Building systems that learn, scale, and behave (mostly).

I’m Howard Hottinger, a Computer Science PhD student working at the intersection of machine learning, weather, and real-world systems.

session.log
$ profile --statusname: Howard Hottingerrole: PhD Student, Computer Sciencefocus: Machine Learning, Weather, AI Systemsstatus: building, testing, learning$ tail -n 5 current.log09:15 preparing the next experiment09:17 checking the data pipeline09:19 evaluating model behavior09:22 writing up results09:24 iterating
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AI-assisted forecasting

Investigating how machine learning can support weather prediction while keeping uncertainty, evaluation, and operational usefulness in view.

  • Weather prediction
  • Uncertainty-aware evaluation
  • Human-centered forecasting

Machine learning systems

Building reliable training and evaluation workflows for data-intensive scientific problems.

  • Reproducible experiments
  • Scalable data workflows
  • Model diagnostics

Research tooling

Turning repetitive research tasks into practical tools that make complex work easier to run, inspect, and trust.

  • Data pipelines
  • Experiment tracking
  • Workflow automation
All writing
Research notes are coming soon. The writing system is ready; published Markdown notes will appear here automatically.

Research should be rigorous—and useful in the real world.

I enjoy building things that turn complicated ideas, messy data, and long-running experiments into systems people can understand and use.

More about me
session.log
$ whoamirole: researcher & builderbased_in: Virginia + North Dakotacoffee: yescurrently: iterating
Have an idea, question, or opportunity to collaborate?I’d love to hear from you.
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