Name: Stefan Wild
Pronouns: he/him/his
Biography:
Wild is a Senior Scientist at Berkeley Lab and adjunct faculty member at Northwestern University. Wild’s primary research focuses on developing model-based algorithms and software for challenging numerical optimization problems and automated learning. He has worked across scientific areas to solve difficult science and engineering problems involving advanced computer simulations, complex data, and physical experiments.
Institution/Lab: Lawrence Berkeley National Laboratory
Website: https://wildsm.github.io/
SRP Collaboration Topic/Title: Learning while optimizing
Field or research area: Numerical optimization and learning
Please select all the topical areas that apply to your project:
Computational Science Applications (i.e., bioscience, cosmology, chemistry, environmental science, nanotechnology, climate, etc.); Data Science (i.e., data analytics, data management & storage systems, visualization); Machine Learning and AI
Brief Abstract:
Our research addresses mathematical optimization of challenging computational science problems. We will be exploring ways that we can use machine learning on the data generated internally by an optimization algorithm in order to improve its performance on a chosen application.
Desired relevant skills, background, or interests:
Desire to collaborate, basic algorithm knowledge and experience in a programming language.
Other comments:
Do any special requirements apply? International OK
Other, specify:
Keywords:
mathematical optimization;scientific computing;adaptive algorithms;reinforcement learning
Lightning Talk Title: Learning while optimizing