Mixed-integer Nonlinear Programming (MINLP) Professors and Supervisors in United States

Jeff LinderothView profile

Professor

University of South CarolinaUnited States

Jeff Linderoth is the Harvey D. Spangler Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research focuses on large-scale numerical optimization, mixed-integer nonlinear programming, and stochastic programming, with applications in energy systems, global routing, and industrial processes. Education: BS in General Engineering (highest honors) from University of Illinois at Urbana-Champaign, MS in Operations Research from Georgia Institute of Technology, PhD in Industrial Engineering from Georgia Institute of Technology. Linderoth's work addresses theoretical and applied challenges in optimization, including developing algorithms for mixed-integer programming, analyzing knapsack polytopes, and creating tools like the Minotaur optimization toolkit. His recent publications explore integer programming techniques for subspace clustering, complementarity constraints, and customized coverage instrumentation. Selected trends in his research include advancements in stochastic programming, orbital branching for symmetric integer programs, and congestion analysis in power systems. His group contributes to optimization software and data-driven libraries like MIPLIB. Scientific Award: Harvey D. Spangler Professor.

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Devon SiglerView profile

Researcher

National Renewable Energy LaboratoryUnited States

Devon Sigler is a Researcher IV in Applied Mathematics and Computational Science at the National Renewable Energy Laboratory (NREL). His expertise lies in optimization, with a focus on mixed integer optimization, convex optimization, and stochastic optimization. He applies these techniques to complex energy systems, leveraging decomposition methods and high-performance computing (HPC) to solve large-scale problems in parallel. PhD in Mathematics (University of Colorado Denver) Master in Applied Mathematics (University of Colorado Denver) Bachelor in Mathematics and Philosophy (University of Colorado Boulder) Devon has worked as a Postdoctoral Researcher at NREL (2016–2018) and as a Graduate Teaching Assistant at University of Colorado Denver (2013–2017). His research spans energy system planning under uncertainty, AC optimal power flow, and water distribution network optimization, contributing to 46 research outputs. Current projects include electrified rental car centers with behind-the-meter storage and advanced probability modeling for grid reliability.

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Juan RuizView profile

Lecturer

University of Texas at AustinUnited States

Juan Ruiz serves as a Lecturer in the Department of Chemical Engineering at the University of Texas at Austin, specializing in computational methods for complex process systems optimization. His work bridges theoretical mathematics with practical engineering applications in energy and chemical production systems. Educational Background: Ph.D., Chemical Engineering, Carnegie Mellon University (2011) B.S., Chemical Engineering, Universidad Tecnologia Nacional, Argentina (2003) Research Focus: Dr. Ruiz develops advanced optimization techniques for process systems engineering, with particular expertise in stochastic programming , generalized disjunctive programming , and global optimization algorithms . His research addresses critical challenges in energy dispatch systems and chemical process design through mathematically rigorous computational frameworks that enhance solution efficiency while maintaining theoretical soundness. Publication Trends: Analysis of his 2010-2013 publications reveals a concentrated research trajectory centered on strengthening relaxation methods for non-convex optimization problems. His work consistently appears in high-impact journals like Computers and Chemical Engineering and Applied Energy , demonstrating significant contributions to mathematical programming techniques applicable to power systems and chemical process networks. Scientific Recognition: Mark Dennis Karl Outstanding Graduate Teaching Award, Carnegie Mellon University (2008) Best National Engineering Graduates Award, Argentine National Academy of Engineering (2004) Argentine Chemistry Association Award, Argentine Chemistry Association (2004) Instructional Role: He teaches graduate-level courses including ChE 356/384 Optimization: Theory and Practice and ChE 381P Advanced Analysis for Chemical Engineers, where he integrates his research on computational optimization methods into advanced engineering education.

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Aida KhajaviradView profile

Assistant Professor

Lehigh UniversityUnited States

Aida Khajavirad is an Assistant Professor in the Department of Industrial and Systems Engineering at Lehigh University. Her research focuses on advancing Mixed-Integer Nonlinear Optimization (MINLP) at theoretical, algorithmic, and software levels, integrating convex analysis, integer programming, and constraint programming. She has recently expanded her work to optimization algorithms for data science and machine learning applications. Education: Ph.D. in Mechanical Engineering from Carnegie Mellon University (2012). Research Interests : Mixed Integer Nonlinear Optimization Nonconvex Optimization Algorithm Development Convex Analysis Combinatorial Optimization Her work emphasizes bridging theoretical foundations with practical algorithm design for real-world challenges. Awards : 2023 INFORMS Computing Society Prize This prestigious award recognizes her contributions to optimization theory and applications. Grants & Funding : Air Force Office of Scientific Research ($1M award, 2023) This funding supports her research on advanced optimization algorithms. Labs and Affiliations: Based in the Harold S. Mohler Laboratory, she leads interdisciplinary efforts in optimization and data science.

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Ignasi Palou-RiveraView profile

Adjunct Professor

Illinois Institute of TechnologyUnited States

Dr. Ignasi Palou-Rivera is an Adjunct Professor in the Department of Chemical and Biological Engineering at Illinois Institute of Technology's Armour College of Engineering. He serves as Executive Director and Chief Technology Officer of the RAPID Manufacturing Institute®, a DOE-funded initiative advancing modular chemical process intensification (MCPI). His career spans over 20 years in process development and optimization across industries including oil refining, biofuels, and sustainability analysis. Education includes a Ph.D. in Chemical Engineering from University of Wisconsin-Madison (1998), post-doctoral work at MIT (2001-2002), and a Chemical Engineering degree from Universitat Politècnica de Catalunya (1991). His work integrates computational tools with industrial applications, focusing on techno-economic analysis, lifecycle assessment, and refinery planning. Research interests emphasize sustainable manufacturing systems, process intensification technologies, and bridging innovation to commercialization. He leads RAPID's efforts to accelerate adoption of advanced chemical processing methods through public-private partnerships. His contributions include development of lifecycle analysis frameworks for biofuels and shale gas, as well as refinery optimization algorithms. Key publications span process intensification strategies, biofuel lifecycle assessments, and energy efficiency improvements. He holds patents related to bioreactor systems and wafer edge characterization. Professional service includes leadership roles in AIChE's Computing & Systems Technology Division and Sustainable Engineering Forum.

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Jean-Philippe RichardView profile

Professor

University of Minnesota Twin CitiesUnited States

Jean-Philippe (JP) Richard is Professor of Industrial and Systems Engineering at the University of Minnesota, Twin Cities, and concurrently serves as Director of Faculty and Academic Affairs for the department. From 2018 onward he has held these roles, having previously been Professor (and PhD coordinator) at the University of Florida (2008-2018) and Assistant/Associate Professor at Purdue University (2002-2008). Education Ph.D. in Algorithms, Combinatorics, and Optimization, Georgia Institute of Technology, 2002 Bachelor of Engineering in Applied Mathematics, Université Catholique de Louvain, 1998 Research Interests Dr. Richard works at the intersection of theory and computation for mixed-integer linear and nonlinear optimization . His methodological focus spans convexification techniques , polyhedral approaches , lifting and cutting-plane methods , and global optimization algorithms . He translates these advances into impactful applications in data analytics , healthcare (radiation therapy & surgery scheduling) , railroad logistics , and infrastructure protection . Scientific Awards & Honors University of Florida Term Professorship (2017–2019) IIE Transactions Best Application Paper Award (2008) NSF CAREER Award (2004) Sigma Xi Best Ph.D. Thesis Award, Georgia Tech (2003) Russell J. Penrose ISyE Excellence in Teaching Award (2023) Grants & Funding Leadership Richard has been PI or co-PI on more than ten NSF awards totaling over $2 million, including recent grants on network interdiction, complementarity constraints, and opioid-policy analytics. Industry partnerships with Union Pacific Railroad and CSX Transportation have funded applied projects exceeding $150,000. Student Mentorship & Lab Culture He has (co-)advised 19 PhD dissertations and numerous Master’s and undergraduate researchers. Current advisees include Bouchra Er-Rabbany and Chengwenjian Wang; recent graduates hold positions at Google, ExxonMobil, Bayer, and leading universities worldwide. His group emphasizes rigorous theory coupled with real-world impact.

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Evrim DalkiranView profile

Associate Professor

Wayne State UniversityUnited States

Dr. Evrim Dalkiran is an Associate Professor in the Department of Industrial and Systems Engineering at Wayne State University's College of Engineering. She holds a Ph.D. in Industrial and Systems Engineering from Virginia Tech (2011), and B.S./M.S. from Bogazici University (2003, 2006). Her work focuses on global optimization and decision analysis with applications in healthcare operations and supply chain management. B.S., Industrial Engineering, Bogazici University, Turkey M.S., Industrial Engineering, Bogazici University, Turkey Ph.D., Industrial and Systems Engineering, Virginia Tech Her research spans Global Optimization , Reformulation-Linearization Technique , Mixed-Integer Programming , and Multi-Objective Optimization , with application domains in Healthcare Operations , Emergency Patient Flow , Supply Chain Management , and Diabetes Risk Modeling . Current research includes real-time coordination tools for emergency departments and inverse optimization models. Her publications demonstrate expertise in polynomial programming , RLT implementations , and healthcare logistics , with recent work on automotive sustainability and smart grid allocation . Articles span journals like European Journal of Operational Research and Operations Research . Best Paper Award, Journal of Global Optimization, 2012 Outstanding Faculty Award, WSU, 2016 Pritsker Dissertation Award Finalist, 2012 IIE Student Paper Competition Advisor, multiple awards As faculty advisor, she mentors students in projects related to emergency department optimization and supply chain modeling . Her grant history includes multiple Veterans Administration projects on patient flow and Goodyear-funded supply chain optimization. She teaches advanced optimization courses and maintains professional affiliations with INFORMS and Mathematical Optimization Society.

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