Ohh you found me?. Howdy! I am
Jeff
Owino.
. . .
Expert Data Scientist
PhD Artificial Intelligence, PhD Statistics, MSc Applied Statistics-machine learning major, BSc Applied Statistics, Dip. Strategic Management. Honors of KAPS hackathon(Computer Aided Drug design),Honors Nairobi Pearl hackerthone, Honors of Audio Analytics, Hons. Japanese Fake news analytics. Hons UN AI in climatic eco-innovations.
Get in touch!What Defines Me.
I am a highly skilled professional in innovation, data science, software development, and biostatistics, with extensive experience across various disciplines. While I primarily work with R, I also utilize Python, MySQL, Snowflake, and big data platforms like Spark and Hadoop.
I hold over 42 professional certificates and have received more than nine awards for my innovative projects. My expertise spans predictive analytics, machine learning, deep learning, natural language processing, and spatial analytics.
I have a strong background in managing teams of data analysts and BI professionals and have successfully led projects such as autonomous crop disease surveillance, audio analytics, and drone surveillance for wildlife. As a lecturer in data science, I am well-published in standard media and journals, showcasing my profound knowledge and experience in the field. I excel in developing analytical pipelines and uncovering opportunities through predictive analysis, combining various tools and methodologies for impactful results.
Here are few technologies that are cup of my tea coffee .
- Python
- R Language
- MySQL
- Apache Spark
- Django
- Java
- JavaScript
- Jenkins
Places i’ve worked.
Since 2019, had a privilege to work with several companies that enables me to hone my skills and talents. These companies will always have a special place in my heart. Currently I am working with United Nations.
Some of my works.
Check out some of my Scholarly Projects and Publications
Autonomous Surveillance of Infants’ cries using Deep Learning Audio analytics model
Autonomous Surveillance of Crops disease using AI machine learning Technique
Computer Aided drug design for ebola vp35,sold to SanFransican Pharmaceuticals
Prediction of post-harvest losses along tomato supply chain in kibwezi west sub-county, web based real-time application
Achievements/Honors
Google PhD Fellowship winner
Third position at KAPS 2019 Hackathon in liaison with JKUAT and other Companies (machine learning to come up with computer aided drug design-Ebola candidate drug) published in Standard media magazine dated 18th Nov 2019
World best researcher Google Washington fellowship 2023, published in google website
Automated the real time logistics Duka and warehouse forecasting inventory at One Acre Fund.
Winner of MKU Youth Innovation Fund from developing Artificial parenting comprehensive tool that uses Deep Learning Predictive models which is capable to discriminate the infant audio cries class like change of pumpers, belly pain, sick, tired, hungry and more.
UN award winner for having developed computer vision for early NTD eye cataract detection using deep learning models