Luiz Henrique Cherri, Ph.D.

I co-founded ODM to apply mathematical optimization and AI to business problems that conventional models cannot solve. I lead multidisciplinary teams end-to-end, from solution architecture to deployment at scale, at the intersection of science, technology, and strategy. We transform complex decisions into scalable, data-driven systems, delivering measurable impact across logistics, finance, agribusiness, and operational planning. Under my leadership, ODM developed projects that: → reduced logistics costs by up to 15% through online optimization and intelligent supplier selection → outperformed financial benchmarks with proprietary portfolio construction models → increased agricultural margins by 5.7% using advanced productivity forecasting models → accelerated decision-making processes through the integration of AI, optimization, and operational automation My role spans strategic definition and solution architecture to technical leadership of multidisciplinary teams, connecting applied research, engineering, and business execution.

I served as Partner and Head of Quantitative Research, responsible for defining proprietary portfolio strategies for fixed income and equity funds, integrating mathematical optimization, machine learning, and risk management in live production environments. I led a highly skilled technical team, bridging applied scientific research and market practice. Under my leadership: → we developed strategies that consistently outperformed benchmarks, delivering higher risk-adjusted returns → we built proprietary backtesting and data collection libraries, reducing redundancies by 50% and accelerating real-time decision-making → in partnership with UFG's AI Center of Excellence, we led the development of an LLM-based autonomous investment assistant, a project that secured R$1M in funding through EMBRAPII

I served as co-advisor for Master's students in Production Engineering, supervising research in mathematical optimization and applied modeling for industrial problems. My role involved research methodology design, critical analysis of models and methods, dissertation structuring, and support for publications in leading international journals. Beyond technical mentorship, I contributed to developing researchers capable of bridging mathematical rigor and practical application.

I conducted research on cutting and packing optimization for irregular pieces, a problem with direct applications in manufacturing and materials management. I developed mathematical models, optimization algorithms, and heuristic methods published in leading international journals. I collaborated with multidisciplinary teams, managed industry-partnered research projects, and mentored undergraduate and graduate students. This period shaped my ability to tackle high-complexity problems by combining rigorous modeling with applied thinking, the same foundation I brought to ODM.

Ph.D. conducted under a dual-degree (cotutelle) agreement between the Institute of Mathematics and Computer Sciences at the University of São Paulo (USP), Brazil, and the Faculty of Engineering at the University of Porto, Portugal. The research focused on developing computational models and methods to solve a class of mathematical optimization problems known as nesting problems, which deal with the efficient cutting of irregularly shaped pieces. This work resulted in the doctoral thesis titled “Nesting Problems”, which includes several peer-reviewed articles published in high-impact international journals.

Ph.D. conducted under a dual-degree (cotutelle) program with the University of São Paulo. The research focused on developing computational models and methods to solve a mathematical optimization problem known as the nesting problem, culminating in the doctoral thesis titled "Nesting Problems". Throughout this period, I deepened my expertise in analytical techniques, data science, and both the theory and practice of optimization and operations research. A key benefit of the dual-degree experience was the opportunity to bridge industrial challenges with engineering, mathematics, and computer science in a highly integrated way.

During my master’s degree at USP, I focused my research on the lot-sizing problem, aiming to optimize industrial production by strategically determining which products to manufacture, on which machines, and in what quantities. My work culminated in the thesis entitled “A hybrid method for the lot-sizing problem". This experience strengthened my skills in advanced mathematical modeling, combinatorial optimization, and the development of hybrid methods applied to solving complex industrial planning challenges.

Faça em ingles16:10Claude responded: > The MBA in Finance and Controllership from USP deepened my ability to structure and navigate complex financial decisions with rigor, a competency I apply di… The MBA in Finance and Controllership from USP deepened my ability to structure and navigate complex financial decisions with rigor — a competency I apply directly in leading the companies where I serve as partner and strategic advisor. The program strengthened my perspective on risk management, investment analysis, strategic planning, and financial governance, building a concrete bridge between the quantitative rigor of my background in mathematics and optimization and the executive language that drives business decisions.

The undergraduate program provided a strong and comprehensive foundation, integrating knowledge in mathematics, computing, and their practical applications. Throughout the course, I developed core skills in mathematical modeling, algorithms, optimization, data analysis, and scientific programming, with a focus on solving complex and high-impact problems. This advanced technical foundation was crucial in enabling me to apply mathematical and computational concepts to real-world environments, delivering innovative and effective solutions to strategic challenges across diverse industrial and technological sectors.