Tag: optimization

Optimization is an act, process, or methodology of making something as fully perfect or effective as possible. Almost everything can be improved, so optimization’s relevance spans to almost every business or process to make it operate more efficiently and effectively. Optimization employs mathematical models to discover more efficient ways to control and manage systems, ranging from radiation treatments to data centers and power networks. Optimization researchers at WID solve systems-level problems in emerging science and engineering applications by using optimization technologies in an integrated, interdisciplinary, and collaborative fashion. This includes finding solutions to problems that are the most cost-effective or achieve the highest performance under given constraints by maximizing desired elements and minimizing the undesired elements. Optimization models promise better process planning that can be tied to and offered by social, economic, and financial systems. Certain social and political constraints have caused optimization to go largely unexplored, as have methods for translating plans into policy. We hope to draw on collaborations with communications experts, political scientists, sociologists, economists, behavioral scientists, and business professionals to further leverage optimization’s potential for boosting efficiencies and improving systems that reach into all corners of our lives. Learn more about Optimization at WID. It is a key component of WID's Data Science Hub.

2022 Publications

2022 publications from our faculty and fellows during their time at WID are listed below. Please see each publication for additional information. View Additional Publications:

WID Seminar Series

Resilience, Robustness and Adaptability. OPTIMIZATION, EQUILIBRIUM, POWER AND CHRISTMAS COOKIES! Join us to hear the Ferris Lab tie it all together in a festive bow! Praful Gagrani from the Baum Lab will introduce this fascinating medley. December 19th at 2pm in the Orchard View Room, Discovery Building. Wisconsin Institute for …

Vanessa Sawkmie

Vanessa Sawkmie headshot

  • Graduate Student

I'm interested in Mixed Integer Programming. I work on discrete and stochastic optimization models for scheduling and search applications.

Alex Lowy

  • Postdoctoral Associate

Privacy-preserving machine learning and optimization

Daniel Ajuzie

  • Graduate Student

Computational modeling of bacterial iron homeostasis and oxidative stress response

Jeongyeol Kwon

Jeongyeol Kwon headshot

  • Postdoctoral Associate

Inference and decision-making with missing or unobserved information.

Woojin Kim

Woojin Kim headshot

  • Graduate Student

Integer optimization problems and stochastic optimization problems on various networks

2021 Publications

2021 publications from our faculty and fellows during their time at WID are listed below. Please see each publication for additional information. View Additional Publications:

Josh Arnold

Campus Energy Coordinator, UW-Madison Office of Sustainability

  • WID Affiliate

Develop policy discussions to inform scenarios for moving Wisconsin to a clean energy future

Jinsu Gim

Jinsu Gim headshot

  • Postdoctoral Associate

Injection molding, Polymer processing, Process monitoring and optimization

Ahmet Alacaoglu

Ahmet Alacaoglu

  • Postdoctoral Associate

Continuous optimization for machine learning, reinforcement learning and other data science problems

Cheng-Wei Lu

Cheng-Wei Lu headshot

  • Graduate Student

Optimization applications on real-world problems.