- INFORMS 2022
Fred Otieno is a Research Engineer building a hybrid cloud platform to accelerate scientific discovery and solutions.
In the past worked on time series analysis. Developing machine learning pipelines enabling explainable climate forecast enhancing resiliency in supply chains and understanding borehole usage and repair patterns.
Over eight years’ engineering experience. Designing and building responsive and reusable UI/UX components as well as orchestrated backend subsystems. Open to learning and leveraging new technology to provide practical solutions.
Lead in implementing strong quality assurance processes and procedures at a startup FrontlineSMS, a two-way SMS platform used across the world. In the past few years, took on a role as a research engineer entailing innovative thinking, design, construction, testing and characterization to enable internal research efforts, evaluating emerging technologies for potential real-world product application and demonstrating the value of those technologies for IBM’s businesses and partners.
Holds an MS in Information Technology from Carnegie Mellon University.
- Program committee member for reviewing the NeurIPS 2020 workshop on Tackling Climate Change with Machine Learning
- Program committee member for reviewing the ICML 2021 workshop on Tackling Climate Change with Machine Learning
- Program committee member for reviewing the NeurIPS 2021 workshop on Tackling Climate Change with Machine Learning
- Program committee member for reviewing the NeurIPS 2022 workshop on Tackling Climate Change with Machine Learning
- INFORMS 2021
Multi-factor authentication for users of non-internet based applications of blockchain-based platforms
- Blockchain 2020
Machine Learning Approaches to Safeguarding Continuous Water Supply in the Arid and Semi-arid Lands of Northern Kenya
- ICLR 2020
- ICBC 2019
- 23 Jan 2023
- 31 Oct 2022