About

Ignacio Grossmann is the R. R. Dean University Professor in the Department of Chemical Engineering at Carnegie Mellon University and a former department head. He obtained his B.S. degree at the Universidad Iberoamericana in Mexico City in 1974, followed by an M.S. and Ph.D. at Imperial College in 1975 and 1977, respectively. His main research interests include discrete continuous optimization, optimal synthesis and planning of chemical processes and energy systems, and supply chain optimization. Grossmann has authored over 700 papers, several monographs, and textbooks such as 'Advanced Optimization in Process Systems Engineering' and 'Systematic Methods of Chemical Process Design.' He is a member of the National Academy of Engineering and has received numerous awards from AIChE, including the Computing in Chemical Engineering award, the William H. Walker award, and the Founders Award for Outstanding Contributions to the Field of Chemical Engineering. Grossmann has also been recognized internationally with honorary doctorates from multiple universities and was the first recipient of the Sargent Medal by IChemE in 2015. His contributions extend to industrial collaborations, including leading the Center for Advanced Process Decision-making, and he is ranked among the top cited scientists in computer science and electronics.

Research topics

• Computer Science
• Mathematics
• Algorithm
• Theoretical computer science
• Engineering
• Programming language
• Mathematical optimization
• Artificial Intelligence
• Industrial engineering
• Software engineering

Selected publications

• Integrated Optimization of Layout and Cable Routing for Wind Farms: From MINLP to MIQCP Formulation and Bilevel Decomposition Method

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• A novel algorithm for bounding the optimal solutions in multi-time scale decarbonization planning problems involving varying energy prices: electrification of oil refineries as a casestudy

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• A Logic-Based Decomposition for the Global Optimization of the Multiperiod Blending Problem Using Symmetry-Breaking Cuts

  Industrial & Engineering Chemistry Research · 2026-02-09

  articleOpen accessSenior author
  PublisherDOI

• Integrated investment, retrofit and abandonment energy system planning with multi-timescale uncertainty using stabilised adaptive Benders decomposition

  European Journal of Operational Research · 2025-04-11 · 4 citations

  articleOpen access
  PublisherOA PDFDOI

• Optimal Retrofit of Carbon Capture and Electrification Technologies in Oil Refineries for Reducing Direct CO₂ Emissions

  Industrial & Engineering Chemistry Research · 2025-05-11 · 7 citations

  articleOpen access

  The chemical industry is making significant investments in clean energy technologies, such as green hydrogen, carbon capture and storage, electric heating, and electrochemical processes to reduce carbon emissions. However, uncertainties regarding investments in recent technologies, fluctuating electricity and carbon prices, and the need to balance existing infrastructure with new ones complicate the transition. In this study, we develop a mixed-integer linear programming formulation to determine the most cost-effective transition for the decarbonization of oil refineries, incorporating electrification for steam generation, green hydrogen production, or carbon capture for blue hydrogen production and other emission sources. Two case studies that consider different refinery configurations are presented. Overall, the results of our simulations indicate that (i) natural gas with carbon capture is more economically favorable than electricity-based options, unless there are significant reductions in electricity prices or stricter emission regulations are imposed; (ii) carbon taxes or credits drive earlier adoption of capture technologies but do not promote electrification.

  PublisherDOI

• 50 years of mixed-integer nonlinear and disjunctive programming

  European Journal of Operational Research · 2025-07-18 · 3 citations

  articleOpen accessSenior author
  PublisherDOI

• Multiscale analysis through the use of biomass residues and CO2 towards energetic security at country scale via methane production

  Systems and Control Transactions · 2025-06-30

  articleOpen accessSenior author

  The growing demand for sustainable energy has driven research into renewable methane production to reduce greenhouse gas emissions and reliance on fossil fuels. Promising feedstocks include lignocellulosic dry residues, wet waste, and captured CO2, converted via gasification, anaerobic digestion, and synthetic processes with renewable hydrogen. This study uses a multiscale approach to compare these sources, incorporating a techno-economic evaluation to identify key performance indicators (KPI) for facilities and renewable energy sources. A facility location pro- blem (FLP) determines plant locations and production capacities, considering material availability and transportation costs. The analysis focuses on the decentralised use of wastes and CO2 from point and diluted sources across Spain, employing an MILP model to optimise waste and CO2 utilisation alongside solar and wind energy systems. Results highlight lignocellulosic dry waste and CO2 captured with MEA from point sources as the most promising options. Sensitivity analysis predicts methane prices between 13.028 �/MWh and 47.216 �/MWh through 2050, requiring substantial investment for full methane self-sufficiency. With carbon taxes, the price could drop to 10.735 �/MWh by 2050, competitive with current natural gas prices.

  PublisherOA PDFDOI

• GRAPSE: Graph-Based Retrieval Augmentation for Process Systems Engineering

  Systems and Control Transactions · 2025-06-30

  articleOpen accessSenior author

  Large Language Models have demonstrated potential in accelerating scientific discovery, but they face challenges when making inferences in rapidly evolving and niche domains like Process Systems Engineering (PSE). To address this, we propose a Graph-based Retrieval-Augmented Generation (RAG) pipeline specifically designed for PSE papers. Our pipeline includes custom document parsing, knowledge graph construction, and refinement to enhance retrieval accuracy. We evaluate the effectiveness of our approach using an automatically generated benchmark consisting entirely of PSE-related questions. The results show that our pipeline outperforms both non-RAG and vanilla RAG implementations in terms of relevant document retrieval and overall answer quality. Additionally, our implementation is fully customizable, allowing users to select the papers most relevant to their specific tasks. This framework is openly available, providing a flexible solution for those working in PSE or similar domains.

  PublisherOA PDFDOI

• Modeling, Simulation, and Optimization in the Chemical Engineering Curriculum

  2025-02-08

  book-chapterSenior author

  In this chapter, a brief history of the development of the chemical engineering curriculum is presented in seven phases to highlight the major drivers towards the current status of the discipline. Finally, the structure of the book is summarized in a table that shows the examples covered in the book and the packages used to solve them.

  PublisherDOI

• Pareto optimal solutions for decarbonization of oil refineries under different electricity grid decarbonization scenarios

  Systems and Control Transactions · 2025-06-30

  articleOpen access

  In response to global efforts to reduce carbon emissions, the oil refining sector, a major source of industrial emissions, has set ambitious decarbonization targets. This study analyzes trade-offs between minimizing CO2 emissions and costs through the use of Pareto optimal solutions. A superstructure optimization framework evaluates various technological pathways and timelines, employing a bi-criterion optimization approach using the ?-constraint method. Results show that cost-effective, higher-emission solutions often involve natural gas-based technologies with carbon capture, while expensive, low-emission solutions favor electric power-based technologies. The analysis incorporates detailed assumptions about grid carbon intensity of varying degrees and accounts for varying national policies. Comparative case studies across locations highlight how grid carbon profiles influence optimal strategies, providing insights to inform local policies and incentivize technologies.

  PublisherOA PDFDOI

Recent grants

• GOALI: Multiscale Decomposition Techniques for the Integration of Optimal Planning and Scheduling of Batch and Continuous Multiproduct Process Systems

  NSF · $278k · 2006–2010

• GOALI: Multi-scale Optimization for the Design, Capacity Planning and Operation of Power Intensive Process Networks under Uncertain Electricity Prices and Market Demands

  NSF · $302k · 2012–2016

• Advanced Computational Models for Multistage Stochastic Optimization of Process Systems with Renewable Resources

  NSF · $272k · 2005–2009

• GOALI: Optimal Design and Operation of Reliable Process Systems

  NSF · $352k · 2017–2021

• Open Cyberinfrastructure for Mixed-integer Nonlinear Programming: Collaboration and Deployment via Virtual Environments

  NSF · $1.2M · 2008–2013

Frequent coauthors

• Mariano Martı́n

  66 shared

• José A. Caballero

  57 shared

• Pedro M. Castro

  50 shared

• Zdravko Kravanja

  38 shared

• José M. Pinto

  38 shared

• John M. Wassick

  36 shared

• Iiro Harjunkoski

  Hitachi (Germany)

  32 shared

• Diego C. Cafaro

  31 shared

Education

• B.S., Chemical Engineering

  Universidad Iberoamericana

  1974

• M.S., Chemical Engineering

  Imperial College, University of London

  1975

• Ph.D., Chemical Engineering

  Imperial College, University of London

  1977

Awards & honors

• William H. Walker Award for Excellence in Publications
• Warren Lewis Award for Excellence in Education
• Research Excellence in Sustainable Engineering
• Founders Award for Outstanding Contributions to the Field of…
• John M. Prausnitz AIChE Institute Lecturer