Hello! As a brief introduction, I am a lecturer at the Statistics and Computing Unit of School of Mathematics, University of Nairobi. My broad interests are in the application of Statistics and Mathematics to solutions of problems in nature.

I believe that mathematical and statistical techniques are "most useful" when implemented through computation and simulation. Otherwise, the beauty of the techniques described in the subjects can only be appreciated by the seasoned mathematician or statistician rather than the general public!. This site seeks therefore to demystify the use of mathematics in understanding real datasets in practice through the works of my students and computation group, the DASCLAB i.e., data analytics and scientific computing laboratory.

I am thankful to my students because through their work, which will be highlighted here, we illuminate the solutions to various problems in industry, with special interest to their significance in Kenya and Africa. The general nature of real-life problems is that they are multidiciplinary and mutifaceted.

The goal of DASCLAB are motivated by my interest, experience and passion in critical inquiry, understanding and modeling of general systems toward problem-solving. In particular, we seek to:

- Encourage and effect multi-disciplinary approach to problem solving through collaborative research
- Solve old problems and new problems in a new way through computation, simulation and visualizations
- Integrate and analyse high-throughput data with respect to time through:
**Dashboards**: historical evaluation of cause and effects i.e., what happened and why**Real-time analytics and data mining**: (near-)real-time analytics of cause and effects i.e., what/why/when is it happening?**Predictive/prescriptive analytics**: futuristic evaluation of which event is going to happen (what/why/where/when) and simulations on why we should care?

- Effective communication and transfer of knowledge through practical tasks, projects and real-data wrangling, munging and analysis.
- Innovate and undertake cutting-edge research toward discoveries in microRNA and their influence to cancer research and other less-understood diseases such as autism and Alzheimer's

I have broad experience in computation, experimental design and data analysis of large-scale structured and unstructured (text, audio and audio-visual image/video streams) as well as high-throughput, specialty-related, genomic and/or proteomic studies involving say microarray (ChIP-chip, ChIP-seq, comparative genomic hybridization - CGH, protein) and mass spectra data. I am well versed with programming in C, R, MATLAB, Python, Perl and other open-source software for exploratory analysis, visualization and reporting.

I enjoy working in computational sciences and data analysis because its unifies my quantitative abilities, education, training and past experiences in statistics, mathematics, accounting and in general problem-solving.