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Amos O Olagunju
The University of Kansas
Overland Park, Kansas
 

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.


     

Parallel-and-stream accelerator for computationally fast supervised learning
Hector E., Luo L., Song P. Computational Statistics & Data Analysis 177(1): 1-12, 2022.  Type: Article

Large enterprises with massive amounts of data require reliable and efficient algorithms for exploring and forecasting trends in available supplies, user purchases, and advertisements. The scalability of the MapReduce approach is advantageous for ...

 

A survey of inverse reinforcement learning
Adams S., Cody T., Beling P. Artificial Intelligence Review 55(6): 4307-4346, 2022.  Type: Article

The process of discovering and incorporating knowledge from educators into machine learning (ML) poses major challenges. Beyond coding the known or derived characteristics of systems into ML algorithms, how should innovative researchers discover, ...

 

 What every engineer and computer scientist should know: the biggest contributor to happiness
Picard R. Communications of the ACM 64(12): 40-42, 2021.  Type: Article

Obviously, people in this world go through periods of happiness and unhappiness. But do computer engineers and scientists really understand the factors that account for true happiness in daily life? Perhaps there are useful features fo...

 

Trustworthy AI
Wing J. Communications of the ACM 10(64): 64-71, 2021.  Type: Article

Artificial intelligence (AI) techniques are useful in creating effective computing tools for diverse applications in areas such as transportation, agriculture, medicine, and justice systems. Yet the credibility of AI is still an interesting subjec...

 

RxNet: Rx-refill graph neural network for overprescribing detection
Zhang J., Kuo A., Zhao J., Wen Q., Winstanley E., Zhang C., Ye Y.  CIKM 2021 Queensland, Australia, Nov 1-5, 2021) 2537-2546, 2021.  Type: Proceedings

The intensifying rates of opioid overuse and drug misuse require effective drug prescription scrutinizing tools. Despite the available prescription drug monitoring programs (PDMPs) in countries like the US, how should indispensable PDMPs be devise...

 
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