems of over a thousand differen-
tial equations via the Runge-Kutta method.

Undergraduate Researcher in Gus Rosania’s Lab
University of Michigan
Date: 2007
Location: Ann Arbor, MI, USA
• Worked calculating and inputting chemistry data for testing a
machine vision program to read molecular structures from image
files.

Khalid Mater H. M. Kunji is a software engineer and researcher whose work sits at the intersection of computer science, bioinformatics, and machine learning. His research focuses on developing computational methods for understanding complex biological systems, with particular interests in bioinformatics, genome-wide association studies (GWAS), protein property prediction—including protein solubility—and the application of machine learning techniques to biological data.

Since 2015, Khalid has been a member of the Qatar Computing Research Institute, where he contributes to advanced research and software development projects. His work combines strong foundations in computational science with practical expertise in large-scale data analysis and predictive modeling.