Mission
We turn new AI research into reliable systems with real value.
About SiliconBlast
We turn new AI research into reliable systems.
We build with rigor, security and accountability for organizations where errors are costly.
Vision
We want to be the applied AI partner enterprises and governments trust to ship. We set the standard for AI work in the lab and in production.
How SiliconBlast fits together
One lab with its own home for research, for products and for client work.
research.siliconblast.comSiliconBlast ResearchWe advance the science of learning systems and put the results to work for people and the planet.
products.siliconblast.comSiliconBlast ProductsSeven apps for your knowledge, your money, your photos, your code, your mail, your messages and your memories.
www.siliconblast.comWork with SiliconBlastAI strategy and delivery for enterprises and governments.
Founder
Ekaba Bisong
Founder and Principal Consultant · Calgary, Canada
Ekaba Bisong founded SiliconBlast and leads its research, its products and its client work. He is a Ph.D. researcher in Computer Science at the University of Victoria and an NSERC Postgraduate Scholar. His thesis, On Adaptive Kelp Forest Monitoring, is supervised by Dr. Neil Ernst in collaboration with Dr. Maycira Costa’s remote-sensing lab.
His research covers reinforcement learning and learning automata, adaptive and self-organizing systems, climate informatics and satellite remote sensing, language models for low-resource languages and machine learning for health. Across more than a decade he has built AI and data systems for Fortune 500 enterprises, banks and public-sector organizations. Before SiliconBlast he was Principal AI Architect at Loblaw Companies Limited.
Honours
- NSERC Postgraduate Scholarship, Doctoral (PGS D)Natural Sciences and Engineering Research Council of Canada, 2025 to 2028
- President’s Research ScholarshipUniversity of Victoria, 2025 to 2026 and 2026 to 2027
- University of Victoria Fellowship, Doctoral2024 to 2025
- University of Victoria Graduate Entrance Award2024 to 2025
Education
- Ph.D. in Computer Science, University of VictoriaIn progress. Thesis: On Adaptive Kelp Forest Monitoring. Supervisor: Dr. Neil Ernst
- B.Sc. in Mathematics, Athabasca UniversityIn progress
- M.Sc. in Computer Science, Carleton UniversityThesis on adaptive data structures. Supervisor: Dr. B. John Oommen
- B.Sc. in Computer Science, Babcock UniversityArtificial intelligence and decision support systems
Career
- Founder and Principal Consultant, SiliconBlast2019 to now
- Principal AI Architect, Loblaw Companies Limited2020 to 2021
- Senior Consultant and Data Science Lead, T4G2019 to 2020
- Data Scientist and Data Engineer, Pythian2017 to 2019
Speaking
- Google ML SummitCambridge, Massachusetts
- Cisco DevNet CreateMountain View, California
- Google DevFestNew Orleans, Springfield and Thunder Bay
- TensorFlow Everywhere North AmericaPlus talks at GDG chapters, BITCON and IEEE
Selected work
- Building Machine Learning and Deep Learning Models on Google Cloud Platform Apress / Springer Nature, 2019
- BioMedBERT: A pre-trained biomedical language model for QA and IR COLING 2020
- Predicting high blood pressure using machine learning models in low- and middle-income countries BMC Medical Informatics and Decision Making, 2024
- On utilizing transitivity and pursuit-enhanced object partitioning to optimize self-organizing lists-on-lists Evolving Systems, 2021
- Optimizing self-organizing lists-on-lists using transitivity and pursuit-enhanced object partitioning IFIP AIAI 2020
- Built to last or built too fast? Evaluating prediction models for build times IEEE/ACM MSR 2017
What we stand for
- We ship working systemsWe measure our work by systems in production. Our proof is the software we run ourselves.
- We test every claimWe tell you when AI is the wrong tool. We back every claim with evaluation.
- Security and accountabilityYou get named, accountable delivery and security by design. Enterprise and government work demands both.
- We apply frontier researchWe track new research and turn the results into reliable, low-cost systems for the real world.