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Our expert team leverages cutting-edge techniques to develop bespoke models tailored to your unique needs. Whether you require predictive analytics, optimization algorithms, or simulation tools, we collaborate closely with you to understand your objectives and design solutions that drive actionable insights.
I am a doctoral researcher at Stanford University, specializing in the application of AI and machine learning methodologies to enhance industrial operations, supply chain management, and logistics.
I am researcher at Stanford University, where I study the stability and control of nonlinear dynamical systems to model and simulate complex phenomena such as chaos, bifurcations, and synchronization.
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models
GitHub - teshnizi/OptiMUS: Optimization Modeling Using mip Solvers and large language models