Find Academic Supervisors

• Operations Research
• Stochastic Optimization
• Energy Systems Modeling
• +7 more

Francisco Alberto Campos Fernández is a Research Associate Professor at the Institute for Technological Research (IIT) and a professor in the Department of Industrial Organization at the School of Engineering (ICAI) of Comillas Pontifical University. Accredited by ANECA and ACAP for all teaching roles, he holds three six-year research terms in operations research. His work bridges theoretical optimization methods with practical energy market applications, focusing on electricity and emerging hydrogen markets. He earned his degree in Mathematical Sciences from Complutense University of Madrid (1999) with specialization in Operations Research, followed by a PhD in Industrial Engineering from Pontifical Comillas University (2006). His research spans mathematical optimization techniques applied to energy systems, with particular expertise in stochastic optimization, market equilibrium modeling, and integration of renewable resources. Recent work has increasingly focused on hydrogen markets, distributed generation, and energy communities, reflecting the evolving energy transition landscape. Analysis of his publication record reveals a clear evolution from foundational work in optimization theory and electricity market modeling toward increasingly complex multi-market integration problems. His recent publications demonstrate a strategic shift toward addressing the challenges of hydrogen-electricity market coupling, renewable integration, and distributed energy resources. This progression reflects both his theoretical depth in operations research and his practical understanding of evolving energy systems. Director of prizewinning work in Chair of Hydrogen Studies Prize for the best Final Master Project 2021-22 Director of prizewinning work in Iberdrola Prize for the best Final Year Project 2017-18 Director of prizewinning work in Iberdrola Prize for the best Final Year Project 2016-17 Fellowship Mobility stays abroad José Castillejo Professor Campos Fernández has supervised multiple PhD students and master's theses, with several currently in progress. His extensive project portfolio includes 91 research projects, primarily conducted for Endesa and other energy companies, focusing on market modeling, strategic analysis, and optimization tools for power system planning. The CODEX project series represents his most sustained research effort, evolving over more than a decade to address increasingly complex energy system challenges. He maintains active collaborations with international research institutions and has served on the Management Committee of the COST Action TD1207 from 2013-2024. As a core member of the IIT research team, he contributes to the institute's mission of developing advanced analytical tools for the energy sector. His work sits at the intersection of theoretical operations research and practical energy market applications, with significant contributions to modeling frameworks used by industry partners. The integration of his research with teaching activities ensures that students benefit from cutting-edge industry-relevant knowledge.

• Liquefied Natural Gas Supply Chains
• Mixed-Integer Linear Programming
• Optimization Modeling
• +2 more

Alice Bittante is affiliated with the Faculty of Natural Sciences and Technology, focusing on computational optimization and energy systems research. She actively contributes to academic publications in the field of liquefied natural gas supply chain modeling. Liquefied Natural Gas Supply Chains Mixed-Integer Linear Programming Computational Time Optimization Sustainable Energy Infrastructure Development Her research centers on mathematical modeling of energy logistics networks, particularly LNG supply chains in the Baltic Sea region. Key areas include: Multi-period optimization frameworks Sea-land transport integration Small-scale LNG distribution systems Cost-efficiency analysis with environmental constraints Computational modeling of energy networks Scenario-based infrastructure planning Between 2014-2018, she published six peer-reviewed works, including five journal articles and one conference proceedings, primarily focused on optimization techniques applied to sustainable energy systems. Her collaborative research with F. Pettersson and H. Saxén demonstrates strong interdisciplinary connections.

• Sustainable Energy Systems
• Mathematical Optimization
• Industrial Process Engineering
• +3 more

Frank Pettersson is a Senior Lecturer at the Faculty of Natural Sciences and Engineering, Department of Process and Systems Engineering, Åbo Akademi University. His research aligns with UN Sustainable Development Goals (SDGs), focusing on sustainable energy systems and industrial process optimization through mathematical modeling. Expertise Areas: Mathematical Optimization, Hydrogen-Based Steelmaking, Biogas Digestate Recycling, Energy Storage Systems, Gas Distribution Networks, Blast Furnace Efficiency His recent work analyzes hydrogen transition in steel plants, water scarcity in power sectors, and nutrient recycling in biogas systems. Key methodologies include Mixed-Integer Linear Programming (MILP) and systems engineering approaches. Academic supervision spans Energy Technology diploma theses (2013–2017) and ongoing Master’s student mentorship (2025). While no specific scientific awards are listed, his publications demonstrate impact in sustainable industrial solutions and energy systems.

Jordi Domingo-PascualView profile

Professor

• 5G Network Architecture
• Software-Defined Networking (SDN)
• Locator/Identifier Separation Protocol (LISP)
• +10 more

Jordi Domingo-Pascual is a Full Professor at the Universitat Politècnica de Catalunya - BarcelonaTech (UPC), affiliated with the Department of Computer Architecture within the Faculty of Informatics of Barcelona (FIB). He is a member of the UPC CBA - Broadband Communications Systems and the IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Group. His research spans networking, telecommunications, and ethical aspects of technology design. Research Interests: His primary areas of expertise include 5G network architectures, software-defined networking (SDN), Locator/Identifier Separation Protocol (LISP), traffic engineering, quality of service (QoS), network monitoring, and ethics in engineering education. He investigates both technical and societal dimensions of emerging network technologies. Publication Trends: His recent scholarly output (2020–2022) emphasizes SDN controller placement optimization, open-source traffic engineering tools, and the integration of ethical considerations in engineering curricula—particularly in the context of AI and pandemic-era digital tracing applications. Earlier works focus on ATM multicasting, QoS, and broadband network characterization. Scientific Awards: Premi o reconeixement Advising and Grants: While specific advisees are not listed, his extensive research activity—including participation in European projects—suggests involvement in supervising students and securing competitive R&D funding. His work on traffic engineering, SDN, and LISP indicates leadership in national and international collaborative grants. Labs and Research Groups: He is actively involved in the UPC CBA research group focused on broadband and communication systems and the IDEAI-UPC group advancing data science and AI. These affiliations reflect a strong interdisciplinary research profile bridging networking and intelligent systems.

Purushothaman DamodaranView profile

Professor

• Industrial Engineering
• Systems Engineering
• Operations Research
• +7 more

Purushothaman Damodaran is a Presidential Teaching Professor at the Department of Industrial and Systems Engineering at Northern Illinois University . With expertise in large-scale optimization , logistics , simulation , scheduling , Lean Manufacturing , and Six Sigma , he develops mixed-integer linear formulations and novel algorithms for real-world applications in electronics manufacturing, healthcare, and logistics. Ph.D. , Industrial Engineering, Texas A&M University (2002) M.S. , Industrial Engineering, Northern Illinois University (1997) B.E. , Mechanical Engineering, University of Madras (1994) His research focuses on optimization models for batch processing machines , parallel machine scheduling , and simulation-based decision support systems . He has collaborated with industries like 3M , Caterpillar , Royal Caribbean Cruise Lines , and IBM , addressing challenges in manufacturing systems , warehouse design , and service operations . Recent publications highlight heuristic approaches (e.g., GRASP , Simulated Annealing , Particle Swarm Optimization ) for flow shop scheduling , job shop optimization , and material slitting problems . His work often integrates Lean Six Sigma principles and simulation-optimization for real-time manufacturing improvements . Scientific Awards : Best Paper Award, IISE Annual Conference (2021) National Science Foundation Grant (2008-2009) for server manufacturing research As a faculty teaching mentor at NIU, he teaches undergraduate and graduate courses in Six Sigma , Warehousing , and Advanced Lean Manufacturing , emphasizing real-life projects and student engagement .

• Game Theory
• Operations Research
• Mathematical Economics
• +3 more

Julio González-Díaz is a university professor at the Department of Statistics, Mathematical Analysis, and Optimization at the Faculty of Mathematics, University of Santiago de Compostela. His research focuses on game theory, operations research, and decision models, with applications in economics and mathematics. He leads the research group MODESTYA (Optimization, Decision, Statistical Models and Applications) and is affiliated with the Galician Mathematical Research and Technology Center (CITMAga). Education: PhD from the University of Santiago de Compostela (2005), thesis titled Essays on Competition and Cooperation in Game Theoretical Models , supervised by Dr. María Estela Sánchez Rodríguez and Dr. Ignacio García Jurado. Research Interests: Game theory (cooperative and non-cooperative), operations research, optimization, and statistical models. His work includes studies on core stability, airport cost allocation, paired comparisons analysis, and algorithmic game theory. Publications: Over 30 peer-reviewed articles and books, including influential works like An Introductory Course on Mathematical Game Theory (2010) and widely cited contributions on core-center concepts and ranking methods. Recent work involves polynomial optimization algorithms (RAPOSa solver), gas transportation networks, and bilevel portfolio design. Collaborations: Extensive co-authorship network, including researchers like Fiestras-Janeiro, Sánchez-Rodríguez, and international collaborations in optimization and game theory. Contact: julio.gonzalez@usc.es

Fabian BastinView profile

Professor

• Operations Research
• Optimization
• Stochastic Programming
• +4 more

Fabian Bastin is a Full Professor in the Department of Computer Science and Operational Research (IRO) at Université de Montréal. He holds a prestigious academic position within the university's research and teaching community. His work focuses on optimization, stochastic programming, simulation, and their applications in transportation, energy systems, and finance. Teaching Responsibilities: Bastin teaches advanced courses such as IFT-2505 (Linear Optimization), IFT-3515 (Nonlinear Programming), and IFT-6512 (Stochastic Programming). He also contributes to graduate-level courses on dynamic programming and simulation techniques. His courses emphasize theoretical foundations alongside practical applications, often using tools like MATLAB and the ORATIO library he helped develop. Research Interests: Bastin's research spans stochastic optimization, simulation methodologies, and decision-making under uncertainty. Key areas include air traffic management optimization, hydroelectric reservoir scheduling, and synthetic population generation using copula-based models. He has pioneered work on scenario tree generation for multistage stochastic programming and developed algorithms for efficient mixed logit model estimation. Research Contributions: His publications highlight advancements in stochastic models for transportation systems, energy planning, and financial engineering. Notable works include contributions to the progressive hedging algorithm, recursive logit models for route choice analysis, and Monte Carlo methods for option pricing. Bastin is also actively involved in software development, notably the ORATIO simulation library used in discrete-event modeling. Professional Engagements: He has co-organized conferences on optimization and simulation, and his work has been supported by grants from NSERC and other funding bodies. Despite no explicit mention of awards in the text, his extensive publication record and methodological innovations suggest significant recognition in his field.

Peter ZhangView profile

Assistant Professor

• Optimization Theory
• Supply Chain Management
• Transportation Systems
• +3 more

Peter Zhang is an Assistant Professor at Carnegie Mellon University's Heinz College of Information Systems and Public Policy, with a courtesy appointment in Civil and Environmental Engineering. He holds a PhD in Engineering Systems from MIT (2019), an MASc in Mechanical and Industrial Engineering from the University of Toronto (2013), and a BASc in Engineering Science from the same university (2011). His research focuses on optimization theory, applied to supply chains, transportation systems, health, and socio-technical systems. He emphasizes robust optimization, dynamic and bilevel problems, and their applications in policy design and high-stakes decision-making. Education PhD in Engineering Systems, MIT (2019) MASc in Mechanical and Industrial Engineering, University of Toronto (2013) BASc in Engineering Science, University of Toronto (2011) Research Interests Robust optimization and its applications Transportation safety and last-mile delivery systems Supply chain resilience and policy design Machine learning integration with optimization Awards & Recognition INFORMS Koopman Prize (2020) First Place, INFORMS Junior Faculty Forum (2022) Ford Engineering Excellence Award (2015) INFORMS Daniel H. Wagner Prize (2014) Advising & Mentorship Supervised PhD students including Hao Hao and Guanting Wu, with postdoctoral mentorship for Ningji Wei and Alberto Japón Sáez. Research teams have participated in datasets like the U.S. Household Commuting Dataset and NASA’s Blue Skies Competition. Labs & Collaborations Collaborates on transportation fairness, hydrogen aviation decarbonization, and school bus optimization through interdisciplinary projects involving data science and policy analysis.

• Operations Research
• Robust Optimization
• Queueing Theory
• +7 more

Chaithanya Bandi is an Associate Professor at the National University of Singapore (NUS) in the Analytics and Operations Department of the NUS Business School, with a joint appointment in the Department of Mathematics. His research focuses on decision-making under uncertainty, robust optimization, and their applications in operations management, healthcare, e-commerce, and energy systems. He develops robust optimization models for queueing control, risk optimization, and mechanism design. Key research areas include robust queue inference, two-stage distributionally robust optimization, and multi-item auction mechanisms. He has contributed to operational challenges in healthcare (e.g., patient re-entry scheduling), energy systems (electricity generation optimization), and e-commerce (price optimization for fashion products). His work integrates theoretical advancements with practical implementations in large-scale systems. Recent publications emphasize adversarial evaluation of large language models, dynamic scheduling algorithms, and robust policies for uncertain environments. His methodologies often involve novel optimization frameworks and scalable computational approaches. Dr. Bandi holds a PhD in Operations Research and has collaborated with industry leaders like Flipkart and healthcare providers to apply his models in real-world settings. His contributions bridge theoretical rigor and practical applicability in complex operational systems.

Moritz DiehlView profile

Professor

• Optimization
• Control Systems
• Embedded Systems
• +3 more

Prof. Moritz Diehl is a Professor at the University of Freiburg, leading the Systems Control and Optimization Laboratory within the Department of Microsystems Engineering (IMTEK) and affiliated with the Department of Mathematics. Born in Hamburg, Germany, he holds a Ph.D. from Heidelberg University (2001) and previously served as a professor at KU Leuven (2006–2013), where he directed the Optimization in Engineering Center (OPTEC). His research focuses on optimization and control, emphasizing numerical methods for engineering applications, particularly embedded systems and renewable energy. Key areas include model predictive control (MPC), nonlinear optimization, and real-time control systems. Education: He studied physics and mathematics at Heidelberg University and the University of Cambridge (1993–1999), culminating in a Ph.D. in Scientific Computing. His academic journey includes roles at KU Leuven and Freiburg, where he has developed influential tools like the AWEbox framework for airborne wind energy systems and the acados optimization library. Research Interests: His work spans numerical optimal control, MPC algorithms, and their applications in robotics, energy systems, and automotive engineering. Recent advancements include collision-free motion planning, real-time NMPC with convex-concave constraints, and stochastic control methods for mobile robots. He also explores optimization for hybrid systems, leveraging finite elements and switch detection for nonsmooth dynamics. Publications: His 2023–2025 work highlights contributions to MPC stability, energy-efficient control systems, and software tools like LCQPow for quadratic programming. His research bridges theory and practice, addressing challenges in industrial processes, renewable energy integration, and autonomous systems. Labs & Teams: He leads the Systems Control and Optimization Lab, fostering interdisciplinary projects in optimal control, robotics, and sustainable energy. His group collaborates on tools like acados, emphasizing real-time feasibility and scalability for complex systems.

William CookView profile

Professor

• Combinatorial Optimization
• Operations Research
• Discrete Mathematics
• +5 more

William Cook is a University Professor in the Department of Combinatorics and Optimization at the University of Waterloo. His research focuses on combinatorial optimization, computational discrete optimization, and the traveling salesman problem (TSP). He is renowned for co-developing the Concorde TSP Solver , a leading software for solving TSP instances. Cook has held editorial roles in top journals such as Mathematical Programming Computation and Mathematical Programming , and served as Chair of the Mathematical Optimization Society and Vice Chair of INFORMS Computing Society. His research interests include algorithm design, operations research, graph theory, and computational methods for NP-hard problems. Notable contributions include advancing cutting-plane methods, branch-and-bound algorithms, and hybrid optimization techniques. Cook has authored influential books like In Pursuit of the Traveling Salesman and The Traveling Salesman Problem: A Computational Study . Awards include membership in the National Academy of Engineering, SIAM Fellowship, INFORMS Fellowship, and the $100,000 Amazon Last Mile Routing Research Challenge prize (2021). He has advised numerous projects in computational optimization, including studies on deep learning applications and combinatorial algorithm development. His work bridges theoretical advancements with practical software tools like QSopt and QSopt_ex .

Rolf FagerbergView profile

Professor

• Algorithms
• Data Structures
• Computational Biology
• +7 more

Rolf Fagerberg is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU). His research centers on algorithms, data structures, and their applications in computational biology and cheminformatics. His research interests include: Algorithms and data structures, particularly dynamic and geometric data structures Graph theory with emphasis on subgraphs, Yao graphs, and hypergraphs Algorithmic cheminformatics and modeling of chemical reaction networks Computational biology, including metabolic pathway analysis Theoretical computer science and discrete mathematics Recent publications highlight a strong trend toward interdisciplinary research combining computer science with chemistry and biology, particularly in modeling chemical reaction networks using hypergraphs and mixed-integer linear programming. His work also includes algorithmic solutions for palindromic subsequence problems and efficient extraction of reaction rules from large databases, reflecting a blend of theoretical and applied algorithm design. Rolf Fagerberg has served as senior coordinator on multiple research projects, including 'Algorithmic Cheminformatics' and 'Fundamental Data Structures', funded by the Danish Ministry of Higher Education and Research. He has also contributed to peer review and editorial work for major conferences such as the ACM Symposium on Parallelism in Algorithms and Architectures and the International Symposium on Experimental Algorithms. He has supervised PhD students and is actively involved in academic service, including membership in assessment committees at Aarhus University and IT University of Copenhagen. His research has received media attention, including coverage of a 'mathematical breakthrough' and applications in understanding intestinal systems in obesity.

• Combinatorial Optimization
• Quadratic Programming
• Binary Optimization
• +5 more

Cédric Elloumi is a Professor at the CEDRIC Laboratory within Conservatoire National des Arts et Métiers (CNAM), specializing in combinatorial optimization and mathematical programming. With a continuous publication record since 1992, he has established himself as a leading researcher in quadratic programming, binary optimization, and facility location problems. His research interests focus on developing exact and approximate methods for discrete optimization problems, particularly through convex reformulation techniques. Elloumi has made significant contributions to the p-center and p-median problems, quadratic assignment problems, and more recently, quantum-inspired optimization methods. His work bridges theoretical advancements with practical applications in network design, energy systems, and telecommunications. Analysis of his recent publications (2022-2025) reveals a continued focus on facility location problems, with increasing attention to robust optimization under uncertainty and emerging applications in quantum computing. His research demonstrates consistent methodological innovation, particularly in reformulation techniques that transform difficult non-convex problems into tractable forms. Throughout his career, Elloumi has maintained extensive collaborations with researchers including Billionnet, Lambert, Alès, and Plateau, resulting in numerous publications in top-tier optimization journals such as Journal of Global Optimization, Computers and Operations Research, and Mathematical Programming.

Yossi BukchinView profile

Professor

• Assembly systems design
• Assembly line balancing
• Facility design
• +5 more

Prof. Yossi Bukchin is a Professor in the Department of Industrial Engineering at The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University. His research focuses on manufacturing systems, production engineering, and operations research with particular expertise in assembly line design and optimization. His primary research interests include: Assembly systems design Assembly line balancing Facility design Operational scheduling Human factors engineering Warehouse and storage systems Prof. Bukchin's recent work demonstrates a strong focus on puzzle-based storage systems, assembly line optimization, and operations management. His research spans both theoretical developments in scheduling algorithms and practical applications in manufacturing and logistics systems. He has made significant contributions to the understanding of Bucket Brigade systems, puzzle-based storage optimization, and assembly line balancing with mixed-model production. His scholarly output shows evolution from early work on robotic assembly lines to contemporary research on machine learning applications in warehouse systems and advanced optimization techniques for modern manufacturing challenges. Contact information: Email: bukchin@tau.ac.il Phone: 03-6407941 Fax: 03-6407669 Office: Wolfson - Engineering

Keely CroxtonView profile

Professor

• Supply Chain Management
• Supply Chain Resilience
• Facility Location
• +4 more

Keely Croxton serves as Professor of Logistics in the Department of Marketing and Logistics at The Ohio State University's Max M. Fisher College of Business. Her academic leadership spans undergraduate, MBA, PhD, and Executive Education programs where she teaches supply chain management, forecasting, modeling, and Social Impact courses. Dr. Croxton holds a PhD from the Massachusetts Institute of Technology and a BS from Northwestern University. Prior to academia, she gained industry experience in automotive, paper and packaging, and third-party logistics sectors. Her research centers on supply chain resilience, developing frameworks to balance vulnerabilities with management capabilities during disruptions. Specialized interests include facility location, demand management, relationship management, and supply chain integration. Her work demonstrates consistent focus on process-oriented approaches to supply chain challenges, particularly examining how firms respond to operational disruptions through strategic adaptation and relationship capital. Analysis of her publication history reveals strong emphasis on supply chain risk mitigation (60% of recent works), with significant contributions to supplier portfolio management, resilience assessment tools, and big data integration challenges. Her research consistently bridges theoretical frameworks with practical industry applications, often developed through collaborations with organizations like OSU's National Center for the Middle Market. Bernard J. LaLonde Best Paper Award (Journal of Business Logistics, 2005) Finalist for Bernard J. LaLonde Best Paper Award (Journal of Business Logistics, 2010) Research grant funding from OSU’s National Center for the Middle Market (2013) Dr. Croxton serves on the advisory board for OSU’s Global Water Initiative and has developed influential frameworks for supply chain management processes. Her industry background informs practical teaching approaches across multiple degree programs, including specialized courses like Contemporary Issues in Supply Chain Management (BUSOBA 7392) and Strategic Supply Chain Management (BUSML 7391).