Dick den Hertog is professor of Operations Research at University of Amsterdam. His research interests cover various fields in prescriptive analytics, in particular linear and nonlinear optimization. In recent years his main focus has been on robust optimization, and recently he started research on Optimization with Machine Learning. He is also active in applying the theory in real-life applications. In particular, he is interested in applications that contribute to a better society.
He received the INFORMS Franz Edelman Award twice: in 2013 for his research on optimal flood protection, and in 2021 for his research on optimizing the food supply chain for the UN World Food Programme. Currently, he is doing research to develop better optimization models and techniques for cancer treatment together with researchers from Harvard Medical School and Massachusetts General Hospital (Boston, USA), and he is involved in research to optimize the locations of health facilities in Timor-Leste and Vietnam together with the World Bank. He is associate editor of Operations Research, and INFORMS Journal on Optimization. Since 2019, he is Visiting Professor at MIT (Cambridge, USA).
Our society is facing many challenges. We believe that Analytics can be of much value to improve our world. It is encouraging to see that more and more (especially young) Analytics researchers are enthusiastic to use Analytics to make this world a better place. Analytics has already contributed significantly to, e.g., the Sustainable Development Goals of the United Nations.
To make these societal contributions of Analytics more visible, and to stimulate research in this area, Dimitris Bertsimas (MIT, Cambridge, USA) and Dick den Hertog have started a new initiative: “Analytics for a Better World (ABW)”.
Read more about Analytics for a Better World.
I consider supervising PhD candidates as the most important part of my scientific life. A significant part of my inspiration I receive from the PhD candidates who I (co-)supervise. Here is the list of these PhD candidates:
I am a PhD candidate at the University of Amsterdam. My research focuses on the optimization of investment decisions regarding the production and deployment of hydrogen, which is predicted to play an important role in the transition to a sustainable energy system. For such large and complex problems, there is much uncertainty regarding future developments in technology, economics, policymaking, etc. The main goal of this PhD project is to develop a robust optimization methodology for dealing with such uncertainties while optimizing long-term, large-scale energy system models.
I am Zihang Qiu, a PhD candidate at the University of Amsterdam. After obtaining my Master's degree in Physics at ETH Zürich, I am working on the EU-funded RAPTOR project to realize online treatment adaption for proton radiotherapy. My research focuses on the daily adaption of proton treatment plan to the patient's latest anatomy to minimize the uncertainty caused by the disagreement between the patient's treatment plan and their anatomy, using mathematical optimization and machine learning. I am carrying out my research project under the supervision of Professor Dick den Hertog (the University of Amsterdam) and Professor Thomas Bortfeld (Massachusetts General Hospital).
I am Parvathy Krishnan, a Data Science Consultant in the public sector working for organisations such as World Bank and UNDP to employ data science tools and techniques to accelerate the achievement of Sustainable Development Goals. I have a Bachelor of Technology in Electrical and Electronics Engineering, Master of Technology in Energy Management & Climate Change Technology and a Professional Doctorate in Engineering (PDEng.) in Data Science. Under the guidance of Prof Dick den Hertog and Prof. Joaquim Gromicho, I am pursuing a part-time PhD on Analytics for a Better World.
I am a PhD candidate at the University of Amsterdam, and I work on the ENW-Groot project OPTIMAL (Optimisation for and with Machine Learning). My research focuses on the investigation of different techniques to embed Deep Learning into optimisation models. The goal is to start from data and use predictive models to build part of the optimisation model, making it data-centric and easier to develop. The two main applications of this project are related to the World Food Programme and the Radiotherapy Optimization.
During my bachelor in AI and a master in Data Science, I developed a particular interest in the application of Machine Learning to approach optimal solutions to optimization problems. As I am now a PhD student at the University of Amsterdam and Sanquin Blood Supply, I am using both mathematical optimization and Machine Learning in order to improve Sanquin's blood supply chain and the issuing of blood products to patients.
My name is Meike Reusken and I am a PhD candidate at the Zero Hunger Lab at Tilburg University. Here we use data science for food security. Before joining the Zero Hunger Lab, I obtained a Master’s degree in Economics at Erasmus University and a Master’s degree in Econometrics at Tilburg University. For my research, I am collaborating with the World Food Programme and the Dutch Food Bank. I aspire to improve their processes using (robust) optimisation techniques, with combating hunger as the main focus.
I am a Phd candidate at the University of Amsterdam funded by the NWO. Previously, I obtained a Master’s degree in Mathematics at the Radboud University and a Master’s degree in Business at Tilburg University. My research focuses on finding new methods to approximately solve hard minimisation problems with concave parts in the objective and/or constraint functions. Such problems arise often in, e.g., logistics, where costs are concave functions due to economies of scale. An important test case is the optimal food supply-chain problem for the World Food Programme.
After obtaining a Master's degree in both Mathematics and Operations Management at Eindhoven University of Technology, I started as a PhD candidate in the OR department of Tilburg University. I am currently working on various topics that explore the merits of applying distributionally robust optimisation as a tool to analyze stochastic systems. My research mainly focuses on the distribution-free analysis of stochastic systems that are driven by some underlying stochastic process. Please take a look at my university profile page.
I lead the model integration and real-time optimisation group at KISTERS, a global provider of software solutions for the water and energy business. Some of the water flow optimisation problems that arise in my work at KISTERS have strongly non-linear equality constraints and as such are not convex. Next to my primary function, I am refining the mathematics I have developed to tackle these problems as a PhD candidate at the University of Amsterdam.
I am a PhD candidate at the Zero Hunger Lab at Tilburg University. My research focuses on applying and developing operations research techniques that help humanitarian organizations to optimise their operations. Examples of my work are finding optimal depot locations for humanitarian logistics service providers using robust optimisation, and optimising route decisions in (partly) unknown road networks that may be heavily affected by weather conditions.
I am a PhD candidate at Tilburg University, working on various optimisation aspects of radiation therapy treatment planning for cancer patients. In particular, my research focuses on biologically-based treatment planning, where patient specific (biological response) information and its uncertainties are taken into account. We employ techniques from adjustable robust optimisation and conic optimisation, amongst others. On these projects we collaborate with researchers from Massachusetts General Hospital and Harvard Medical School (Boston, USA), whom I have visited several times. Please take a look at my university profile page.
I am a PhD candidate at Tilburg University funded by the NWO Research Talent grant titled 'A new optimization framework to solve hard decision problems under uncertainty’. My research focuses on the analysis of existing methods to handle uncertainty in continuous optimization as well as designing new methods to treat such problems. Examples of my work are ‘Reducing conservatism in robust optimization’ and ‘Tractable approximation of hard uncertain optimization problems’. In 2019 I was a visiting researcher at Imperial College London for three months and in 2020 I visited Technion in Haifa, Israel for two weeks.
Koen Peters is a project manager in the Supply Chain Planning & Optimization unit of the World Food Programme. After finishing a Master’s degree in Operations Research at Tilburg University, he decided to apply his optimisation knowledge to support humanitarian operations. For the last few years, he has been leading optimisation initiatives at the World Food Programme, developing user-friendly tools to ensure that WFP can reach as many beneficiaries as possible. Under the guidance of professors Hein Fleuren and Dick den Hertog he is pursuing a PhD at Tilburg University’s Zero Hunger Lab.