I am an independent consultant, focused on architecture, performance tuning, advisory services, and proofs of concept around data intensive applications. I am available for hire, doing business under the name "Data-ken Research" for short term and ongoing engagements.
Some current and recent projects include:
- Design and prototyping of data engineering infrastructure as a part of a project to commercialize a new deep learning technology.
- Performance tuning of a streaming analytics benchmark involving Apache Spark, Apache Kafka, Redis, and Kubernetes.
- General advisory services regarding analytics and machine learning applications. This includes participating in discussions with the client's prospective customers.
- Work with an academic research institute on machine learning based prediction of events, leveraging natural language event metadata and interrelationships.
- As an Innovation Commercialization consultant at an industrial research laboratory, I evaluated market opportunities for a Healthcare IoT technology portfolio. As a part of this effort, I also updated the technology stack, added cloud integration, and designed a patent-pending peak detection algorithm for ECG/PPG data.
- Initial prototyping and architecture for an IoT middleware project at an academic research institute. This resulted in the ThingFlow framework for event-driven IoT (https://thingflow.io). I also created a class on IoT hardware and software (http://micropython-iot-hackathon.readthedocs.io/en/latest/) and led sessions of the class at the PyBay conference and SFPython.
You can reach me via my email address jeff @ THIS_WEBSITES_DOMAIN_NAME or through one of the social media links in the sidebar.