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Amos O Olagunju
St Cloud State University
St Cloud, Minnesota
 

Amos Olagunju is a professor in the Department of Computer Science and Information Technology at St. Cloud State University (SCSU) in Minnesota. He previously served as the interim dean of undergraduate studies for two years at SCSU. Prior to that position, he served as the dean of the School of Graduate Studies and chief research officer at Winston Salem State University in North Carolina. Amos served as the chair of the Mathematics and Computer Science Department, and later the Computing and Information Sciences Department, at Delaware State University (Dover, DE). Before that, he taught in the Asian Division at the University of Maryland University College, North Carolina A&T State University, and Michigan State University.

A faculty fellow and later a senior faculty fellow selected jointly by the American Society of Engineering Education and the Navy, Amos developed manpower mobilization and data-mining algorithms for monitoring the retention behaviors of personnel. As a member of the technical staff at Bell Communications Research (now Telcordia), he developed an architecture for a generalized C transaction environment, quantitative models for system workload projection and characterization, software metrics, and managerial decision support systems.

Amos developed statistical methods for the determination of content validity to obtain his doctorate in educational research and evaluation from the University of North Carolina at Greensboro. He investigated a distributed model as a basis for keyword detection to earn his master’s in computer and information sciences from Queen’s University (Canada). He received a bachelor’s degree in mathematics and computer science from Ahmadu Bello University in Nigeria. Amos was designated as an ACM senior member in 2007. His current research interests are in the areas of bioinformatics, quantitative security risk assessments, numerical computing, and artistic storytelling of breakthrough computing algorithms and technologies. He has been a reviewer for Computing Reviews since 2005, and has written over 100 reviews.


     

Finding a healthier approach to managing medical data
Greengard S.  Communications of the ACM 61(5): 31-33, 2018. Type: Article

Healthcare providers are confronted with formidable obstacles when it comes to providing effective medical care, even without taking into account the existing privacy laws that protect patients. Is the use of patient data when exploring new medica...

 

Is the law ready for driverless cars?
Calo R.  Communications of the ACM 61(5): 34-36, 2018. Type: Article

Current and future technologies will likely continue to be beset with clumsy legal laws. Should driverless vehicles and devices be responsible for violations such as a crash? Depending on the situation, Calo, in this rare viewpoint, echoes the dif...

 

Never-ending learning
Mitchell T., Cohen W., Hruschka E., Talukdar P., Yang B., Betteridge J., Carlson A., Dalvi B., Gardner M., Kisiel B., Krishnamurthy J., Lao N., Mazaitis K., Mohamed T., Nakashole N., Platanios E., Ritter A., Samadi M., Settles B., Wang R., Wijaya D., Gupta A., Chen X., Saparov A., Greaves M., Welling J.  Communications of the ACM 61(5): 103-115, 2018. Type: Article

Human beings are continuously learning via exposure to a variety of experiences and situations. Can current computers with limited knowledge bases (KBs) and learning models ever mimic real human intelligence? Mitchell et al. compellingly critique ...

 

A new nonparametric screening method for ultrahigh-dimensional survival data
Liu Y., Zhang J., Zhao X.  Computational Statistics & Data Analysis 119(C): 74-85, 2018. Type: Article

Groundbreaking effective algorithms for overcoming the discrepancies in the existing screening procedures for ultrahigh-dimensional medical survival data are long overdue. Liu et al. offer a nonparametric Kolmogorov-Smirnov (K-S) test statistic fo...

 

Analysis of the relation between computational thinking skills and various variables with the structural equation model
Durak H., Saritepeci M.  Computers & Education 116 191-202, 2018. Type: Article

The task of detecting the attributes of computational thinking skills in students remains a major challenge for educational researchers. What are the most reliable global predictors of the computational thinking abilities among primary, high schoo...

 
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