09:00 - 09:30: Doors open and welcome coffee
09:30 - 09:50: Opening - Dick den Hertog - UvA
09:30 - 12:00: Part 1: OPTIMAL Presentations
09:50 - 10:20: Embedding outcome models in treatment planning - Donato Maragno - UvA
10:20 - 10:50: Performance analysis of optimization methods for machine learning - Hadi Abbaszadehpeivasti - Tilburg University
10:50 - 11:20: Neur2RO: Neural two-stage robust optimization - Esther Julien - TU Delft
11:20 - 11:50: Learning-augmented algorithms with explicit predictors - Marek Eliáš - Bocconi University
12:00 - 13:00: Lunch break
13:00 - 15:00: Part 2: Company Presentations
13:00 - 13:40: Why response matters: Simultaneous Bi-Level Optimization for Network Design Problems - Maarten Schadd - TNO
13:40 - 14:20: Leveraging Deep Learning models to estimate travel time durations for the VRP problem - Ruggiero Seccia - Ortec
14:20 - 15:00: Machine learning for simulated annealing: ideas and results from practice - Frans de Ruiter - CQM
15:00 - 15:30: Break and refreshments
15:30 - 17:30: Part 3: Keynote Speakers
15:30 - 16:30: The R.O.A.D. to precision medicine - Dimitris Bertsimas - MIT
16:30 - 17:30: On the interplay between learning and optimization and its effect on MIP solving - Andrea Lodi - Cornell
The research project Optimization for and with Machine Learning (OPTIMAL) is an ENW-GROOT research project funded by NWO. It is a collaboration between researchers from Centrum Wiskunde & Informatica (CWI), Delft University of Technology (TU Delft) and the University of Amsterdam (UvA). It started in 2020 and will end in 2025. Research from this project will be shared in various events. For more information about this research project visit the project site OPTIMAL.uva.nl and the events calendar.