Dr. José Antonio Marmolejo-Saucedo
Research Professor at the National Autonomous University of Mexico ( Universidad Panamericana), Guadalajara Campus, and a Level 3 member of the National System of Researchers (SNI). He earned his Ph.D. in Operations Research with honors from UNAM. He served as a scientific consultant for Romway Machinery Manufacturing Co., Ltd. in Zhejiang, China, where he implemented digital twin technology in modular smart factories for large-scale optimization.
His research lies at the intersection of operations research, large-scale mathematical optimization, and emerging digital technologies. His current research areas are: Cognitive Federated Digital Twins for the Optimization and Autonomous Control of Large-Scale Systems, integrating LFM (Layer Foundation Models), deep reinforcement learning, and heuristics in distributed digital twin architectures; and Large-Scale Optimization in Digital Twins via QUBO formulations and Hybrid Quantum-Classical Solvers, leveraging quantum annealing to solve complex combinatorial problems embedded in digital simulation environments.
His work integrates artificial intelligence, advanced analytics, IoT, discrete-event simulation, and Industry 4.0/5.0, with applications in logistics, manufacturing, energy, mobility, and supply chain systems. He actively collaborates with researchers from China, the U.S., the U.K., Russia, Turkey, Ukraine, Malaysia, Thailand, and Mexico, and has more than 200 research outputs, including indexed articles, books, book chapters, and international presentations.
Research Areas
- Cognitive Federated Digital Twins for Optimization and Autonomous Control of Large-Scale Systems
- Large-Scale Optimization in Digital Twins Using QUBO Formulations and Hybrid Quantum-Classical Solvers