Gurobi Summit Americas 2024
September 19 & 20, 2024
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Wynn Encore Resort, Las Vegas, Nevada
Join us this September in Las Vegas at the beautiful Wynn Encore, our event venue! This exclusive event includes informative presentations, inspiring use cases, hands-on training, and one-on-one consultation sessions with our experts. Plus, you’ll get to network with other like-minded professionals, learn how others are using decision intelligence technology, and share you own success stories.
Why the Gurobi Summit?
Optimization is all around us—calculating the quickest route on your mobile phone, ensuring timely package deliveries, and streamlining your airline and hotel bookings. But how can this decision intelligence technique impact your organization?
This will be a valuable, educational, relationship-building event that you won’t want to miss.
Benefits for You:
Summit Highlights:
Don’t leave your decisions to chance! Join us in Las Vegas this September.
Who Should Attend
Operations Researchers
Sharpen your mathematical modeling and optimization skills, with guidance from our experts.
Data Scientists
Learn how to turn your predictions into optimized business decisions.
Business Leaders
Discover how decision intelligence can help you achieve multiple, conflicting objectives simultaneously—amid an ever-changing business landscape and global disruption.
Registration Pricing
May 29, 2024 – September 3, 2024
$195
Starting September 4, 2024
$295
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Duke PerrucciChief Executive Officer Gurobi Optimization |
Mr. Perrucci has more than 30 years of experience in roles spanning sales, marketing and analytics. He joined Gurobi in 2018 as the CRO, heading both sales and marketing. He then moved into the COO role and ultimately the CEO position in 2023. Prior to Gurobi, he held the position of CRO at Cambridge Analytica – a predictive analytics firm. Here he built the commercial practice in North America by helping companies drive better advertising through the use of artificial intelligence. Before Cambridge he spent 8 years in the MarTech space with FocusVision. Here he built a global sales organization across 6 continents and 10 offices. Prior to FocusVision, Mr. Perrucci spent a total of 9 years at Information Resources Inc. (IRI) working in various analytic consulting roles across the entire PepsiCo enterprise. After the first 4 years at IRI, he decided to gain experience on the brand side and moved into analytics at Unilever. Before long he secured a position in brand management working on the Bertolli business – a $400 million brand in the United States. When IRI came calling again, it was an offer too good to pass up – running the Pepsi Cola and Quaker businesses out of PepsiCo’s world headquarters in Purchase, NY. Before this journey, Duke earned a BA in Classical Civilization from Fordham University. While en route, he earned his MBA from Cornell University.
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Michael NorthVice President of NFL Broadcast Planning & Scheduling. NFL - National Football League |
Michael North is in his 25th season with the NFL and his 22nd in the Broadcasting Department where he is part of the team that creates the playing schedule each season. North works closely with the 32 Clubs, network television partners, stadium operators, and the NFL’s International team while managing the relationships with software and hardware vendors, as well as mixed integer programming, combinatorial optimization, and predictive analytics experts, in an effort to help search through millions of permutations in pursuit of the one magical, mythical, “perfect” NFL schedule each season that satisfies all the teams and television networks. A 1992 graduate from Washington University in St. Louis with a degree in computer science, Mike lives with his artist wife, three teenage sons, two dogs, and a turtle in Westchester County, NY, tantalizingly close to Hudson National Golf Club.
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Charlotte CareyDirector of Broadcasting NFL - National Football League |
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Ian FinderGroup Product Manager, Accelerated Computing NVIDIA |
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Dr. Zonghao GuChief Research Fellow Gurobi Optimization |
Dr. Zonghao Gu has a B. Eng. in Mechanical Engineering and an M. Eng. in Industrial Management from Tongji University, Shanghai. He has a PhD in Industrial Engineering from the Georgia Institute of Technology. Dr. Gu has published several papers on the computational aspects of mathematical programming. He is one of the world’s leading experts on the computational aspects of linear, integer, and quadratic programming, and is particularly well known for his deep understanding of cutting planes and their application to the solution of general mixed-integer programs. Dr. Gu worked from 1995 to 1998 as an optimization software developer for LINDO Systems, Inc., before joining the ILOG CPLEX R&D team in 1998 as a senior software developer and later as a Distinguished Scientist. From 2005 to 2008 he was Project Architect for the CPLEX R&D team and was the lead developer for CPLEX 11. He was responsible for the implementation of the CPLEX QP simplex and MIQP solvers, had primary responsibility for the presolve and cutting plane routines, and made various contributions to the CPLEX LP simplex solver.
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Carl DukatzGlobal Quantum Program Lead Accenture |
Carl Dukatz is the Global Lead of the Quantum Computing Program at Accenture. Over the past five years he has led the creation of dozens of quantum applications and prototypes, published research and business perspectives on quantum, and developed multiple training and workforce readiness programs for quantum practitioners. Today, Carl focuses on helping businesses map their most challenging problems to formulations that will one day run more efficiently on quantum computers.
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Kirk BorneFounder Data Leadership Group |
Dr. Kirk Borne is the founder and owner of Data Leadership Group LLC, advisor to AI startups including Prime.ai, career data professional, data science leader, and research astrophysicist. From 2015 to 2021, he was Principal Data Scientist, Data Science Fellow, and Executive Advisor at Booz Allen Hamilton. Previously, he was Professor of Astrophysics and Computational Science at George Mason University. Before that, he spent 20 years supporting data systems activities for NASA space science missions, including the Hubble Telescope. He is a top worldwide social influencer promoting data science and AI for all.
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Priyanshu MutrejaSenior Principal Engineer Toyota Motor North America |
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John LybargerManager & Product Owner Toyota Motor North America |
John Lybarger is a Manager & Product Owner on the Supply Chain & Fulfilment Transformation (SCaFT) team at Toyota Motor North America in Plano, Texas. With over 10 years at Toyota, John has held various roles in R&D and Quality, which have equipped him with a deep understanding of the company’s operations and strategic needs. Since May 2023, he has guided the development and launch of Sim Engine Supply Chain Resiliency (SCR) and Customer Experience (CX) products, effectively navigating supply chain disruptions and enhancing operational efficiency while delivering innovative solutions for Toyota’s customers.
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Dr. Ed KlotzSenior Mathematical Optimization Specialist Gurobi Optimization |
Dr. Ed Klotz has over 30 years of experience in the mathematical optimization software industry. He is a technical expert who, over the course of his career, has worked with a wide array of customers to help them solve some of world’s most challenging mathematical optimization problems. In his role as a Senior Mathematical Optimization Specialist on the Gurobi R&D team, Dr. Klotz works closely with our customers to support them in implementing and utilizing mathematical optimization in their organizations. He also interacts heavily with the R&D team based on his experiences with the customers.
Prior to joining Gurobi, Dr. Klotz was a member of the CPLEX development team of IBM. He was involved in product development, customer training, product documentation, and numerous other tasks, with a primary focus on delivering CPLEX customer support and leveraging his experiences with customers to help inform the R&D team about customer needs and product improvements. Dr. Klotz has extensive knowledge in linear programming, integer programming, and numerical linear algebra for finite precision computing. Using this knowledge, he was able to investigate customer support issues at the source code level and identify potential improvements in CPLEX, both in terms of performance and accuracy of computation.
Before joining IBM, Dr. Klotz was a principal technical support engineer at ILOG, Inc., and a mathematical programming specialist at CPLEX Optimization, Inc.
Dr. Klotz has presented at numerous conferences, workshops, and web seminars and published numerous papers on mathematical optimization. His interests are in all aspects of mathematical programming, with a primary interest in research that can impact mathematical programming software. He obtained a BA in Math and Economics from Oberlin College and a PhD in Operations Research from Stanford University.
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Dr. Markus G. DrouvenTechnical Director, National Methane Emissions Reduction Initiative U.S. Department of Energy, National Energy Technology Laboratory |
Dr. Markus Drouven is an Oil & Gas Systems Optimization Expert with the U.S. Department of Energy’s National Energy Technology Laboratory (NETL). He has over a decade of experience in developing and deploying decision-support solutions for energy systems. Markus is an engineer by training, having earned a Bachelor’s degree in mechanical engineering, and a Master’s degrees in chemical engineering. He also holds a Ph.D. in Process Systems Engineering from Carnegie Mellon University. Prior to joining NETL, Markus was with EQT Corporation, the largest natural gas producer in the United States, where he was responsible for establishing an in-house optimization engineering team. At NETL, Markus is currently serving as the Technical Director of NETL’s National Methane Emissions Reduction Initiative, NEMRI.
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Brett StewartAI Solutions Director C3.ai |
Brett Stewart, PhD is an AI Solutions Director at C3 AI. Drawing from 15 years of manufacturing experience, he partners with customers to develop and implement tailored AI solutions to solve business challenges. Prior to C3 AI, Brett was an optimization engineer at ExxonMobil. He holds a Bachelor of Science in Chemical Engineering from The University of Texas at Austin and a Doctor of Philosophy in Chemical Engineering from the University of Wisconsin-Madison.
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Suman TripathyLead Data Scientist C3.ai |
Suman Tripathy is a Lead Data Scientist at C3 AI. She is the product lead for C3 Process Optimization. She has been a key developer for the application and progressed it across C3 platform versions V7 and V8. She also managed C3 Process Optimization app deployments across eight different customers and numerous industries. Prior to C3 AI, she attained a B.S. in Electrical Engineering & Computer Science from UC Berkeley as well as an M.S. in Data Science from Columbia University.
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Bruno Scalia C. F. LeiteSenior Data Scientist Suzano S.A. |
Bruno Scalia C. F. Leite is a senior data scientist specializing in operations research, developing supply chain digital solutions for a leading pulp and paper company. With a robust background in optimizing complex logistical and operational systems, Bruno has consistently driven significant efficiency improvements and cost reductions within the industry. At Suzano S.A., Bruno is pivotal in leveraging advanced analytical methods and tools, including Gurobi, to tackle intricate supply chain challenges. His position combines theoretical aspects of operations research, including linear programming, integer programming, and heuristics, with modern software engineering and data solutions to create efficient decision intelligence systems in a dynamic business environment. Bruno's contributions have streamlined operations and fostered a culture of continuous improvement and innovation both inside and outside the organization. By contributing to established code packages, distributing online short courses, sharing open-source coding examples, writing about modeling, and mentoring projects, he has been instrumental in navigating the complexities of operationalizing operations research and numerical optimization solutions. As a speaker at the Gurobi Summit, Bruno will share valuable insights from his extensive experience in the pulp and paper industry, highlighting real-world applications of Gurobi in optimizing supply chain operations across strategic to operational levels. Attendees can look forward to gaining practical knowledge and innovative strategies to apply in their own operational contexts. Bruno holds a Master’s degree in Chemical Engineering from Universidade Federal de Minas Gerais (UFMG), where he dedicated his research to numerical methods and applications of numerical optimization to complex industrial processes. He continues contributing to the academic environment by co-mentoring undergraduate projects inspired by real-world industrial applications of operations research.
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Gourav GuptaSenior Data Scientist ABC Supply |
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Prashanth DevireddySenior Data Scientist ABC Supply |
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Carolyn MooneyCEO Nextmv |
Carolyn Mooney is CEO of Nextmv, a DecisionOps platform that accelerates optimization AI teams with tools for deployment, testing, CI/CD, collaboration, and management of decision models. Previously, she analyzed simulations at Lockheed and Zoomer, and also ran Grubhub’s Systems Engineering team, impacting all of Grubhub’s fulfillment systems. Outside of work, she is usually coaching volleyball or playing with her pup, Wally.
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Ryan O'NeilCTO Nextmv |
Ryan O'Neil is CTO of Nextmv, a DecisionOps platform that accelerates optimization AI teams with tools for deployment, testing, CI/CD, collaboration, and management of decision models. Previously, he led the Decision Engineering department at Grubhub and Zoomer, which owned forecasting, scheduling, routing, and simulation. Additionally, Ryan worked as an Operations Research Analyst at MITRE, and led software teams at The Washington Post, Yhat, and Polimetrix. During this, he earned a PhD in Operations Research at George Mason University, and wrote his dissertation on real time routing for pickup and delivery problems.
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Dr. Jay ForakerLead Data Scientist Aimpoint Digital |
Jay is a Lead Data Scientist with 10+ years of experience leading teams of operations research analysts. He has supervised 21 different capstone projects focused on resource allocation, supply chain management, discrete event simulation, data visualization, and scheduling. He is passionate about helping organizations use data to make better decisions and improve their operations.
Jay joins Aimpoint Digital after retiring as a Navy Captain. During his more than 30 years of service, Jay served as a Naval Flight Officer, accumulating over 2400 flight hours in T-34C, T-43A, E-6A, and E-6B aircraft. He also served as a catapult and arresting gear officer on the USS Kitty Hawk (CV-63), where he contributed to the safe launch and recovery of over 17,000 flights, including 1,500 combat missions in support of Operation IRAQI FREEDOM. His last tour in the Navy was as a Permanent Military Professor in the Mathematics Department at the United States Naval Academy. Jay holds the following degrees: a Ph.D. in Operations Research from the Naval Postgraduate School, an MA in National Security and Strategic Studies from the Naval War College, an MS from the Georgia Institute of Technology, and a BS from the United States Naval Academy.
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Dr. Linlin YangPrincipal Data Scientist Aimpoint Digital |
Linlin is a Principal Data Scientist at Aimpoint Digital with 7+ years of advanced analytics experience in the Oil & Gas industry. She brings to the team technical background in mathematical programming as well as a passion for developing practical business decision-support solutions.
Prior to joining Aimpoint, Linlin worked in various roles advocating and creating engagement opportunities for advanced analytics within ExxonMobil downstream. She worked closely with business, engineering, and research teams to create optimization and machine learning solutions for improved decision-making in areas spanning manufacturing to commercial. Linlin earned a Bachelor’s in Chemical Engineering from Cornell University and a Doctorate in Chemical Engineering from Carnegie Mellon University focused on the field of Process Systems Engineering.
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Dr. Amit GargFounder and Chief Scientist ORMAE |
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Patricia RandallDirector Princeton Consultants |
Patricia specializes in designing, developing, and implementing large-scale, high-impact systems that leverage optimization and machine learning to enhance business decision-making at strategic, tactical, and operational levels. Her engineering background enables her to translate complex mathematical models into practical business solutions across various industries, including transportation, manufacturing, biotech, finance, and advertising. In her optimization and analytics projects, Patricia collaborates on-site with client executives and subject matter experts. She leads a multidisciplinary team of optimizers, software developers, data scientists, and mathematicians. Together, they employ diverse approaches and algorithms to create functional models that deliver optimal results for complex, real-world problems. These models are custom designed to capture the unique nuances of each client's business operations. Since joining Princeton in 2007, Patricia has advanced to the role of Director. In this position, she leads teams to ensure complete client satisfaction and success. She holds a PhD in Industrial Engineering from Clemson University. As a speaker at Gurobi Days in Dallas in February 2020, Patricia presented "Optimization Powers a New Operating Universe at Birchbox," highlighting her experience in applying optimization techniques to real-world business challenges.
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Dr. Gregory GlocknerVice President and Technical Fellow Gurobi Optimization |
Dr. Gregory Glockner has a B.S. magna cum laude from Yale University in Applied Mathematics and Music, and an M.S. and Ph.D. in Operations Research from the Georgia Institute of Technology. His doctoral dissertation was awarded the 1997 Transportation Science Dissertation Prize from INFORMS. Dr. Glockner has trained users of optimization software in Brazil, Hong Kong, Japan, Singapore, South Korea, and throughout the USA and Canada. He is an expert in optimization modeling and software development: his professional experience in software development includes all major platforms and 9 of the top 10 programming languages in the TIOBE Programming Community Index. Prior to joining Gurobi Optimization in 2009, Dr. Glockner was partner and Chief Operating Officer for Dwaffler, a provider of decision analysis tools. From 1998-2007, he worked at ILOG in two different positions: as a Senior Technical Account Manager and a Product Manager. As an ILOG Senior Technical Account Manager, he introduced advanced optimization and rules software to customers across North America. As an ILOG Product Manager, he was responsible for product management of CPLEX, ODM, OPL and Solver. From 1997-1998, he worked at Pacific Gas & Electric, where he developed stochastic programming software for hydroelectric power scheduling, and he built statistical tools for energy trading in the deregulated energy market. He has also worked as an operations research analyst for the Federal Aviation Administration and for Northwest Airlines.
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Caroline DaughertyData Translator Pfizer |
Caroline Daugherty, Data Translator with Pfizer’s Operations & Insights team, has experience developing custom data science and optimization solutions for applications ranging from manufacturing to quality control. She enjoys leveraging complex data to unlock insights and drive business value.
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Abby Garrett FreemanData Translator, Pfizer Pfizer |
Abby Garrett Freeman, Lead Data Translator with Pfizer’s Operations & Insights team, has spent the last 3 years developing custom software to make insights generated from optimization, machine learning, and descriptive analytics accessible to all leadership levels at Pfizer, from floor managers up to Pfizer’s CEO, Albert Bourla.
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Marcelo ReisOptimization Director BITKA Analytics |
Marcelo Reis is Optimization Director at BITKA Analytics and one of the company's founders. He has a degree in Computer Science from the Federal University of Viçosa and a master's degree in Algorithms and Combinatorial Optimization from PUC-Rio. He has scientific papers published in several academic journals, including the Mathematical Programming journal. He has more than 20 years of experience in Advanced Analytics, having worked on several projects for large Brazilian and multinational companies.
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Jerry YurchisinSenior Data Science Strategist Gurobi Optimization |
Mr. Yurchisin has over ten years’ experience applying operations research, machine learning, statistics, and data visualization to improve decision making. Before joining Gurobi, Jerry (who also goes by Jerome) was a Senior Consultant at OnLocation, Inc. where he customized several linear programming models within the National Energy Modeling System (NEMS) to analyze implementing specific energy policies and utilizing new technologies. Prior to OnLocation, Jerry was an Operations Research Analyst & Data Scientist at Booz Allen Hamilton for over seven years. There he formulated scheduling and staffing integer programming models for the US Coast Guard, as well as led a project to quantify the maritime risks of offshore energy installations with the Research & Development Center. Further, Jerry was the technical lead on several Coast Guard studies including Living Marine Resources and Maritime Domain Awareness, providing statistical analysis and building supervised and unsupervised machine learning models. He also performed statistical analyses, machine learning modeling, and data visualization for cyberspace directorates at DoD and DHS. Jerry has several years of experience teaching a wide variety of college-level mathematics and statistics courses and has a passion for education. He also enjoys golfing, biking, and writing about sports from an analytics point of view. He lives in Alexandria, Virginia with his wife, son, and two dogs. Jerry holds B.S., Ed. and M.S., Mathematics degrees from Ohio University and an M.S. in Operations Research and Statistics from The University of North Carolina at Chapel Hill.
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Ron NorrisDirector of Innovation Georgia-Pacific |
As a catalyst for change, Ron Norris is dedicated to reshaping how work gets done. Renowned for his opportunity-focused leadership, Ron is known for sparking transformative conversations in forums around the world. Ron is at the forefront of creating innovative ways to utilize technology to assist both new and existing employees. By leveraging cutting-edge technologies like AI, Machine Learning (ML), Machine Teaching (MT), and Causal AI, he enhances operational efficiency and empowers employees to perform their best in all areas of the organization. With extensive experience in operations, manufacturing, and sales and marketing, Ron drives business growth and profitability. Throughout his career, Ron has led cross-functional teams and driven organizational transformation, breaking down complex concepts to make them understandable and actionable for all. "The work remains the same. What changes is how we participate in getting the work done."
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Dr. Cara TouretzkySenior Technical Account Manager Gurobi Optimization |
Dr. Cara Touretzky holds a BChE from University of Delaware and PhD in Chemical Engineering from The University of Texas at Austin. During her graduate work she studied dynamic optimization and model-based process control, with applications ranging from HVAC system automation to production scheduling for chemical processes. Prior to Gurobi she worked as an Application Engineer for ExxonMobil managing nonlinear controller deployments for plastic plants in the gulf coast. Cara participates in several organizations including INFORMS, IEEE, and AIChE, where she has served as a program director for the process control division.
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Dr. Alison CozadOptimization Support Manager |
Dr. Alison Cozad holds a Ph.D. in Chemical Engineering from Carnegie Mellon University where she leveraged mixed-integer and semi-infinite optimization methods to improve machine learning algorithms. Prior to joining Gurobi, she held multiple roles at ExxonMobil, including as a Senior Data Science Lead and Real-time Optimization Engineer. In her free time, Alison loves making things from CNC woodworking to electronics to cheese making to sock puppetry.
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Jennifer LockeManager of Technical Account Management-Americas Gurobi Optimization |
Jennifer Locke has over 20 years of professional experience with mathematical, statistical and data analysis software as a software engineer, consultant, pre-sales engineer and product management. She has programming expertise with all major computer programming languages. Prior to joining Gurobi, she was a lead developer on the IMSL (International Mathematical and Statistical Library) engineering team and later serving as IMSL Product Manager. Holds a BSc in Mathematics and Computer Science from College of the Ozarks and completed master’s courses in Mathematics and Computer Science at University of Tennessee Space Institute.
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Juan Antonio Orozco GuzmánSenior Optimization Engineer Gurobi Optimization |
Before joining Gurobi Optimization, Juan spent several years in the IT industry, performing roles in R&D, business intelligence, and data science. He has also taught undergraduate courses about statistical process control and mathematical optimization in the industrial engineering department at ITESM, campus Guadalajara. Juan earned a M.Sc. in statistics and operational research at the University of Edinburgh with distinction. His main interests are in optimization, machine learning, and deep learning.
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Dr. Rodrigo FuentesSenior Technical Account Manager Gurobi Optimization |
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Dr. Dan SteffySenior Optimization Engineer Gurobi Optimization |
Dr. Steffy received his PhD in Algorithms, Combinatorics and Optimization from the Georgia Institute of Technology. He has published many papers in scientific journals, including work on computing numerically exact solutions to linear and integer programming problems. Prior to joining Gurobi in 2022 he was an Associate Professor of Mathematics at Oakland University. He also spent time working as a researcher at the Zuse Institute Berlin. In his free time he loves being outdoors, playing board games and spending time with his wife and two daughters.
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Zed DeanTechnical Account Manager – Americas Gurobi Optimization |
Zed has twenty years of multi-disciplinary career experience; including IT support, data science, operational research and analytics sales. An engineer who started his career as an ICT officer at the United Nations, he was awarded outstanding contribution during the Iraq humanitarian response for his participation in building the system architecture of a rapid deployment ICT solution. He then built a predictive modeling analytical framework for promotional campaigns in the publishing industry. His inputs provided confidence in the company's strategic decisions regarding revenue management and pricing. While teaching operational research, Zed was voted the most dedicated lecturer at the university. Teaching several types of audiences; including business, engineering and informatics, exposed him to a wide range of OR applications. He most recently worked as a project manager, corporate trainer, account manager and salesperson in a highly competitive marketing analytics industry. Based in Canada, Zed enjoys kayaking and canoeing in his free time; he has great interest in the history of math and algorithms.
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Mohit AggarwalDirector of Asset Optimization BrightNight |
Mohit Aggarwal is a seasoned expert in machine learning and advanced analytics with over 15 years of experience in the energy sector. He holds a PhD in process systems engineering from Carnegie Mellon University and a bachelor’s degree in chemical engineering from IIT Delhi. Currently, as the Director of Asset Optimization at BrightNight Energy, he plays a key role in developing a cutting-edge optimization platform for the design and operation of renewable energy power plants.
Throughout his career, Mohit has held pivotal roles at renowned organizations such as Air Products, Bloom Energy, and Arm. At Air Products, he developed a real-time optimization application for the world’s largest hydrogen pipeline. At Bloom Energy, he established and led the advanced analytics and controls team, enabling the scalable operation of thousands of fuel cell energy systems. Additionally, his entrepreneurial experience includes founding a tech startup, where he built a consumer website for book reviews, gaining valuable insights into product and business development.
Mohit’s expertise lies at the intersection of energy systems, software engineering, and machine learning, and he continues to be driven by a passion for solving real-world challenges through innovative technologies.
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Dan JeffreySenior Technical Account Manager – Americas |
Dan Jeffrey has twenty years of professional experience in Math Programming and Data Science, working as a technical product expert and as a consultant. He has architecture and programming expertise with all major computer programming languages, math programming experience with Python, AMPL, and OPL plus programming expertise with the AMPL Solver library. Today, Dan is a MIP Fanatic -- working as a member of the Gurobi Support Team.
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Christian ValenteSenior Software Engineer AMPL Optimization, Inc. |
Christian Valente is a Senior Software Engineer in charge of AMPL solver interfaces, APIs, and CI/CD.
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Daniel FylstraFounder and CEO Frontline Systems |
Daniel Fylstra is founder and CEO of Frontline Systems Inc. (https://solver.com), developers of the Solver in Microsoft Excel that enables optimization for over 1 billion spreadsheet users, and the very first Gurobi ISV partner fifteen years ago in 2009. Earlier in his career, Dan was founder and Chairman of VisiCorp, the company that brought the first electronic spreadsheet, VisiCalc, to market with Apple Computer in 1979. Dan was also co-founder and Chairman of Compass Modeling Solutions in 1994, offering the first Windows-based GUI for the AMPL modeling language, and co-founder and initial President of Sierra Sciences, a biotech anti-aging research firm in 1999. Frontline Systems, a Silver Sponsor of the Decision Intelligence Summit, offers its products Analytic Solver for Microsoft Excel and its cloud-based RASON algebraic modeling language, both handling large-scale optimization models up to millions of variables and constraints, using the Gurobi Solver. With its Gurobi Solver Connector, Frontline offers an easy way for any customer using the Gurobi Solver from any source, to also use their Gurobi Solver with Microsoft Excel-based spreadsheet optimization models.
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Yash PuranikPrincipal Data Scientist Aimpoint Digital |
Yash is a Principal Data Scientist with deep expertise in the development and implementation of optimization and machine learning algorithms. Yash is particularly interested in helping clients derive value by leveraging data science and optimization techniques to solve practical problems. Prior to joining Aimpoint Digital, Yash was an Optimization Research Scientist at The Optimization Firm, where he contributed to the development of state-of-the-art optimization solver BARON. Before this, Yash was a Research Scientist at Rockwell Automation, where Yash developed novel algorithms for learning on streaming data, which led to multiple patents. Yash obtained his PhD in Chemical Engineering from Carnegie Mellon University.
Welcome to The Gurobi Decision Intelligence Summit! Hear the latest Gurobi Optimization news and updates from CEO Duke Perrucci.
Optimization is all around us—calculating the quickest route on your mobile phone, ensuring timely package deliveries, and streamlining your airline and hotel bookings. Optimization technology is being used in all those situations because it “creates value” – but what exactly does that mean? What’s the hidden connection between a deeply mathematical puzzle-solving tool, and your bottom-line results? What is the interplay between complexity and value?
The optimization market is changing as the compute landscape shifts to emerging technologies. High-performance computing is on the rise as GenAI is pushing widespread GPU and TPU demand. Niche technologies like quantum and neuromorphic are capturing the imagination of the next generation. Classical processors continue to be a work horse for enabling these specialized systems while not losing their edge on critical load types. This new landscape means an inherent change for how decision sciences teams and systems will be incorporated into business. As companies can address larger and more complex challenges, redefining what is tractable, they must also be agile enough to adopt new practices and adapt to the changing landscape.
Every few years, a new computing technology emerges with the promise to transform the world. Some technologies like the personal computer, the internet and the smartphone became indispensable tools in our work and personal lives. Others, like the CD-ROM, had limited impact. Here, we consider three emerging technologies that may transform optimization: GPU computing, Generative AI and Quantum Computing. We will learn how each may potentially benefit optimization, and whether they are likely to become the next big thing or whether they may become a footnote in computing.
Hear from the NFL’s Mike North, VP of Broadcast Planning, and Charlotte Carey, Director of Broadcast, on the latest learnings on how they helped to solve one of the hardest scheduling problems in existence.
Methane emissions are known to contribute significantly to climate change. Despite its shorter atmospheric lifespan than carbon dioxide, methane is a highly potent greenhouse gas (GHG), with a 20-year warming potential 80 times that of carbon dioxide. According to the EPA, about one-third of the current GHG-induced warming is attributed to anthropogenic methane emissions, with oil and natural gas operations identified as the foremost industrial source of methane emissions across the U.S.
Most oil and gas production sites across the country (roughly 80%) are low-production well sites, yielding, on average, 15 barrels of oil equivalent per day or less. Despite contributing to only 6% of overall oil and gas production across the nation, the combined methane emissions from these well sites constitute about 50% of the total methane emissions from all oil and gas production sites in the United States. In addition, several studies have found that abandoned and orphaned wells – which produce no hydrocarbons at all – can also release substantial quantities of methane into the atmosphere. Relative to their energy output, these low- and non-producing wells emit a disproportionate amount of methane, which makes them a particularly attractive target for environmental mitigation.
The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) is developing and releasing a portfolio of software tools to help reduce methane emissions from oil & gas operations. Specifically, NETL is making available a suite of free and open-source optimization-based decision-support tools that can help identify, characterize, prioritize, and mitigate methane emissions from oil & gas wells. These tools are designed to make recommendations about (1) which wells to target for “retirement” (known as permanent “plugging” in the industry), (2) how to make best use of precious well characterization and emissions quantification resources, and ultimately (3) how to design and execute efficient and impactful well plugging campaigns.
This talk will provide an example of one such optimization tool that NETL has developed to help guide emissions mitigation efforts across the oil & gas sector. It will highlight specifically how this tool addresses the many challenges that industry and state regulators face in this space, and why mathematical optimization – due to its distinctive attributes – is particularly suitable for meeting the technical and non-technical needs of decision-makers.
In this presentation, we explore the transformative potential of combining Causal AI, Automated Reasoning, and advanced Optimization to tackle complex business problems. We delve into how utilizing cutting-edge optimization techniques, integrated with Causal AI, drives improved decision-making, operational efficiency, and business growth. Attendees will gain insights into practical applications, illustrating how these technologies empower organizations to solve intricate challenges, improve profitability, and stay competitive in a dynamic market landscape.
This presentation examines the role of optimization tools in the renewable energy sector, focusing on how BrightNight’s PowerAlpha platform, powered by Gurobi’s optimization engine, transforms the design and operation of hybrid renewable power projects. As the energy industry targets greater sustainability and reliability, advanced decision-making tools are becoming increasingly essential.
PowerAlpha integrates advanced engineering with financial modeling to align fluctuating renewable energy production with grid demands. By leveraging Gurobi’s optimization engine, it simulates millions of design scenarios to find the most cost-effective configurations, ensuring projects achieve top-tier Levelized Cost of Energy (LCOE) and maximize returns.
Through case studies, the presentation will showcase how PowerAlpha optimizes solar and storage systems, delivering reliable power to data centers while achieving significant cost savings. PowerAlpha offers a comprehensive solution to the challenges of renewable energy project development, setting a new standard in the industry.
In the dynamic and competitive pulp and paper industry, integrated decision systems are crucial for companies to run efficient supply chain operations and establish a solid market position. These systems can assist decisions at several granularity levels reducing costs and improving overall performance with an integrated operational perspective. At Suzano S.A., the in-house data team created the Pulp Planning Portal in that sense, applying advanced analytical methods and tools, and leveraging numerical optimization models to assist operations across strategic, tactical, and operational levels. Exploring the flexibility ensured by mathematical models and the powerful solver performance of Gurobi, their tailor-made solutions are easily adapted to complex ever-changing business requirements.
At the strategic level, the models focus on long-term decisions such as capacity planning, resource allocation, production, product replacements, annual contract rules, and restricted demand planning on monthly buckets. The outcome of strategic models goes to the tactical level where mid-term decisions are taken on weekly buckets, such as vessel nomination, and inventory management. These results are unfolded into short-term operations planning on daily buckets with detailed production planning, transportation logistics, and vessel loading.
Based on experience implementing these systems, in this presentation, we aim to share how they can run in an integrated manner and how they help Suzano S.A. to solidify its position as a market leader in the pulp and paper industry. The path towards Suzano’s current technology position will be presented showcasing the main challenges and insight on both business and technical aspects.
Join us to explore the journey from conceptualization to implementation of these decision systems and discover the tangible benefits they bring to the industry.
Gurobi can handle a number of nonlinear functions in optimization models. Historically, Gurobi first supported convex quadratic function in the objective and constraints. With Gurobi 9.0, Gurobi introduced a global solver for non-convex quadratic models and automatic piecewise-linear approximations of common arithmetic functions. Gurobi 11.0 comes with support for global optimization of models containing univariate nonlinear functions . In this talk, we will review those various features and present our current work for tackling nonlinearities better, including a preview of Gurobi 12.0.
The automotive industry faced unprecedented supply chain disruptions following the pandemic, impacting production and delivery across the sector. In this presentation, we will showcase how Toyota developed and leveraged optimization techniques to dynamically update its production plans to enhance supply chain resilience and adaptability. Additionally, we will also discuss how we further extended these capabilities to meet evolving customer demands as part of the broader Supply Chain and Fulfillment Transformation efforts. Attendees will gain insights into the practical application of optimization in navigating complex supply chain scenarios and adapting to a rapidly changing market landscape.
Artificial Intelligence is rapidly transforming industry and manufacturing. At C3.ai, we provide artificial intelligence-based applications to enable this transformation. We will highlight a recent success providing an optimization application for sugar manufacturing that offers hourly AI-optimized recommendations to operators. The presentation will cover our dual approach of Machine Learning paired with Gurobi optimization for this customer solution.
NVIDIA Grace™ is a groundbreaking Arm® CPU platform with uncompromising performance and efficiency. Discover how the NVIDIA Grace Family is revolutionizing the enterprise data center when paired with NVIDIA GPUs, such as the accelerated NVIDIA Grace Hopper Superchip, which delivers breakthroughs AI at scale, or as a standalone CPU for leading efficiency and scalability across the rest of the data center. Leverage a robust ecosystem of Arm solutions, OEMs, ISVs and system integrators to reduce your carbon footprint and transform your organization’s compute capabilities with a trusted, end-to-end solution.
Join us for dinner after a day of learnings and networking.
We’ll welcome you to Day 2 and will give you an overview of the tree tracks to choose from to ensure you get the most out of your day.
Grab your badge, some coffee and get ready to join us for two days packed with learnings and networking!
This session invites you to explore the complexities of decision-making through the Burrito Optimization Game, where you take on the role of a burrito truck owner, tasked with feeding hungry customers and ensuring tasty profits. Through gameplay and discussion, you’ll learn how some decisions can be made intuitively, while others—due to their complexity, tradeoffs, and time constraints—require optimization tools. After the game, we’ll tie these lessons to real-world problems, illustrating how similar challenges arise in areas like warehouse placement and oil well location.
This session will introduce you to the importance and fundamentals of Mathematical Optimization (MO). You’ll learn how MO differs from other methods in AI, how it aids in making complex decisions by translating predictions into actionable solutions, and why it’s so valuable to add this expertise to your professional toolkit. You’ll see how to identify the essential building blocks of optimization models in business problems: decision variables, constraints, and objective functions. This session will also feature a hands-in example, guiding you through running your ‘Hello World!’ optimization model.
In addition to solving LPs, MIPs and MIQCPs, Gurobi has many useful features that you may not be aware of. In this talk we review modeling features such as multiple objectives, multiple scenarios, solution pools and general constraints. We also present features to help analyzing infeasibility and tools designed to analyze and improve the performance of Gurobi on your models.
In the landscape of custom decision-support tools using commercial platforms, developers often face the challenge of navigating across multiple platforms tailored to specific analytics methodologies. As a result, optimization, ML, and simulation models tend to live in their preferred platform based on a natural division, which makes it challenging for users to interpret and reconcile the recommendations from these various models.
Gurobi’s available APIs in multiple programming languages provide a great opportunity to integrate optimization solutions in a variety of modern data warehouses and cloud architectures. In this talk, we demonstrate the benefits of Databricks through a network optimization example. Using this approach, we can streamline forecasting, optimization, and scenario analysis in a unifying platform, which can help foster better collaboration across teams with various analytics capabilities, and ultimately accelerates time-to-value in complex decision-making.
You already have an in-depth knowledge of your business challenges, likely supported by code and conditional statements that define the business rules and established specifications. Additionally, you have regression and machine learning models that provide predictions and address more intricate aspects of your business. In this session, we will guide you through converting these elements into the components of a robust optimization model. We will illustrate this by extending the example introduced in the ‘Optimization Crash Course’. By converting these existing representations into optimization frameworks, we’ll show you how to translate your predictive models into decision-making tools, embracing the principle that if you can model it, you can optimize it.
Finding an optimal solution can be quite challenging for some models. In this session, we discuss potential reasons for this and how to deal with it. We also show a few techniques that help determine why some model is infeasible. Additionally, we give insights into the geometry of MIP to better understand the difficulty of models. Heuristics are essential to finding reasonable solutions quickly. We discuss heuristics included in the solver and other general concepts.
Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior. When solving a model with numerical issues, tiny changes in the model or machine can make a big difference in the results. In this session, you will learn about Gurobi’s guidelines on numerical issues, how to identify them, how they impact your solutions and, most importantly, how to avoid them.
In today’s competitive landscape, optimizing business processes is crucial for success. This presentation explores the power of Supply Chain Optimization Systems (SCOS), leveraging mathematical optimization to improve planning and operations. We’ll delve into the key factors for identifying business challenges ripe for SCOS application.
Using a real-world case study of Vale, a leading Brazilian mining company, BITKA Analytics will showcase the development and deployment of a customized SCOS. This will demonstrate the tangible benefits achieved, overcoming challenges associated with implementing such a system.
Key takeaways:
Imagine a project where issues are identified early, users are engaged and excited, and valuable results are delivered rapidly. In this talk, we’ll explore how adopting a customized agile methodology, specifically tailored for optimization models, can revolutionize their development compared to the traditional waterfall approach.
Agile for optimization involves iterative, modular development, frequent validation, and continuous integration to manage the unique complexities of optimization problems. This approach allows for faster delivery of value, enabling teams to see results and make improvements quickly. Enhanced collaboration and continuous feedback loops foster a user-centric approach, ensuring the model meets real-world needs and gains user buy-in.
By addressing potential issues early, agile reduces risk and improves overall model quality. Through engaging case studies, we’ll demonstrate how these benefits have been realized in actual projects, showcasing the success of agile for optimization in delivering robust and efficient solutions.
See the powerful potential and significant risks of using generative AI for modeling. While generative AI can help you get started modeling and coding quickly, it often requires careful oversight. We will walk you through a couple of examples of optimization modeling using Generative AI, highlighting key issues that can arise. The session will also cover quality assurance and best practices to ensure reliable and accurate models.
In this session, Gurobi Partners AMPL, Nextmv and Ormae, and Frontline Systems will host roundtables where you can bring your questions to get insights and recommendations for your toughest problems.
AMPL Roundtable topic: Streamline & Conquer: How Optimization Boosts Efficiency
In today’s competitive landscape, streamlining operations and maximizing resource efficiency are necessities. This round table, hosted by AMPL Optimization, explores how optimization transforms performance by finding the best solutions to complex problems. Whether it’s cutting costs, improving quality, or enhancing services, optimization empowers data-driven decisions for short- and long-term gains. Join us for a dynamic discussion to share challenges, insights, and explore solutions tailored to your operational needs.
Facilitator: Christian Valente, Senior Software Engineer, AMPL
Nextmv Roundtable topic: Supercharge your growth: How optimization drives top-line revenue
When optimization technology works well it feels magical. But it is not magic. From the modeling framework to the solver, infrastructure, workflows, and people contributing, decision optimization is team sport that involves orchestrating a symphony of moving parts. This means there are opportunities to optimize within optimization technology stacks and teams in order to drive top-line revenue. This roundtable will explore what those opportunities are through different lenses: technology choices, algorithm team dynamics and productivity, solution and results analysis, business stakeholder buy-in, collaboration across disciplines, and more. Bring your questions, observations, and stories of what has or had not worked, and walk away with tangible insights into how to improve your approach going forward.
Facilitators: Carolyn Mooney and Ryan O’Neil from Nextmv
ORMAE Topic: Mitigate Risk, Maximize Results: The Power of Optimization
Many organizations operate in multiple-geographies, and for them, a disruption in one corner of supply-chain can sometime unexpectedly turn into a major risk. For example, their manufacturing may be concentrated at a single location or probably they are dependent upon a single supplier for a critical raw material. In these situations, modelling capabilities of optimization can help them to identify what is the best way of demand fulfilment when the weakest link in their supply chain breaks. Also, modelling multiple scenarios can help organizations identify their weakest links.
Facilitator: Dr. Amit Garg, Founder and CEO, ORMAE
Frontline Systems Topic: Unleashing Cost Savings Through Business Optimization
This Roundtable will focus on applications of optimization that yield measurable cost savings – an outcome that businesses always want to achieve, but that often becomes urgent in case of a recession or industry slowdown.
Besides identifying common applications, found across industries, where cost savings can be realized via optimization, we’ll discuss the kinds of companies and people who are good prospects for an optimization solution. Wherever possible, we’ll aim for concrete use cases and demonstrations, not just abstract ideas, for how we can help customers achieve their goals.
We’ll start with the view that optimization provides better ways to allocate scarce resources to specific uses to reach business goals, subject to a range of constraints. The resources may be money, raw materials, inventory, warehouse space, production time and space, vehicle and equipment time, and often people time. Businesses seek to apply resources to achieve goals – for example meeting demand from customers – doing so at lowest cost. Optimization “shines” when there are far too many possible combinations of resource assignments to “figure out manually”, so an automated method is needed.
Some classic examples we can discuss in this Roundtable include:
But not all businesses are equally good candidates for a cost-saving optimization model. Large businesses can very often benefit from a small percentage cost savings, because that percentage is applied to millions or even billions of dollars of cost. But for many small businesses where costs are measured in thousands of dollars, the savings achievable from optimization may not justify the cost of software and the user / analyst time and effort to build and test the model. Businesses also vary in their ability to pull together the data needed to drive the optimization model, on a timely basis.
This Roundtable will also seek to address that last problem: How to lower the user / analyst time and effort required to build and test an optimization model, thereby enlarging the available market. We can discuss pre-packaged application solutions and pre-designed models, the use of spreadsheets, high-level modeling languages, and high-level programming language and Internet APIs to lower time and cost. We can also discuss user training programs, the role of higher education, software “wizards”, and modern generative AI tools to speed and simplify the task of building and testing optimization models.
Facilitator: Daniel Fylstra, Founder and CEO, Frontline Systems
In this session, we will share insights and lessons learned from helping Gurobi customers from a wide range of industries adjust their optimization models to improve solver performance and numerical behavior. We will look at the challenges that we see most often in LP, MIP and MINLP models, and discuss our approach and typical recommendations to help address them. We will also consider some well-known modeling “rules of thumb” and discuss how applicable they are in 2024.
Join us for an engaging and dynamic Q&A session to close out the event! Moderated by Sonja, our VP of Support, this session will feature a panel of experts ready to address your questions, offering an informal opportunity to explore event topics in more depth.
An invited panel of experts will discuss strategies and experiences getting buy-in for optimization projects. Analytics professionals and projects maximize their impact when they get the right support. Panelists will discuss strategies for communicating the impact and value of optimization projects, generating excitement, and getting buy-in from leadership and business stakeholders.
Development and Experts team members will meet with you to discuss your most pressing pain points.
Our Journey Mapping sessions are for those just getting started with Optimization or are looking for advice on their path to greater adoption of Optimization within their organization. Schedule when registering for the Summit.
Explore new dimensions of decision intelligence within the context of innovative analytics at the expanding frontier of emerging digital technologies, including the exploding Internet of Things (IoT) market. Business examples and applications will be presented, focused on creating business value “at the intelligent edge” from ubiquitous data sources. Specifically, IoT data sources provide rich context (i.e., contextual variables) that enable greater insights into outcomes and optimizations of business processes, operations, and systems. Specific analytics strategies will be presented, going beyond predictive and prescriptive analytics (i.e., traditional forecasting and optimization) into novel analytics techniques for data science / AI innovators, business incubators, and startups (i.e., datapreneurs). These novel techniques include: sentinel analytics, precursor analytics, and cognitive analytics, aimed at delivering mission-critical Insights-as-a-Service (IaaS) to rocket-boost your organization’s forecasting and optimization (Decision Intelligence) capabilities to new heights. As a matter of fact, I am a rocket scientist.
What is the business value of optimized decisions that don’t touch the real world? The path to delivering useful solutions in operational environments is well trod, but not always smooth. While decision optimization technology plays a critical role in driving cost savings in industries worldwide, there are tremendous — and often overlooked — gains to be had in streamlining the infrastructure, tooling, and collaboration workflows that increase the efficiency of operationalizing said technology. Similar to how the DevOps movement ignited a transformation in software development tools and practices, DecisionOps promises to not only simplify the process of shipping optimization models to production, but also scaling and accelerating model development with confidence and buy-in from stakeholders to ultimately derive more value out of optimization investments.
In the competitive landscape of manufacturing, the continuous improvement of processes is vital for maintaining an edge. This presentation delves into the intricacies of optimizing a drug manufacturing process through the lens of baking a cake. We will explore the trade-offs between different objective functions, the challenges of adoption, and the importance of a tangible and actionable solution. By employing advanced optimization models, we have demonstrated a 13% increase in throughput, in addition to massive time savings and error reduction. Join us as we showcase the transformative power of optimization in manufacturing, where strategic planning meets innovative technology to create a streamlined, cost-effective production process.
In this session we will showcase how ABC Supply’s Dispatch Advisor tool utilizes sophisticated optimization techniques to tackle the challenges of truck routing and load optimization. By combining cutting-edge algorithms with real-world applicability, we simplify the creation of daily outbound schedules and enhance both decision-making and operational efficiency. We’ll explore how our tool automates the identification of cost-effective loading and routing strategies, leading to reduced transportation costs and faster scheduling. Attendees will gain valuable insights into how these technologies can solve complex logistics problems and drive significant improvements in supply chain management.
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Gurobi Summit Americas 2024
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