The 2025 ICS Prize Committee recommended the recognition of two submissions as co-winners of the ICS Prize: (1) Alper Atamtürk, Andrés Gómez, and Shaoning Han (2) Jason Altschuler and Pablo Parrilo

The 2025 ICS Student Paper Award winner is Hao Hao (CMU) for the paper "Robust Paths: Geometry and Computation," co-authored with Peter Zhang.

The 2025 ICS Harvey J Greenberg Research Award was presented to Braden L. Crimmins, J. Alex Halderman, and Bradley Sturt for their paper "Improving the Security of United States Elections with Robust Optimization."

The latest ICS Newsletter, highlighting the 2024 ICS Awards, is out. higherlogicdownload.s3.amazonaws.com/INFORMS/a4f8...

The latest ICS Newsletter, highlighting the 2023 ICS Awards, is out. higherlogicdownload.s3.amazonaws.com/INFORMS/a4f8...

Wrapping up three great days of talks and casual discussions in Toronto, the INFORMS Computing Society Conference was listed as an official event of the 2025 International Year of Quantum Science and Technology (IYQ). Thank you David Esteban Bernal Neira for making that official! 😎

Houra Mahmoudzadeh talks at the INFORMS Computing Society Conference about joint work with Kimia Ghobadi on using inverse optimization for learning the feasible region from past decisions for application on planning radiation therapy treatments. 🧵1/2

Alinson Santos Xavier talks at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social about using artificial intelligence to improve the performance of optimization algorithms in solving problems in power systems. 🧵1/N

Can we use transformers for inverse optimization? Yes we can! Macarena Navarro shows at the @icsinforms.bsky.social Conference how to use generative models for learning from good feasible solutions under formulation uncertainty while enforcing known hard constraints. 🧵1/N

Willem-Jan van Hoeve talks at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social about a general-purpose decision diagram-based discrete optimization solver, motivated by dynamic programming not being regarded more as an algorithmic than as a modeling device. 🧵1/N

Sanjeeb Dash gave a very interesting keynote talk at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social on the use of polynomial optimization for automatic knowledge discovery through symbolic regression. 🧵1/N

Lagrangian cuts seem to be a stronger alternative to Benders cuts in stochastic mixed-integer linear programming, but can we make them even stronger? That quest is what Weijun Xie told us at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social. 🧵1/N

John Hooker talks at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social about using nonserial decision diagrams to solve discrete optimization problems, inspired by the similar (but not identical) concept of nonserial dynamic programming models. 🧵1/N

Sebastian Perez-Salazar talks at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social about scheduling jobs in a single server with unknown duration and unknown abandonment times. 🧵1/2

Andre Augusto Cire walks a fine line to get the benefits from expected feasible and exact feasible relaxations by proposing a structure aware Lagrangian relaxation at the INFORMS Computing Society @informs.bsky.social @icsinforms.bsky.social Conference.

Dick Forrester presents joint work with Lucas Waddell at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social on using machine learning to predict good solutions for the multidimensional quadratic knapsack problem as a first step for local search heuristics. 🧵1/2

Justin Dumouchelle presented a neat outline of own work on approximating value functions with neural networks and solving stochastic, bilevel & robust optimization problems as a constraint learning problem in 3 published papers. Great @informs.bsky.social @icsinforms.bsky.social Conference talk!

Changhyun Kwon gave a very interesting talk at the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social about using deep learning for producing genetic algorithm operators based on characteristics of the optimization problem.

In the first plenary of the INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social, Simge Küçükavuz talked about mixed-integer convex formulations and algorithms for causal discovery and hidden Markov models. 🧵1/N

Simge reminded us at the @icsinforms.bsky.social Conference today too! 🥧

We are kicking off the awesomest ever INFORMS Computing Society Conference @informs.bsky.social @icsinforms.bsky.social in Toronto. Thank you Andre Augusto Cire, Sheng Liu and Maryam Daryalal for taking the lead in making this possible!

Anthony Karahalios is talking at the @icsinforms.bsky.social Conference about a new primal heuristic for branch-and-price optimization models. This work is motivated by most primal heuristics for this setting depending on concluding the processing of the root node, which may take too long. 🧵1/2

How big should a neural network be to learn the solution for a partial differential equation? Sébastien André-sloan shows through experiments and theory at the INFORMS Computing Society @icsinforms.bsky.social Conference that it may not need to be that big for the Hamilton-Jacobi-Bellman PDE. 🧵1/3

The latest ICS Newsletter, highlighting the 2022 ICS Awards, is out. higherlogicdownload.s3.amazonaws.com/INFORMS/a4f8...

The ICS Newsletter, highlighting the 2021 ICS Awards, is out. higherlogicdownload.s3.amazonaws.com/INFORMS/a4f8...