NewsMachine Learning Research at IEMS
News
The IEMS department hosts a recurring meeting in which faculty present their work related to machine learning.
Presentations
Brenna Argall and Michael Watson: April 25, 2024
Machine Learning in the Assistive/Rehab Field
![Brenna Argall](../images/events/2024/argall-brenna.jpg)
Brenna Argall
How Operations and Supply Chain Executives Learn About AI/Machine Learning
![Michael Watson](../images/events/2024/watson-michael.jpg)
Michael Watson
Andreas Waechter: June 9, 2022
DNNs In Engineering Applications
![Andreas Waechter](../images/people/waechter-andreas.jpg)
Andreas Waechter
Julia Gaudio: March 31, 2022
Generalization Error
![Julia Gaudio](../images/people/gaudio-julia-t.jpg)
Julia Gaudio
Barry Nelson: February 3, 2022
Simulation Optimization and Bandits
![Barry Nelson](../images/events/nelson-barry.jpg)
Barry Nelson
David Morton: August 21, 2020
2020 Distributionally Robust Two-Stage Stochastic Programming
2019 Distributionally Robust Stochastic Dual Dynamic Programming
![David Morton](../images/events/2020-2021/morton-david.jpg)
David Morton
Simge Kucukyavuz: July 24, 2020
Integer Programming for Learning Directed Acyclic Graphs from Continuous Data
Consistent Second-Order Conic Integer Programming for Learning Bayesian Network
On the Convexification of Constrained Quadratic Optimization Problems with Indicator Variables
Ideal Formulations for Constrained Convex Optimization Problems with Indicator Variables
A polyhedral approach to bisubmodular function minimization
![Simge Kucukyavuz](../images/events/2020-2021/simgekucukyavuz_2.jpg)
Simge Kucukyavuz
Noshir Contractor: June 12, 2020
Moon 2024: Translating Research to Practice
A Successful Crew Composition Countermeasure Validated in HER
![Noshir Contractor](../images/events/2020-2021/contractor-noshir.jpg)
Noshir Contractor
Barry Nelson: May 22, 2020
Barry Nelson
![Barry Nelson](../images/events/nelson-barry.jpg)
Barry Nelson
Ed Malthouse and Diego Klabjan: April 17, 2020
An Algorithm for Allocating Sponsored Recommendations and Content: Unifying Programmatic Advertising and Recommender Systems
Multistakeholder Recommendation with Provider Constraints
Multistakeholder Recommender Systems Algorithm for Allocating Sponsored Recommendations
Ed Malthouse
![Ed Malthouse](https://www.mccormick.northwestern.edu/images/research-and-faculty/directory/malthouse-edward.jpg)
Ed Malthouse
Diego Klabjan: 2022
LUCK, MACHINE LEARNING AND IEMS: You do need all three of them
Diego Klabjan
![Diego Klabjan](https://www.mccormick.northwestern.edu/images/research-and-faculty/directory/klabjan-diego.jpg)
Diego Klabjan
Zhaoran Wang and Jorge Nocedal: February 19, 2020
Zhaoran Wang
Jorge Nocedal
![Zhaoran Wang](https://www.mccormick.northwestern.edu/images/research-and-faculty/directory/wang-zhaoran.jpg)
Zhaoran Wang
![Jorge Nocedal](https://www.mccormick.northwestern.edu/images/research-and-faculty/directory/nocedal-jorge.jpg)
Jorge Nocedal