Find Academic Supervisors

• Modeling of Electrical Generation and Transportation Systems
• Planning and Scheduling of Industrial Processes
• Methods and Timing of Operations (MTM)
• +7 more

Pedro Sánchez Martín is an Associate Professor in the Department of Industrial Organization at the School of Engineering, Comillas Pontifical University, where he has been a faculty member since January 1999. He is affiliated with the Institute for Technological Research (IIT) and holds a PhD in Industrial Engineering from the same institution, with additional research experience at the University of Texas at Austin. His research interests include: Modeling of Electrical Generation and Transportation Systems Planning and Scheduling of Industrial Processes Methods and Timing of Operations (MTM) Simulation of Manufacturing Processes and Logistics Supplies Operations Research and Optimization His recent publications focus on virtual power plants, electricity market bidding under uncertainty, stochastic programming, and integrated energy systems. These works appear in top journals such as IEEE Transactions on Power Systems, Energy, and Sustainable Energy, Grids and Networks, reflecting a strong trend toward robust optimization, renewable integration, and market design for sustainable energy systems. He has supervised several PhD students, including C.M. Correa-Posada and S. López, and currently mentors H. Nemati and M. Abideen. His research is supported by significant projects funded by the European Commission (e.g., POSYTYF, TWENTIES), Spanish ministries (MICIU/AEI), and industry partners such as Iberdrola, Enagás, and Repsol. He has organized scientific events like the European Energy Market Conference (EEM10) and delivered invited seminars on simulation techniques. He also participates in thesis committees and research evaluations at Comillas and other institutions.

• Energy Systems Modeling
• Optimization
• Generation Expansion Planning
• +2 more

Sonja Wogrin is an Associate Professor in the Department of Industrial Organization at the Higher Technical School of Engineering, Pontifical University of Comillas. She holds a Ph.D. in Electricity Markets from the Instituto de Investigación Tecnológica (IIT) at the same university and has been a researcher there since 2009. Her work focuses on decision support systems for energy systems, optimization techniques, and generation capacity expansion planning. Education: B.Sc. in Technical Mathematics (Graz University), M.Sc. in Computation for Design and Optimization (MIT), Ph.D. in Electricity Markets (IIT-Comillas) Affiliations: Researcher at IIT-Comillas, Associate Professor in Industrial Organization Her research interests include energy systems modeling , optimization (particularly bilevel programming ), and electricity storage . She has developed open-source tools like the LEGO model for low-carbon expansion and analyzed market feedback in transmission planning. Her work addresses technical constraints in generation commitment, inertia in low-carbon grids, and policy implications of renewable integration. Recent article trends show a focus on gas pipeline MILP modeling , thermal demand simulations , and convex optimization in imperfect markets . She emphasizes stochasticity , multi-objective frameworks , and GIS-based siting for renewables. Scientific awards include the Iberdrola Spain Research Grant , 4th EASE Student Award (Belgium), and multiple mobility grants from Erasmus and NILS. As an advisor, she has supervised four Ph.D. theses on transmission planning , European gas markets , and co-optimized storage . Her grants include EU-funded projects like STEXEM and hydrogen roadmap development for Colombia with the IDB. She collaborates with institutions such as MIT, Johns Hopkins, and NTNU through research stays and contributes to IEEE Transactions , Applied Energy , and European Journal of Operational Research as a reviewer.

• Operations Research
• Mathematical Programming
• Combinatorial Optimization
• +7 more

Jose Manuel Belenguer Ribera is a full-time Professor in the Department of Statistics and Operations Research at the University of Valencia. He is a member of the OPTIMATH research group, focusing on optimization and mathematical modelling. His academic career is centered on operations research and combinatorial optimization. His research interests include: Operations Research Mathematical Programming Combinatorial Optimization Vehicle Routing Problems Capacitated Arc Routing Logistics Optimization His publications span from 1990 to 2023, with a strong focus on exact and heuristic methods for routing and scheduling problems. Key contributions include branch-and-cut algorithms, cutting plane methods, and bounds for capacitated and mixed arc routing problems. His recent work extends into port logistics, particularly yard crane scheduling in container terminals. Notable collaborative work includes joint publications with Enrique Benavent, Christian Prins, and Caroline Prodhon. His research has been published in leading journals such as Computers & Operations Research , European Journal of Operational Research , and Operations Research . He earned his PhD from the University of Valencia in 1990 with a thesis on the polyhedron of capacitated arc routing problems, establishing a strong foundation in polyhedral combinatorics.

Julian PfeifleView profile

Associate Professor

• Combinatorics
• Discrete Geometry
• Polytopes
• +3 more

Julian Pfeifle is an Associate Professor in the Department of Mathematics at the Polytechnic University of Catalonia (UPC), affiliated with the Terrassa School of Industrial, Aerospace, and Audiovisual Engineering. He is part of the UPC's research group GAPCOMB (Geometric, Algebraic, and Probabilistic Combinatorics). His research focuses on combinatorics, discrete geometry, and algebraic structures, with particular emphasis on polytopes, graph theory, and geometric algorithms. Affiliations: Department of Mathematics, UPC; GAPCOMB Research Group. Education: Doctorate in Mathematics from UPC (thesis directed by G. M. Ziegler). His research interests span polytope theory, combinatorial geometry, algebraic combinatorics, and discrete optimization. Recent work includes studies on non-realizability certificates for polytopes, polynomial roots via Gale duality, and geometric constructions using the Cayley trick. He has contributed to projects funded by national and international grants, including the European Science Foundation's 'SDModels' initiative. Pfeifle has published extensively in top journals like Journal of Combinatorial Theory , Discrete & Computational Geometry , and Experimental Mathematics . His articles often explore polytopal structures, graph algorithms, and combinatorial topology. A notable award is the Richard Rado Preis (Ehrenvolle Anerkennung) for his doctoral thesis. He has advised doctoral students and contributed to research projects such as 'Geometric, Algebraic and Probabilistic Combinatorics' (AGRUPS-2023) and 'Combinatorics and Complexity of Discrete Geometric Structures' (MTM-funded). His work frequently intersects with computational geometry and combinatorial algorithms, with applications in optimization and discrete mathematics.

• Operations Research
• Mathematical Programming
• Optimization under Uncertainty
• +5 more

Consuelo Parreño Torres is a Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, University of Valencia, Spain. She holds a permanent academic position and is an active researcher in operations research and optimization, particularly in maritime logistics. University: University of Valencia School: Faculty of Mathematics Department: Department of Statistics and Operations Research Email: consuelo.parreno@uv.es She earned her PhD in 2020 with a thesis on improving container terminal efficiency through models and algorithms for pre-marshalling and stowage problems, supervised by Dr. Ramón Álvarez Valdés and Dr. Rubén Ruiz García. Her research focuses on operations research, mathematical programming, and combinatorial optimization , with specific applications in container terminal logistics . She develops advanced algorithmic solutions such as integer programming, constraint programming, and matheuristics to solve complex scheduling and optimization problems in port operations. Her work addresses real-world challenges like minimizing crane times and optimizing container rearrangement. Her recent publications, primarily in journals like European Journal of Operational Research and Computers & Operations Research , show a consistent trend in solving the pre-marshalling and stowage problems using exact and heuristic methods. These works reflect a deep engagement with computational optimization and algorithm design for dynamic logistical environments. Consuelo Parreño Torres is a member of the research group PROMEDyA (Prediction and Optimization under uncertainty: dynamic stochastic models and applications), which focuses on developing models for uncertain and dynamic systems. She collaborates extensively with researchers such as Ramón Álvarez-Valdés, Rubén Ruiz, and Celia Jiménez-Piqueras. While no formal students are listed, her collaborative work indicates a strong advisory and mentoring role within her research team. There is no mention of major grants or scientific awards in the provided text.

• Software Engineering
• Artificial Intelligence
• Scheduling Problems
• +3 more

María Isabel Alfonso Galipienso is a full-time University Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante, Spain, and a member of the University Institute of Computer Research (IU of Computer Research). She has held significant administrative roles, including Director of her department from 2012-2016 and Sub-director from 2005-2012. Education PhD in Computer Engineering, University of Alicante (2001) Graduate in Computer Science, Polytechnic University of Valencia (1991) Research Interests Her research spans Software Engineering , Artificial Intelligence , Constraint Satisfaction Problems , and Educational Technology . She focuses on developing scheduling algorithms, agile software processes, and innovative pedagogical approaches for teaching computer science and engineering courses, often integrating real-world projects and collaborative learning techniques. Across her publications and projects, a clear trend emerges toward bridging theoretical AI methods with practical software engineering education . Her early 2000s journal articles introduced hybrid CSP-based scheduling techniques, while later conference papers and books translated these insights into iterative, student-centered curricula and group-based learning frameworks. Scientific Awards No specific scientific awards or fellowships are recorded in the provided documents. Advising & Grants Directed or co-directed 1 undergraduate/master’s thesis in the last five years. Participated as collaborator in 8 competitive public research projects (2012-2016), funded by Spanish Ministries of Economy and Education, focusing on robotics, SLAM, and vision-based systems. Contributed to one technology-transfer project developing a research portal for accounting and business administration entities (2004-2005). Labs & Teams She is affiliated with the IU of Computer Research at the University of Alicante, collaborating in multidisciplinary teams that integrate robotics, computer vision, and educational innovation.

Natalia AlguacilView profile

Professor

• Power Systems
• Optimization
• Smart Grids
• +3 more

Natalia Alguacil is a Full Professor at the University of Castilla-La Mancha, affiliated with the Higher Technical School of Industrial Engineering in Ciudad Real, Spain. Her research focuses on power systems optimization, smart grid technologies, and renewable energy integration, with an emphasis on robustness, demand response mechanisms, and decentralized optimization frameworks. She has contributed significantly to topics such as transmission network expansion, energy storage systems, and electricity market design through advanced methodologies like bilevel programming and ADMM-based approaches. Her work addresses critical challenges in modern grid operation, including renewable integration uncertainties, fair prosumer incentives, and grid resilience. Key contributions include frameworks for optimal residential demand response coordination and robust scheduling under wind energy variability. Her research bridges theoretical advancements with practical implementation, influencing both academic discourse and industry practices. Natalia has authored over 40 peer-reviewed articles, many published in top journals like IEEE Transactions on Smart Grid and Power Systems. She has led projects on transmission tariff allocation, grid observability restoration, and defense planning against deliberate outages. Her educational efforts include pioneering problem-based learning curricula in engineering education.

• Combinatorics
• Discrete Geometry
• Computational Geometry
• +4 more

Julian Thoralf Pfeifle is a Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), affiliated with the School of Industrial, Aerospace and Audiovisual Engineering of Terrassa (ESEIAAT). He leads the GAPCOMB research group focused on Geometric, Algebraic and Probabilistic Combinatorics, and maintains strong connections with the Faculty of Mathematics and Statistics (FME). Dr. Pfeifle's research spans combinatorial geometry, polytope theory, and discrete structures with emphasis on the interplay between geometric configurations and algebraic methods. His work explores fundamental questions about realizability of combinatorial structures, symmetry in polytopes, and connections between graph theory and geometric representations. He employs both theoretical approaches and computational techniques to investigate lattice points in polytopes, Ehrhart polynomials, and triangulations of point configurations. Analysis of his recent publications reveals a sustained focus on Plücker relations, non-realizability certificates, and symmetry properties in polytopes. His research demonstrates consistent theoretical depth while maintaining connections to computational applications. The interdisciplinary nature of his work bridges pure combinatorics with practical computational geometry problems. Dr. Pfeifle has received the Richard Rado Preis, a significant recognition in combinatorial mathematics. His research has been supported by multiple competitive grants including projects under Spain's Plan Estatal de Investigación Científica. As an academic advisor, Dr. Pfeifle has supervised doctoral students including Dall, A. (Matroids: h-vectors, zonotopes, and Lawrence polytopes) and Padrol, A. (Neighborly and almost neighborly configurations, and their duals). He has also been involved in educational innovation projects such as the development of interactive learning tools for mathematics education and served on conference committees including FPSAC 2010. Leading the GAPCOMB research group, Dr. Pfeifle coordinates a collaborative team investigating the intersections of geometric, algebraic, and probabilistic approaches to combinatorial structures. The group's work continues to advance understanding of discrete mathematical objects and their applications across multiple domains.

Alfredo N. Marin PerezView profile

Professor

• Operations Research
• Location Problems
• Optimization
• +2 more

Alfredo N. Marin Perez is a Professor at the Department of Statistics and Operations Research, Faculty of Mathematics, University of Murcia. His research focuses on operations research, discrete location problems, hub network design, and optimization theory. He has extensively published on p-median problems, hub location models, and equity-based facility allocation. Research Areas: Facility Location, Game Theory, Mathematical Optimization Key Collaborations: Mercedes Landete, Antonio M. Rodriguez-Chia, Justo Puerto Albandoz Methodologies: Lagrangian Relaxation, Branch-and-Cut Algorithms, Polyhedral Analysis Selected Publications: His work includes foundational contributions to the tree of hubs problem, capacitated p-center models with failure foresight, and rank pricing optimization. Recent articles explore equity in location problems and multi-period stochastic covering models.

• Operational Research
• Machine Learning
• Logistics Optimization
• +3 more

Alberto Santini is an Assistant Professor (tenure-track) at the Department of Economics and Business at Universitat Pompeu Fabra (UPF), currently on leave while serving as a Marie Curie Post-Doctoral fellow at ESSEC Business School in Paris. He holds affiliate professor positions at the Data Science Centre of the Barcelona School of Economics, the Barcelona Graduate School of Mathematics, and CY Advanced Studies. His academic journey includes a PhD in Automation and Operational Research from the University of Bologna. His research focuses on Operational Research and Machine Learning, with specialization in combinatorial optimization problems, logistics systems, and algorithm design. Notable contributions include work on hazardous routing problems, energy-efficient farming systems, and optimization frameworks for pandemic resource allocation. He integrates methodologies such as column generation, heuristic algorithms, and stochastic modeling to address real-world challenges in transportation, healthcare, and agriculture. His publications span journals like Networks , Omega , and Computers and Operations Research , highlighting advancements in knapsack problems, vehicle routing, and adaptive search algorithms. His research portfolio reflects a balance between theoretical rigor and practical applications, addressing both industrial logistics and societal issues like sustainable farming and epidemic management. Alberto has contributed to interdisciplinary initiatives through affiliations with leading institutions in Barcelona and Paris, emphasizing collaborative research in data science and operations. His work bridges academic innovation with industry needs, particularly in optimizing complex systems under constraints.

• Model Predictive Control
• Water Resources Systems
• Intelligent Transportation Systems
• +5 more

Pau Segovia Castillo is a Research Fellow in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC) since September 2023, holding the prestigious Beatriz Galindo Fellowship. His research focuses on large-scale systems management using non-centralized predictive control approaches, with applications in water resources, transportation, and energy systems. He holds a joint PhD in Automatic Control from UPC and IMT Lille Douai (France), completed in 2019. Previously, he held postdoctoral positions at IMT Lille Douai (2019–2020), TU Delft (2020–2023), and UPC (2023). His educational background includes a BS/MS in Industrial Engineering from UPC (2015). He is a member of the Advanced Control Systrems (SAC) group within the CS2AC research center. His work emphasizes model predictive control (MPC), observer design for nonlinear systems, and digital twin technologies applied to waterway infrastructure. Notable contributions include multilayer control strategies for canals and coordinated scheduling for inland vessel navigation. Key research areas span fault diagnosis in hydraulic systems, optimization algorithms for transportation logistics, and sustainable energy production from waterways. His publications address topics like MPC-based digital twins, observer schemes for noisy nonlinear systems, and lock scheduling using max-plus linear systems. He currently supervises Javier Pedrosa Alias's PhD on job-shop scheduling with AI approaches. Awards: Beatriz Galindo Fellowship Labs/Teams: Advanced Control Systrems (SAC) group, CS2AC Research Center

• Power Systems
• Natural Gas Systems
• Energy Market Modeling
• +4 more

Luis Manuel Montero Guirao is a Research Assistant Professor at the Institute for Research in Technology (IIT) and a lecturer at the ICAI School of Engineering, both affiliated with Comillas Pontifical University. He holds a Ph.D. in Power Systems (2024), an M.Sc. in Chemical Engineering (2017), and a B.Sc. in Chemical Engineering (2015). Ph.D. in Power Systems, Comillas Pontifical University (2024) M.Sc. in Chemical Engineering, University of Salamanca (2017) B.Sc. in Chemical Engineering, University of Granada (2015) His research focuses on energy systems modeling, particularly in integrating operational details for power and natural gas systems in medium-term horizons. He specializes in optimization techniques, machine learning applications for competitive market asset management, and forecasting for energy markets. Recent publications analyze computational performance in unit commitment problems, novel formulations for start-up costs, and methodologies for feasible thermal operations. These works emphasize mathematical rigor, multi-area market dynamics, and integration of renewable energy sources. He has led 35+ industry-specific projects for companies like Endesa, Enel, and Enagas, focusing on Monte Carlo simulations, VALORE/SEIE model enhancements, and regulatory adaptations for energy markets.

Jordi Castro PerezView profile

Professor

• Mathematical Optimization
• Operations Research
• Interior Point Methods
• +1 more

Jordi Castro Perez is a Professor at the Department of Statistics and Operations Research within the Faculty of Mathematics and Statistics (FME) at Universitat Politècnica de Catalunya-BarcelonaTech . He leads the GNOM - Grup d'Optimització Numèrica i Modelització research group and contributes to the Institut de Matemàtiques de la UPC-BarcelonaTech . Expertise : Mathematical Optimization, Interior Point Methods, Operations Research, Data Privacy Research Focus : Dr. Castro develops specialized optimization techniques for complex problems in data privacy, machine learning, and large-scale stochastic programming. His recent work includes privacy-preserving dynamic data publishing, microaggregation algorithms, and efficient methods for support vector machines. Scientific Recognition : Spanish Society of Statistics and Operations Research – BBVA Foundation Awards 2024 Advising & Projects : He advised doctoral thesis by De La Lama Zubirán, Paula and leads the R&D project Modelización y Optimización de Problemas Estructurados y Aplicaciones , which includes collaborators like Heredia, Albareda-Sambola, and Gentile.

• Power Systems Planning
• Transmission Expansion Planning
• Renewable Energy Integration
• +5 more

Dr. Andrés Ramos Galán is a Full Professor at the Industrial Organization Department and Instituto de Investigación Tecnológica (IIT) of Comillas Pontifical University since 1984. His work spans power systems planning , renewable integration , and energy market modeling with a focus on stochastic optimization and Benders decomposition techniques. He has led 134 projects including DIAMOND (Horizon Europe) and ATMOSPHERE (green hydrogen modeling) and served as IIT Director (2020-2023) and MBA Director (2015-2020). His research bridges complex network analysis for grid topology and offshore wind farm layout optimization , with 21 supervised Ph.D. theses covering topics from hydrothermal scheduling to virtual power plants . Recent projects like OPEN_ENTRANCE and DEFINER address energy transition challenges. Key publications (2022-2025) demonstrate expertise in transmission expansion , storage valuation , and flexibility assessment , with a focus on Spanish and European systems. His 2025 work on CSR and grid resilience and 2023 Renewable & Sustainable Energy Reviews paper on flexibility visualization tools highlight practical applications. Students and collaborators include leading researchers in hydro modeling (S. Lumbreras), unit commitment (G. Morales-España), and network analysis (R. Espejo). Current projects involve hydrogen integration and renewable-dominated system optimization for 2030-2050 horizons.

ANGEL MANUEL GONZALEZ RUEDAView profile

Assistant Professor

• Optimization
• Operations Research
• Mathematical Modeling
• +3 more

Angel Manuel González Rueda is an Assistant Professor at the University of Santiago de Compostela (USC), affiliated with the Department of Statistics, Mathematical Analysis and Optimization, part of the Higher Technical School of Engineering. He is a member of the MODESTYA research group (Optimization, decision, statistical models and applications) and the Galician Mathematical Research and Technology Center (CITMAga). His research focuses on optimization algorithms, energy networks, and decision models, with notable work on gas transmission systems, home care scheduling, and polynomial optimization tools like RAPOSa. He holds a Doctorate from USC (2017), completing his thesis on Gas transmission networks optimization algorithms and cost allocation methodologies , supervised by Dr. Julio González Díaz. His expertise spans mathematical modeling, computational optimization, and game theory applications in energy and logistics systems. Key research trends in his articles include: (1) Development of hybrid optimization algorithms for differential equations and network problems, (2) Multiobjective scheduling in healthcare and retail logistics, and (3) Fair cost allocation mechanisms in energy and gas networks using cooperative game theory. His RAPOSa software has become a notable open-source tool for polynomial optimization. Rueda has contributed to over 15 peer-reviewed articles since 2014, addressing topics ranging from wildfire suppression modeling to decentralized energy markets. Though no formal awards are listed, his work demonstrates significant innovation in applied mathematical optimization. He has advised no doctoral students listed here but collaborates extensively with industry partners on network optimization challenges. His affiliations include the Interuniversity Research Center CITMAga, emphasizing applied mathematics in technology, and the MODESTYA group, which bridges theoretical optimization with real-world applications in engineering and economics.