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Mr. Semba Masumbuko

Assistant Lecturer
Semba is an assistant lecturer at the Nelson Mandela African Institution of Science and Technology (NM-AIST), in Arusha, Tanzania. Semba holds a Master degree in Marine Sciences from the University of Dar es salaam. He also holds a Bachelor degree in Fisheries and Aquaculture from the University of Dar es salaam.

Experience & Activities

Semba has developed interest ina data science with focus on developing tools and algorithms for automated spatial and non-spatial analysis in oceanography. Semba possess proficiency in various programming languages such as – MATLAB, Python, Observable JavaScript, and R. Leveraging my programming skills, I have developed a diverse range of tools, algorithms, and analytical workflows that streamline the organization, management, analysis, and modeling of data. By harnessing these languages, I am able to automate data processing and analysis tasks, as well as generate comprehensive reports in different formats such as LATEX, PDF and HTML.
Notably, the scripts and tools I create are intended for reproducibility of data analysis workflows, produce insights form data that bolster informed decision-making processes. Semba also take pride in open sharing of analytical codes that can be found at his platforms such as blog[https://semba.netlify.app/], website [https://lugoga.github.io/semba-quarto/] and github[https://github.com/lugoga/], allowing the public to freely access and utilize these resources.

Packages
A wior packaged built by Masumbuko Semba and Nyamisi Peter focusing on Easy Tidy and Process Oceanographic Data. The packages is basically developed to help marine and freshwater scientist access a large and varied format of in-situ and satellite data in easy way. In fact, the package has made data access in much easy way. The authors are trying to remove the barrier of data access and leave a space for scientists to focus in much deeper thinking of their field rather than spending several days to understand codes for a specific data download. The package contains several tools that allows scientist to get a wide array of datasets. And the funny things is that you get a tidy format result of the download, which is easy to handle in R and also to share it out of R environment. The tidy format is in form that many scientists familiar with Excel spreadsheet will find it handy. You can access this package through this link: https://github.com/lugoga/wior