Mulang' Onando

Mulang' is a research scientist at IBM Research Africa. He is currently involved with the Accelerated Discovery team on work to generate innovative AI methods for accelered discovery in science, specifically in helth care through De-risking of clinical trials.  With his experience in Foundation Models, Mulang' is part of the IBM foundation models for clinical trials team. He has also been working on Subgroup Analysis techniques and Post Discovery Analysis - This involves applying techniques such as subset scanning and stratification to detect anomalous patterns of care in  health records as well as on the application of machine learning algorithms to study population-level behavious and response to interventions. Mulang' holds a Ph.D. in Computer Science degree from the University of Bonn, in Germany with concetration in bridging the gap between the Natural Language Processing (NLP) and the Semantic Web communities by designing approaches and tools for the disambiguation of entities and relations in text to Knowledge Graphs (KGs) with outputs directly applicable to conversational AI systems such as question answering and dialogue systems, chatbots as well as automated  KG construction, and population. He holds a Master of Software Engineering, and a Bachelors in Computer Technology degrees from Jomo kenyatta University of Agriculture and Technology (JKUAT).

Mulang' has also contributed to innovation through patenting, with currently 3 patents being filed at IBM. His work has recently been recognised with the Outstanding Technical Achievenment Award (OTAA), for his contribution to the Healthcare Delivery Pattern Discovery Toolkit.