The Offshore Resources Scheduling Problem: Detailing a Constraint Programming Approach. - Thiago Serra; Gilberto Nishioka; Fernando J. M. Marcellino (CP, 2012)

The Integrated Last-Mile Transportation Problem (ILMTP). - Arvind U. Raghunathan; David Bergman; John N. Hooker; Thiago Serra; Shingo Kobori (ICAPS, 2018)

Bounding and Counting Linear Regions of Deep Neural Networks. - Thiago Serra; Christian Tjandraatmadja; Srikumar Ramalingam (ICML, 2018)

How Could Polyhedral Theory Harness Deep Learning? - Thiago Serra; Christian Tjandraatmadja; Srikumar Ramalingam (CoRR, 2018)

Last-Mile Scheduling Under Uncertainty. - Thiago Serra; Arvind U. Raghunathan; David Bergman; John N. Hooker; Shingo Kobori (CPAIOR, 2019)

Equivalent and Approximate Transformations of Deep Neural Networks. - Abhinav Kumar 004; Thiago Serra; Srikumar Ramalingam (CoRR, 2019)

Empirical Bounds on Linear Regions of Deep Rectifier Networks. - Thiago Serra; Srikumar Ramalingam (AAAI, 2020)

Enumerative Branching with Less Repetition. - Thiago Serra (CPAIOR, 2020)

Lossless Compression of Deep Neural Networks. - Thiago Serra; Abhinav Kumar 004; Srikumar Ramalingam (CPAIOR, 2020)

Reformulating the disjunctive cut generating linear program. - Thiago Serra (Ann. Oper. Res., 2020)

When Lift-and-Project Cuts Are Different. - Egon Balas; Thiago Serra (INFORMS J. Comput., 2020)

Compact representation of near-optimal integer programming solutions. - Thiago Serra; John N. Hooker (Math. Program., 2020)

MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions. - Thiago Serra; Ryan J. O'Neil (Oper. Res. Forum, 2020)

Scaling Up Exact Neural Network Compression by ReLU Stability. - Thiago Serra; Xin Yu 003; Abhinav Kumar 004; Srikumar Ramalingam (NeurIPS, 2021)

Training Thinner and Deeper Neural Networks: Jumpstart Regularization. - Carles Roger Riera Molina; Camilo Rey; Thiago Serra; Eloi Puertas; Oriol Pujol (CPAIOR, 2022)

The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. - Xin Yu 003; Thiago Serra; Srikumar Ramalingam; Shandian Zhe (ICML, 2022)

Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. - Aidan Good; Jiaqi Lin; Xin Yu 003; Hannah Sieg; Mikey Ferguson; Shandian Zhe; Jerzy Wieczorek; Thiago Serra (NeurIPS, 2022)

Template-Based Minor Embedding for Adiabatic Quantum Optimization. - Thiago Serra; Teng Huang 002; Arvind U. Raghunathan; David Bergman (INFORMS J. Comput., 2022)

Optimal Decision Diagrams for Classification. - Alexandre M. Florio; Pedro Martins; Maximilian Schiffer; Thiago Serra; Thibaut Vidal (AAAI, 2023)

Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. - Junyang Cai; Khai-Nguyen Nguyen; Nishant Shrestha; Aidan Good; Ruisen Tu; Xin Yu 003; Shandian Zhe; Thiago Serra (CPAIOR, 2023)

When Deep Learning Meets Polyhedral Theory: A Survey. - Joey Huchette; Gonzalo Muñoz 001; Thiago Serra; Calvin Tsay (CoRR, 2023)

Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks. - Fabian Badilla; Marcos Goycoolea; Gonzalo Muñoz 001; Thiago Serra (CoRR, 2023)

Optimization over Trained Neural Networks: Taking a Relaxing Walk. - Jiatai Tong; Junyang Cai; Thiago Serra (CPAIOR (2), 2024)

Seamless Multimodal Transportation Scheduling. - Arvind U. Raghunathan; David Bergman; John N. Hooker; Thiago Serra; Shingo Kobori (INFORMS J. Comput., 2024)

Optimization over Trained (and Sparse) Neural Networks: A Surrogate within a Surrogate. - Hung Pham; Aiden Ren; Ibrahim Tahir; Jiatai Tong; Thiago Serra (CoRR, 2025)

Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts. - Radhika Kulkarni; Gianluca Brero; Yu Ding; Swati Gupta; Sven Koenig; Ramayya Krishnan; Thiago Serra; Phebe Vayanos; Segev Wasserkrug; Holly Wiberg (CoRR, 2025)