1015: Mathematical Optimization in the Agentic AI Era, with Gurobi's Jerry Yurchisin
In Episode #1015, Jerry Yurchisin (manager of decision intelligence strategy at Gurobi Optimization) joins Jon Krohn to explain the AI technology that makes breaking a constraint mathematically impossible. Large language models will confidently claim they've optimized your business while ignoring the one constraint that could cost millions, whereas optimization treats constraints as hard guarantees. Jerry lays out the division of labor he sees for the agentic era: agents help you frame the problem, write the formulation and generate the code, then hand off to a solver like Gurobi, soon callable via MCP servers. In this episode, Jerry breaks down the three building blocks of any optimization model, traces the leap in non-linear solving, explains how to pitch optimization to your CFO and to the planners whose jobs it touches, and shares case studies spanning energy grids, retirement planning and USA Cycling's Paris 2024 gold.
Additional materials: https://www.superdatascience.com/1015
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(02:42) The three building blocks of an optimization model
(21:43) Where optimization fits in the agentic AI era
(29:58) Inside the Gurobi Intelligence Hub
(39:40) Energy, retirement planning and a cycling gold medal
(50:58) How to sell optimization inside your organization
940: In Case You Missed It in October 2025
Jon Krohn curates a selection of clips from the month that was. Hear from the orchestrators of an expanding AI universe in this episode of In Case You Missed It, with news, views and groundbreaking ideas from Sheamus McGovern, Jerry Yurchisin, Stephanie Hare, Larissa Schneider, and Adrian Kosowsky. We cover baby dragons, the Hippocratic Oath, and, of course, all the latest in artificial intelligence!
Additional materials: www.superdatascience.com/940
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin
AI predictions, and how to act on them: Data Science Strategist at Gurobi, Jerry Yurchisin, speaks to Jon Krohn about how mathematical optimization helps enterprises automate decisions for business success and where to find the resources to make it happen.
This episode is brought to you by the ODSC, the Open Data Science Conference, by Fabi, by Dell, and by Intel.
Additional materials: www.superdatascience.com/931
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(02:34) What mathematical optimization is
(13:58) How to get started with mathematical optimization
(45:56) Gurobi’s use cases
(56:29) Quantum computing and mathematical optimization
813: Solving Business Problems Optimally with Data, with Jerry Yurchisin
Jerry Yurchisin from Gurobi joins Jon Krohn to break down mathematical optimization, showing why it often outshines machine learning for real-world challenges. Find out how innovations like NVIDIA’s latest CPUs are speeding up solutions to problems like the Traveling Salesman in seconds.
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
• The Burrito Optimization Game and mathematical optimization use cases [03:36]
• Key differences between machine learning and mathematical optimization [05:45]
• How mathematical optimization is ideal for real-world constraints [13:50]
• Gurobi’s APIs and the ease of integrating them [21:33]
• How LLMs like GPT-4 can help with optimization problems [39:39]
• Why integer variables are so complex to model [01:02:37]
• NP-hard problems [01:11:01]
• The history of optimization and its early applications [01:26:23]
Additional materials: www.superdatascience.com/813
723: Mathematical Optimization, with Jerry Yurchisin
Mathematical optimization should be known to every data scientist: Jon Krohn speaks to Jerry Yurchisin, Data Science Strategist at Gurobi, the decision-making technology and best-kept secret of 80% of America’s leading enterprises.
This episode is brought to you by the Zerve data science dev environment, by ODSC, the Open Data Science Conference, and by CloudWolf, the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• What mathematical optimization is [04:27]
• How Gurobi solver works [29:01]
• How to use Gurobi with Python [36:08]
• Coding and algebra resources [41:14]
• When to use mathematical optimization and machine learning together [54:23]
• Using mathematical optimization in natural language processing [1:01:00]
Additional materials: www.superdatascience.com/723