May 10th, 2023, 10:00 am PT / Category: Interviews
What is Optimization and how does it relate to AI and Data Science? What kinds of applications is Optimization used for and what skills are needed to apply it successfully?
Summary of the video
Dr. Irv Lustig, the optimization principal at Princeton Consultants, discusses the essential role of optimization in the AI revolution. He highlights the need for comprehensive thinking in applying optimization, from understanding the problem to deploying the solution and changing decision-making processes. Princeton Consultants focuses on management consulting and information technology, applying optimization to help customers make better decisions. The convergence of optimization and AI is driven by the availability of data, which enables improved decision-making. Optimization can automate processes and solve business problems efficiently. Skills required for optimization include a background in operations research, data science, and business analytics. Dr. Lustig emphasizes the importance of communication and considering downstream effects when implementing optimization solutions. He suggests pursuing degrees or programs in operations research, business analytics, or data science and attending conferences to learn more about optimization and its applications.
Bio
An internationally recognized subject matter expert and thought leader in Operations Research and Optimization, Dr. Irv Lustig manages the design and deployment of custom optimization solutions at Princeton Consultants. He also leads Princeton’s optimization model review and validation service, the first quality assurance service of its kind for advanced analytics.
In 1993 Irv became Employee #7 at CPLEX, the trailblazing commercial optimization solver that was later acquired by ILOG and then IBM, and at various times Irv led product development, technical services, and sales. At IBM Research, Irv investigated approaches for the next generation of optimization/business integration.
Irv received Sc.B. and Sc.M. degrees in Applied Mathematics/Computer Science from Brown University and a Ph.D. in Operations Research from Stanford University, where he studied under George Dantzig, the father of linear programming. Irv was an Assistant Professor at Princeton University, where he won the Beale-Orchard-Hays Prize for excellence in computational mathematical programming. He has authored more than 30 articles and scientific papers.
Irv is a fellow and longtime active member of INFORMS—the largest professional society in the world for professionals in the field of operations research (O.R.), management science, and business analytics—and he is a Certified Analytics Professional.
