Lecturer
Allan Omondi is a lecturer in the School of Computing and Engineering Sciences at Strathmore University, Kenya. He received his Bachelor of Business Information Technology in 2012, his Master of Science in Information Technology in 2015, and his Doctor of Philosophy in Information Technology in 2020, all from Strathmore University.
His current research interest is in the application of Artificial Intelligence and mathematical optimization techniques in data management. This is with a focus on self-driving databases that can perform query optimization of queries with join-crossing correlations, knob configuration (performance tuning), physical database design (indexing and partitioning), and hardware provisioning.
He extends the progress he makes in this discipline-specific research area to have a significant societal impact in development economics. This entails applying Artificial Intelligence and mathematical optimization to optimize the allocation of resources in communities and to formulate policies with the aim of promoting sustainable social welfare.
He is a member of the Information and Communication Technology for Development (ICT4D) research group (where he has been the research group leader since 6th May 2021) and the Database research group (where he is a faculty member) both at the Strathmore University’s School of Computing and Engineering Sciences.
The 2 main courses he loves teaching at both undergraduate and graduate levels are Advanced Database Systems and Business Intelligence. He has successfully supervised several master’s students with a success rate of 90% from 2022; where “success” implies shortlisted for the final defence after the proposal was accepted, defended their research, and passed their defence. He is also currently co-supervising 1 PhD student working on a thesis titled, “Deep Learning Model for Cardinality Estimation of Multi-Attribute Queries in a Cost-Based Query Optimizer”.
2016 to 2020: Doctor of Philosophy in Information Technology from Strathmore University. Thesis title: “A Monte Carlo Tree Search Algorithm for Optimization of Load Scalability in Database Systems”; supervised by Professor Ismail Ateya and Professor Gregory Wanyembi.
2013 to 2015: Master of Science in Information Technology (Systems Security and Audit Option) from Strathmore University. Thesis title: “Vision-Based Data Fruit Maturity-Level Prediction Model: A Case of Pawpaw in Makueni County”; supervised by Dr Joseph Orero.
2008 to 2012: Bachelor of Business Information Technology (Database Administration Option) from Strathmore University
His current research interest is in the application of Artificial Intelligence and mathematical optimization techniques in data management. This is with a focus on self-driving databases that can perform query optimization of queries with join-crossing correlations, knob configuration (performance tuning), physical database design (indexing and partitioning), and hardware provisioning.
He extends the progress he makes in this discipline-specific research area to have a significant societal impact in development economics. This entails applying Artificial Intelligence and mathematical optimization to optimize the allocation of resources in communities and to formulate policies with the aim of promoting sustainable social welfare.
2024 University of Michigan African Presidential Scholar
The 2 main courses he loves teaching at both undergraduate and graduate levels are Advanced Database Systems and Business Intelligence.
He has successfully supervised several master’s students with a success rate of 90% from 2022 and over 130 undergraduate projects with a success rate of 99% from 2015; where “success” implies shortlisted for the final defence after the proposal was accepted, defended their research, and passed their defence.
He is also currently co-supervising 1 PhD student working on a thesis titled, “Deep Learning Model for Cardinality Estimation of Multi-Attribute Queries in a Cost-Based Query Optimizer”.
Students (undergraduate, master’s, or PhD) who have a similar research interest and would like to work with him are welcome.
He is also open to academic or industrial research collaborations, whether in the same discipline or involving a multidisciplinary approach.