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Virtual Technical Training

You are invited to join us at Gurobi Days Digital Academic, which will be taking place on August 26, 2025.

Theme: Gen AI & Optimization

Explore the cutting edge where Generative AI meets Mathematical Optimization. Join leading researchers, students, and academics from around the world for a day of discovery, innovation, and insight.

This year’s free 1-day event for academic and commercial users will feature some great sessions:

Time (ET) Title Speaker(s) Description
9:45 AM Gurobi Welcome, Academic Program Introduction & Event Kickoff Gurobi Team Join us as we kick off Gurobi Days Digital Academic with a warm welcome and an overview of the event. We’ll introduce Gurobi’s Academic Program, highlight key opportunities for students and researchers, and preview what’s ahead in our lineup of talks and panels. This session sets the stage for an engaging day focused on optimization, education, and innovation.
10:00 AM Panel Discussion: Leveraging GenAI for Optimization Education and Research in 2025 Dr. Laura Albert, Prof. Naser Nikandish Generative AI (GenAI) is transforming how we teach and research optimization. This panel explores how tools like large language models and code generators are being used in 2025 to enhance modeling, accelerate discovery, and support curriculum design. Panelists will share practical insights from academia and industry while addressing challenges such as accuracy, reproducibility, and responsible use. Join us for a forward-looking discussion on the evolving role of GenAI in optimization education and research.
11:00 AM A Front Row Seat on the AI Revolution Dr. Yuri Balasanov & Dr. Mike Watson Over the last 12+ years, both Mike and Yuri were lucky enough to be part of companies implementing and using the latest AI (or Machine Learning) while teaching these topics at the University of Chicago and Northwestern. In this back-and-forth talk, they are going to cover lessons from the early days to the trends we see going forward. We’ll also cover the role of OR and optimization. Yuri comes to the field from the finance industry and Mike from supply chain and operations. They both now teach a class on what this all means for managers. And they don’t always agree with each other!
12:00 PM Explaining Optimization Problems Using Large Language Models Dr. Can Li This talk will provide an overview of recent advances in large language models (LLMs) and their applications in operations research, including leveraging LLMs to generate and formulate optimization models and develop novel optimization algorithms. A particular focus will be on using LLMs to enhance the interpretability of optimization models for practitioners. One of the key challenges in deploying optimization models is ensuring that practitioners can effectively understand and interpret their results. To address this, we have developed OptiChat, a software platform designed to assist users by diagnosing infeasibilities, conducting sensitivity analyses, generating counterfactual explanations, and responding to general queries. OptiChat has been rigorously tested on a diverse dataset of optimization-related queries. The talk will conclude with a discussion on both the opportunities and limitations of applying LLMs in optimization.
1:00 PM Cracking the Vault with Gurobot: Generative AI and the Future of Mathematical Modeling Dr. Steven Edwards Discover how Gurobi is exploring the use of generative AI to support and streamline the modeling of mathematical optimization problems. Through the lens of a hands-on museum heist challenge, we’ll walk through examples of AI-assisted modeling across varying levels of complexity. We’ll highlight current capabilities, acknowledge present limitations, and offer a glimpse into where we’re headed next as we expand the role of AI in the modeling workflow.

Bonus: This interactive example also illustrates how our Generative AI tools can inspire engaging, classroom-ready optimization challenges for educators and students alike.

 

Don’t miss this special virtual event! Registrations are opening soon – keep an eye on our LinkedIn page for updates!

Meet the Experts

View Bio

Dr. Can Li

Assistant Professor
Purdue University

Dr. Can Li

Assistant Professor
Purdue University

Can obtained his bachelor’s degree from Tsinghua University, China, in Chemical Engineering. He completed his PhD in Chemical Engineering at Carnegie Mellon University. His PhD research is focused on stochastic mixed-integer nonlinear programming and long-term expansion planning of power systems. Can did a one-year Postdoc at Polytechnique Montreal on using machine learning techniques to accelerate optimization algorithms. He joined the Davidson School of Chemical Engineering at Purdue University as an assistant professor in the Fall of 2022. His research group is focused on optimization, machine learning, and applications in sustainable energy systems. His group won Air Liquide’s global scientific challenge on data sharing for decarbonization in 2023 and the Amazon Research Award in 2024.

View Bio

Dr. Michael Watson

Associate Professor of Instruction
Northwestern University

Dr. Michael Watson

Associate Professor of Instruction
Northwestern University

He was the co-founder and CEO of Opex Analytics, an AI firm that grew from 0 to 140 data scientists from 2013 to 2019.  Their clients included many Fortune 500 companies.  In 2019, it was acquired by LLamasoft and by Coupa in 2020. At Coupa, he led the AI Center of Excellence until December 2021. He is now a full-time faculty member at Northwestern University in the Department of Industrial Engineering.  He teaches master’s and undergraduate level courses in Supply Chain, Operations Excellence, Managerial Analytics, and Optimization.  He also runs a capstone course where students do projects for companies. He has a Ph.D. from Northwestern, is the lead author of the books “Supply Chain Network Design” and “Managerial Analytics,” and writes at https://MikeTalksAI.substack.com/.

View Bio

Dr. Yuri Balasanov

Professor of Instruction
Northwestern University

Dr. Yuri Balasanov

Professor of Instruction
Northwestern University

Yuri Balasanov, Ph.D. is Professor of Instruction and Deputy Director of the MS in Machine Learning and Data Science (MLDS) program at the McCormick School of Engineering, Northwestern University. He earned his M.S. in Applied Mathematics and Ph.D. in Probability Theory and Mathematical Statistics from Lomonosov Moscow State University, where he studied under Andrey Kolmogorov and other prominent members of his school. His expertise spans stochastic modeling, advanced data analysis and AI, digital transformation, risk evaluation, and decision-making under uncertainty. Dr. Balasanov has over 20 years of experience in the financial industry, where he has served as a data scientist, lead quantitative researcher, risk manager, and quantitative trader at major financial institutions. He was a member of the Advisory Committee for the U.S. Department of Energy–funded project, Developing a Deep Learning–Computer Vision Framework to Monitor Avian Interactions with Solar Energy Facility Infrastructure, and has advised several other industry initiatives. In parallel with his industry work, Professor Balasanov has more than 25 years of academic experience. As Deputy Director of the MLDS program, he leads industry engagement and teaches a wide range of courses including Data Science, Bayesian Decision Making, Financial Engineering, and Generative AI. He previously taught at the University of Chicago in the programs MS in Financial Mathematics (MSFM) and MS in Applied Data Science (hosted by Data Science Institute), where he also served as Curriculum Director. He has provided professional training to organizations such as the Federal Reserve Banks of Chicago and Philadelphia, PwC, and Chicago Trading Company.

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Dr. Laura Albert

Professor Industrial and Systems Engineering
University of Wisconsin-Madison

Dr. Laura Albert

Professor Industrial and Systems Engineering
University of Wisconsin-Madison

Laura Albert, Ph.D., is a Professor of Industrial & Systems Engineering at the University of Wisconsin-Madison and a thought leader in operations research and analytics. She served as the David H. Gustafson Department Chair from 2021-24 and the President of the Institute for Operations Research and the Management Sciences (INFORMS) in 2023. Dr. Albert’s research focuses on mitigating risks in the public sector through optimization and operations research methodologies, with applications in critical infrastructure protection, public safety, and emergency response. She is a Fellow of both the American Association for the Advancement of Science (AAAS) and the Institute of Industrial and Systems Engineers (IISE). Her work has been recognized with numerous accolades, including the INFORMS Impact Prize, a National Science Foundation CAREER award, and a Fulbright Award. An advocate for public engagement, Dr. Albert has penned several op-eds for national news outlets, and she authors the engineering blogs “Punk Rock Operations Research” and “Badger Bracketology.” 

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Dr. Steven Edwards

Product Manager
Gurobi Optimization

Dr. Steven Edwards

Product Manager
Gurobi Optimization

Dr. Steven Edwards completed his PhD at Monash University in the field of discrete optimization. His thesis was motivated by the scheduling of automated pathology testing systems used for the diagnosis of cancers and infectious diseases. As part of his research, he developed a modeling framework for efficiently solving large-scale optimization problems using constraint programming inspired by existing techniques in boolean satisfiability and mixed-integer programming. After completing his thesis, Steven worked briefly at the Australian Bureau of Statistics on optimization problems in data security before commencing as a Research Fellow in Operations Research at the University of Melbourne. 

View Bio

Lindsay Montanari

Senior Director of Academic Programs
Gurobi Optimization

Lindsay Montanari

Senior Director of Academic Programs
Gurobi Optimization

Lindsay brings over 13 years of experience working at the intersection of technology and education. Prior to Gurobi, Lindsay worked as an Operations leader at Opex Analytics, a product and services firm dedicated to solving complex business problems using the power of Artificial Intelligence. While there, she focused on growth and business development, product launch, and marketing. Lindsay spent 10 years working in various leadership capacities at Universities including Columbia University, Northwestern University, and the University of Chicago. From 2013 to 2017, she worked to establish and grow the Master of Science in Analytics degree at Northwestern University’s School of Engineering, the program was one of the earliest MS degrees focused on an applied data science curriculum. During her time with Northwestern, she managed external relations and corporate relations, helped hire and onboard new faculty and subject-matter experts in various disciplines of analytics, directed recruiting efforts/admissions/student advising, and managed a team of administrative professionals. Prior to Northwestern, she spent over 5 years working in Advancement at Columbia University’s School of Engineering and Applied Science.   She completed her Bachelor’s Degree in English and Fine Art at Sewanee: The University of the South and her Master’s Degree in Nonprofit Management at Columbia University.

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