Short bio: Ralf Borndörfer is a Professor for Discrete Mathematics at Freie Universität Berlin and head of the Network Optimization department at Zuse Institute Berlin; he also serves as Scientist in Charge of the Application Area Networks of the Berlin Mathematics Excellence Cluster Math+, as president of the heureka Foundation for Environment and Mobility, and as one of the heads of the Traffic and Transport working group of the German Operations Research Society. His work is on combinatorial optimization and integer programming with applications to traffic and transport. He was head of several projects with Deutsche Bahn AG, in which RotOR, an ICE highspeed train rotation optimizer based on hypergraphical methods, was developed. This optimizer is integrated in DB’s FEO planning system, which was presented in the finals of the 2020 INFORMS Edelman award.
He is one of the founders of LBW Optimization, a supplier of commercial high performance vehicle and duty optimization systems.
His current research is on geometric optimization methods for periodic timetabling, discrete and continuous optimization methods for flight planning, electric vehicle scheduling, predictive railway maintenance, air cargo scheduling, and toll enforcement.

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Dr. Ying Chen is a financial statistician and data scientist. She develops statistical modelling and machine learning methods customized for nonstationary, high frequency and large dimensional complex data such as cryptocurrency, limit order book, and renewable energy. She also works on forecasting, quantum computing in finance, citation analysis and research metrics, financial text mining and sentiment analysis, and network analysis.

Dr. Chen is Associate Professor in Department of Mathematics, Academic Director of the Digital FinTech PhD program in Asian Institute of Digital Finance, and Joint Appointee in Risk Management Institute (1 July 2019 to 30 June 2023), National University of Singapore. She also holds Joint Appointment in Department of Statistics and Applied Probability (1 January 2019 to 31 December 2021), and Courtesy Appointment in Department of Economics (April 1, 2018 to March 31, 2021) at the National University of Singapore. She is also Faculty member in NUS Graduate School for Integrative Sciences and Engineering since July 2016.

Dr. Chen is Council Member of the International Statistical Institute for the period 2023 – 2027. She is Associate Editor of 4 journals including Statistica Sinica, Statistics and Its Interface, and Digital Finance. She is ISI Elected Member since March 2016. She is Scientific Secretary (August 2017 to July 2019) and member of Executive Committee of the International Association for Statistical Computing (IASC) from July 2017 and Board of Director ordinary member of the Asian Regional Section (ARS) of IASC. She is regular member of the Advisory Board of Institute of Statistical Mathematics, Japan from 1 April 2018 to 31 March 2022.

Short bio: Thorsten Koch is Professor for Software and Algorithms for Discrete Optimization at TU-Berlin and head of the Applied Algorithmic Intelligence Methods and the Digital Data and Information for Society, Science, and Culture departments at the Zuse Institute Berlin (ZIB). He has worked in several areas, especially the planning of infrastructure networks, chip verification, mathematical education, and integer optimization. From 2000 to 2020 he led the efforts on developing Integer Programming Solvers at ZIB, including the SCIP development.
From 2008 to 2014 he was the coordinator of the FORNE project, an industry collaboration project regarding gas transportation involving five universities and two research institutes. The project received the 2016 EURO Excellence in Practice Award of the European OR Society.
From 2013 to 2019 he was head of the GasLab and the SynLab within the Research Campus MODAL (Mathematical Optimization and Data Analysis Laboratory). The project Optimized Execution of Dispatching conducted together with Germany's largest Gas Transmission System Operator became a finalist of the 2020 INFORMS Innovative Applications in Analytics Award.
Currently, the work is focused on developing high-performance parallel methods for solving large-scale structured optimization problems. Such problems arise, for example, in data-driven, real-world analysis and planning of sustainable network infrastructures. This includes high-performance solvers for Steiner Tree Problems in Graphs (STPG) and Quadratic Unconstraint Binary Optimization (QUBO).