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Wes Chaar
Wes Chaar

Wes Chaar

CEO
WesChaar
Bio

Over the course of his career, Wes brought his deep knowledge of mathematical modeling and computer science, establishing himself as a leading expert in the Analytics, Data Science, Machine Learning, Artificial Intelligence, and Data Fusion fields. Wes has driven industry-leading innovations in the Airlines, Hospitality, CPG, Retail, Advertising, Media, Marketing, Private Equity, and Data Services sectors.

His work has been recognized, including receiving an Emmy for Engineering and Technology (Turner team), the INFORMS Innovative Applications of Analytics Award, the ANA Genius Awards for Marketing Analytics Science, the ANA Genius Awards for Excellence in Pioneering Analytics Innovation, the ARF Great Mind Award in Analytics Leadership, Corinium’s Top 100 Innovators in Data & Analytics for the Americas, finalist for the Wagner Prize, finalist for the Edelman Award, and more. Furthermore, he has published in numerous journals and proceedings, including IEEE Transactions, M&SOM, AAS, Interfaces, and others, and has presented at conferences around the globe. He is a member of AIAA, IEEE, and INFORMS.

Wes attained his Ph.D. from the University of Texas at Austin. He resides in Dallas, Texas.


Responsible AI, Responsible Optimization: Charting the Future of Decisioning

As artificial intelligence (AI) and optimization technologies rapidly evolve, organizations face a historic opportunity—and responsibility—to reshape how decisions are made. This talk explores the convergence of AI’s predictive power and operations research’s prescriptive rigor, arguing that the future of enterprise decisioning lies in their thoughtful integration. Generative AI, machine learning, and mathematical optimization each play distinct but complementary roles: while AI reveals what might happen, optimization determines what should be done. Yet, neither is inherently aligned with fairness, transparency, or ethics—hence the growing need for responsibility at the core of every system.

In this session, we will examine the foundations of Responsible AI and Responsible Optimization, presenting a framework for building intelligent systems that are not only effective, but also trustworthy and explainable. From dynamic pricing and fraud detection to resource allocation and customer engagement, we’ll highlight real-world use cases where AI and optimization must be orchestrated responsibly. The session concludes with a vision of “Decision Intelligence” platforms that integrate human judgment, algorithmic governance, and ethical safeguards. 

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