Subject to

Francisco Saldanha da Gama is professor of Operations Research in the Department of Statistics and Operations Research at the Faculty of Science, University of Lisbon, Portugal. He has a large teaching experience both in terms of undergraduate and post-graduate programs focusing on the fields of Operations Research, Mathematical Programming, Discrete Optimization, Stochastic Optimization, Logistics, and Operations Management. Has published extensively in scientific international journals mostly in the areas of supply chain management, logistics, location analysis, project scheduling, and discrete optimization. He has co-edited the two editions of the volume “Location Science” published by Springer International Publishing. Presented above 150 contributed talks in scientific events and has been invited to innumerable scientific events as a plenary/semi-plenary/keynote speaker. Has been awarded several prizes and honors such as the EURO prize for the best EJOR review paper (2012) and the Elsevier prize for the EJOR top cited article 2007–2011 (2012). He has been member of innumerable scientific committees of international conferences and other scientific events. He is member of several international scientific organizations and institutions such as INFORMS, CMAFcIO—Centro de Matemática Aplicações Fundamentais e Investigação Operacional, University of Lisbon, ECCO—European Chapter on Combinatorial Optimization, EWGSO Working Group on Stochastic Optimization, SOLA—INFORMS Section on Location Analysis), and EWGLA—EURO Working Group on Locational Analysis, of which he is one of the past coordinators. Currently he is Editor-in-Chief of Computers & Operations Research as well as member of the Editorial Advisory Board of the Journal of the Operational Research Society (UK) and Operations Research Perspectives. His research interests include supply chain management, logistics, decision-making under uncertainty, project scheduling and management.

Greet Vanden Berghe holds a degree in Metallurgy and Materials Engineering (KU Leuven). She has always been interested in mathematical modelling which led her in the direction of pursuing combinatorial optimization research. Her PhD focused on scheduling and particularly on developing a general model for personnel rostering that would be applicable across a wide range of health care organizations. This subject provided the perfect opportunity to initiate cooperation with the University of Nottingham, where she spent a one-year research stay. In 2002, she obtained a PhD in Engineering Science (Ghent University). Greet Vanden Berghe was appointed as professor at KU Leuven, Department of Computer Science in October 2014. She is currently a member of research unit NUMA (Numerical Analysis and Applied Mathematics) and leads the CODeS research group located at KU Leuven-Gent. Operational research represents Greet Vanden Berghe's primary research interest. Within the broad domain of operational research she focuses on complex combinatorial optimization problems. Examples of such problems include personnel scheduling, vehicle routing and all sorts of logistic operations. Her fundamental research activities involve mathematical modelling and the development of intelligent search algorithms such as heuristics and decomposition methods. She has successfully developed many heuristic decomposition algorithms, smart ways of tightening objectives or relaxing constraints, heuristics based on lower and upper bounding, and general-purpose local search operators. These new algorithm components have helped achieve the best computational results in several international competitions and benchmarking challenges. When studying industrial combinatorial optimization problems, especially their complicated constraints and objectives, Greet Vanden Berghe's team experienced that theory almost always falls short when it comes to efectively solving real-world problems. These insights led to the development of completely new yet highly efficient models and algorithms for industrial problems. Interestingly, developments for industrial-scale optimization problems often result in new theoretical insights given the inevitable need to simplify reality when modelling. Indeed, these new modelling methodologies are competitive with and often better than state-of-the-art algorithms focused on theoretical problems. CODeS provides benchmarks for various international challenges involving problems  such as pickup and delivery, vehicle routing and sports timetabling. Greet Vanden Berghe cooperates with industry within many applied research projects (supported by VLAIO or by the companies themselves). These projects target the internal use of optimization algorithms for real-world applications. Implementations of these algorithms are often deployed in more generally applicable decision support systems.

Ricardo Fukasawa is a Professor at the Department of Combinatorics and Optimization at the University of Waterloo. He did his undergraduate and Masters in Electrical Engineering at PUC-Rio in Brazil. He worked at GAPSO Inc from 2000-2003. He then did a PhD in the Algorithms, Combinatorics and Optimization program at GeorgiaTech. He was a recipient of the IBM Herman Goldstine Postdoctoral fellowship from 2008-2009, and moved to Waterloo afterwards. He received the Early Researcher Award from the Ontario Ministry of Research and Innovation. He is an Associate editor of Operations Research, OR Letters, RAIRO-OR and INFOR: Information Systems and Operational Research, and a Technical Editor for Mathematical Programming Computation. He has publications in several prestigious international journals like Mathematical Programming, Math of OR, INFORMS Journal on Computing, Mathematical Programming Computation and Transportation Science. His research interests are in developing theory and computational tools for the exact solution of hard discrete optimization problems, as well as their applications in practical problems. He has contributions in several areas, including Integer Programming, Vehicle Routing, Stochastic Programming, Bilevel Programming, as well as several applications.

Martin Savelsbergh is a logistics and optimization specialist with over 30 years of experience in mathematical modeling, operations research, optimization methods, algorithm design, performance analysis, transport, supply chain management, and production planning. He has published over 200 research papers in many of the top operations research and optimization journals and has supervised more than 30 Ph.D. students. Martin has a track record of creating innovative techniques for solving large-scale optimization problems in a variety of areas, ranging from service network design, to last-mile and crowdsourced delivery, to ridesharing. He has demonstrated an ability to design and implement highly sophisticated and effective optimization algorithms as well as an ability to analyze practical decision problems and translate the insights obtained into optimal business solutions. Martin is an INFORMS fellow and he was the James C. Edenfield Chair in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Institute of Technology until he retired in 2021. Martin is past Editor-in-Chief of Transportation Science, one of the most prestigious academic journals in the area of transportation science and logistics.

Pooja Dewan is the Vice President and Chief Data Analytics Officer for Otis Elevator Company. She is responsible for driving the data and analytics vision, strategy, and execution. In this critical role, she leads the company’s data science and analytics capabilities, identifying opportunities to accelerate growth and efficiency. She also owns the Otis data management roadmap driving sustainable business growth and profitability, as well as internal efficiencies through improved access to through data architecture, constant data cleanliness and insight, and efficient data governance and processes. Prior to this role, Pooja spent more than 20 years at BNSF Railway where she served as the Chief Data Scientist. There she led the Operations Research and Advanced Analytics group for 17 years. Her team received international recognition through an INFORMS award as the Best Advanced Analytics Team in 2019. Pooja has been a member of INFORMS (Operations Research Society) since 1993. During this time, she led several initiatives offered by INFORMS, including the Chairing of Edelman competition the prized Practice Award, various officer roles for Practice and Railway Section including being the President. In addition to her role for Practice and Railway section she has also been instrumental in championing activities that help bridge the gap between academia and real-world application and is currently serving on several Advisory Boards. Pooja earned a master's and doctorate in industrial engineering from Pennsylvania State University. She is also the author of several research publications in various scientific journals.

Ramayya Krishnan is the W. W. Cooper and Ruth F. Cooper Professor of Management Science and Information Systems at the H. John Heinz III College of Information Systems and Public Policy and the Department of Engineering and Public Policy at Carnegie Mellon University. He joined the CMU faculty in 1988. He is the Founding Dean of the Heinz College of Information Systems and Public Policy and has held that position since 2009. Krishnan’s education spans engineering, operations research, statistics and computing (the data sciences). He studied Mechanical Engineering at the Indian Institute of Technology and then went on to complete a M.S. in Industrial Engineering and Operations Research at the Cockrell School of Engineering and a PhD in Management Science and Information Systems at the McCombs School of Business, both at the University of Texas at Austin. A distinctive feature of his work has been deep partnerships with firms and government agencies and the pursuit of work that has made foundational contributions to science while making a real-world impact. His multi-disciplinary research program has involved faculty and students, undergraduate and graduate, from nearly all the Colleges and Schools at the university. He has been a serial academic entrepreneur and established multiple, externally funded, university-wide research centers at CMU. He founded the Master of Information Systems Management program in 1998 and is currently leading the creation and launch of new undergraduate programs at the nexus of systems thinking, information systems, and data analytics. His scholarly contributions to Operations Research, Information Systems, and analytics, and his editorial and leadership activities resulted in his being elected an AAAS Fellow, an INFORMS Fellow, and a fellow of the National Academy of Public Administration. He has been deeply engaged in policy work both at home and abroad. He led the CMU Task Force supporting Gov. Wolf in economic recovery and reopening in 2020-2021. In 2022, he was appointed to the National AI advisory committee which is charged with advising the President and the White House National AI Initiatives Office. He is a recipient of the distinguished alumnus award of the Indian Institute of Technology, Madras and the University of Texas at Austin. He served as the 25th President of INFORMS, the global operations research and analytics society, in 2019 and a three year term on its executive committee from 2017-2020.

Jeff Linderoth is the Harvey D. Spangler Professor in the department of Industrial and Systems Engineering at the University of Wisconsin-Madison. He holds a courtesy appointment in the Computer Sciences department and as a Discovery Fellow at the Wisconsin Institutes of Discovery. His research interests include optimization, integer programming, mixed integer nonlinear programming and stochastic optimization. His awards include an Early Career Award from the Department of Energy, the SIAM Activity Group on Optimization Prize, and the INFORMS Computing Society Prize. In 2016, Jeff was elected to membership as an INFORMS Fellow. He  acted as Associate Editor for highly important OR journals such as Operations Research, INFORMS Journal on Computing and Computational Optimization and Applications. He also acted as consultant for more than 10 companies and supervised 11 PhD dissertations.

Phebe Vayanos is Professor of Industrial & Systems Engineering and Computer Science at the University of Southern California, and an Associate Director of the Center for Artificial Intelligence in Society.  Prior to joining USC, she was a lecturer in the Operations Research and Statistics Group at the MIT Sloan School of Management, and a postdoctoral research associate in the Operations Research Center at MIT. She holds a PhD degree in Operations Research and an MEng degree in Electrical & Electronic Engineering, both from Imperial College London. Through her research, she aims to advance integer, stochastic, and robust optimization, and their interface with machine learning, causal inference, and economics to enable the design of predictive and prescriptive models that are robust, interpretable, and fair, being suitable to deploy in high-stakes settings. In particular, she aims to directly apply the methods and tools she creates in her work to make a positive impact on society, especially supporting undeserved and marginalized communities. She is the recipient of the NSF CAREER award and the USC Viterbi Junior Research Award and, jointly with her students, she earned the INFORMS Diversity, Equity, and Inclusion Ambassador Program Award. Since 2019, Phebe is serving as a member of the ad hoc INFORMS AI Strategy Advisory Committee. She is an elected member of the Committee on Stochastic Programming, which is the governing body of the Stochastic Programming Society. Phebe is also the VP of Communications for the Section on Public Sector OR at INFORMS. In addition, she is an Associate Editor for Computational Management Science and for Operations Research Letters.

Andrés Medaglia is full professor of Industrial Engineering at Universidad de los Andes (Bogotá, Colombia) and director of the research center Centro para la Optimización y Probabilidad Aplicada (COPA). He holds a Ph.D. (2001) in Operations Research (OR) from North Carolina State University (USA). From 1999 to 2002 he worked as an optimization specialist developing decision support systems for SAS (Cary, NC, USA). In 2002, he joined the Industrial Engineering Department at Universidad de los Andes and served as Department Chair from 2014 to 2017. He has more than 20 years of experience designing, developing, and applying optimization methodologies to transportation and logistics, healthy and sustainable cities, engineering design, and agricultural systems. His research has led to over 70 peer-reviewed publications in operational research (OR).  He currently serves in the editorial boards of Transportation Science, Computers and Operations Research, the European Journal of Industrial Engineering, and TOP (journal of the Spanish OR and Statistics Society). He has served as Secretary and Vicepresident of the Latin-Ibero American Association of Operations Research (ALIO); as Vicepresident of Central/South America for the Institute of Industrial and Systems Engineers (IISE); and as Vicepresident of the Colombian Operational Research Society (ASOCIO). In INFORMS, he currently serves in the Publications Committee. He has been the recipient of several awards, most recently, the Glover-Klingman Prize (2020), the INFORMS/TSL President’s Service Award (2017), the IFORS Prize for OR in Development (Quebec City, Canada, 2017), and the EURO Award for the Best EJOR (Review) Paper in 2015. He was the IFORS Invited Tutorial Lecturer at EURO 2018 (Valencia, Spain); and keynote speaker at the IISE Annual Conference and Expo (2021), the International Conference on OR for Development (ICORD 2016) (México DF, Mexico), Optimization Days (Montréal, Canada, 2014), and the NSF - Pan-American Advanced Studies Institute (PASI) on Modeling, Simulation and Optimization of Globalized Physical Distribution Systems (Santiago, Chile, 2013). As an avid amateur cyclist, he has won bronze, silver, and gold medals in the (Colombian) individual time trial championships at the masters category. More information at: http://wwwprof.uniandes.edu.co/~amedagli.

Kate Smith-Miles is a Melbourne Laureate Professor of Applied Mathematics in the School of Mathematics and Statistics at The University of Melbourne, and Director of the ARC Industrial Transformation Training Centre for Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). She is also Associate Dean (Enterprise and Innovation) for the Faculty of Science at The University of Melbourne.  

Prior to joining The University of Melbourne in September 2017, she was Professor of Applied Mathematics at Monash University,  Head of the School of Mathematical Sciences (2009-2014), and inaugural Director of the Monash Academy for Cross & Interdisciplinary Mathematical Applications (MAXIMA) from 2013-2017. Previous roles include President of the Australian Mathematical Society (2016-2018), and membership of the Australian Research Council College of Experts (2017-2019).  

Kate obtained a B.Sc(Hons) in Mathematics and a Ph.D. in Electrical Engineering, both from The University of Melbourne. Commencing her academic career in 1996, she has published 2 books on neural networks and data mining, and over 280 refereed journal and international conference papers in the areas of neural networks, optimisation, data mining, and various applied mathematics topics. She has supervised 30 PhD students to completion, and has been awarded over AUD$20 million in competitive grants, including 13 Australian Research Council grants and industry awards. She was awarded a Georgina Sweet Australian Laureate Fellowship from the Australian Research Council (2014-2020), enabling her Instance Space Analysis methodology to be expanded into an online tool (MATILDA, Melbourne Algorithm Test Instance Library with Data Analytics).  

Kate was elected a Fellow of the Australian Academy of Science in 2022, a Fellow of the Institute of Engineers Australia (FIEAust) in 2006, and a Fellow of the Australian Mathematical Society (FAustMS) in 2008. Awards include: the Australian Mathematical Society Medal in 2010 for distinguished research; the EO Tuck Medal from ANZIAM in 2017 for outstanding research and distinguished service; the Ren Potts Medal for outstanding research in the theory and practice of operations research from the Australian Society for Operations Research (ASOR) in 2019; and the Monash University Vice-Chancellor’s Award for Excellence in Postgraduate Supervision in 2012.  

In addition to her academic activities, she also regularly act as a consultant to industry in the areas of optimisation, data mining, and intelligent systems. She is also actively involved in mentoring, particularly with the aim of encouraging greater female participation in mathematics, and she chairs the Advisory Board for the AMSI Choose Maths program.