We contribute to the field, not only consume it
SiliconBlast is led by a published researcher. Our work spans learning systems, climate informatics, machine learning, language models, and applied AI engineering. The same rigor goes into every system we ship.
Where our research focuses
Research perspectives, several backed by peer-reviewed publications, each connected to the systems we build.
Learning systems
Reinforcement learning and adaptive, self-organizing systems. Pursuit and transitivity-based object partitioning, published across Evolving Systems, AIAI, and ICIC.
Climate informatics
Machine learning for climate and the environment. Land-cover segmentation from satellite imagery, and greenhouse-gas inventories for land use, forestry, and waste.
Machine learning for health in emerging markets
Predictive models for hypertension in low- and middle-income countries. Published in BMC Medical Informatics and Decision Making.
Biomedical NLP and language models
BioMedBERT, a pre-trained biomedical language model for question answering and information retrieval. Published at COLING.
Applied AI engineering on the cloud
Practical machine learning and deep learning systems on Google Cloud, captured in a full Apress textbook.
Applied ML and software analytics
Prediction models for software build times. Published at the IEEE/ACM Mining Software Repositories conference.
Published textbooks
Programming in Java: A Quick Starter Guide
University of Calabar Press, 2016. ISBN 978-007-277-2.
Peer-reviewed publications
A selection of journal and conference papers. The complete, current list lives on Google Scholar.
Journal articles
Predicting high blood pressure using machine learning models in low- and middle-income countries
Bisong, E., Jibril, N., Premnath, P., Buligwa, E., Oboh, G., Chukwuma, A.
BMC Medical Informatics and Decision Making, 24(1), 234
On Utilizing Transitivity and Pursuit-Enhanced Object Partitioning to Optimize Self-Organizing Lists-on-Lists
Bisong, O. E., Oommen, B. J.
Evolving Systems, 12, 655-686
On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists
Bisong, O. E., Oommen, B. J.
Evolving Systems, 1-32
Conference papers
BioMedBERT: A Pre-trained Biomedical Language Model for QA and IR
Chakraborty, S., Bisong, E., Bhatt, S., Wagner, T., Elliott, R., Mosconi, F.
Proceedings of COLING 2020, 669-679
Optimizing Self-organizing Lists-on-Lists Using Transitivity and Pursuit-Enhanced Object Partitioning
Bisong, O. E., Oommen, B. J.
IFIP AIAI 2020, 227-240, Springer
Optimizing self-organizing lists-on-lists using pursuit-oriented enhanced object partitioning
Bisong, O. E., Oommen, B. J.
ICIC 2019, 201-212, Springer
Optimizing self-organizing lists-on-lists using enhanced object partitioning
Bisong, O. E., Oommen, B. J.
IFIP AIAI 2019, 451-463, Springer
Built to last or built too fast? Evaluating prediction models for build times
Bisong, E., Tran, E., Baysal, O.
IEEE/ACM MSR 2017, 487-490