The need for automated decision-making is steadily increasing. The goal is to derive methods and data-driven models for automated decision support for practical applications in uncertain and changing environments. Solving problems in practical applications requires bringing together data management, analytics, optimization, and computer science.

Our research group Data-Driven Decision Support focuses on automated decision-making in the areas of Operations Management and beyond using quantitative methods of operations research (cf. modelling, simulation, and optimization) and data science (cf. AI/ML). Our research has been published in over 75 peer-reviewed publications including renowned OR Journals (EJOR, JEDC, IJPE, IJPR, COR, DGAA, ITOR, JRPM, JIMS, JCLP), distinguished data science conferences (KDD, IJCAI, RECSYS, SDM, ICDM, PMLR, ECML, ICDE), and leading computer science venues (BISE, VLDB, EDBT, DAPD, CIKM, EDOC, SSDBM). Rainer serves as a reviewer for over 60 Journals in the areas of operations management, AI/ML, and information systems.

Keywords: Data-Driven Decision Support, Business Analytics, Risk & Robustness, Markov Decision Processes, Reinforcement Learning, Revenue Management & Pricing, Inventory Management, Resource Allocation, Recommerce, Sustainability, Circular Economy

• Self-Learning Agents in the ReCommerce Industry
• Risk-averse Control of Markov Decision Processes
• Optimal Product Replacement & Recycling
• Approximate Dynamic Programming & Reinforcement Learning
• Circular Economy & Sustainable Revenue Management
• Dynamic Pricing on Amazon Marketplace
• Price Wars: An Interactive Simulation Platform

• Planned: "AI meets Sustainability: Using Digital Twins to Leverage Reinforcement Learning – Based Dynamic Pricing in Circular Markets under Competition", EURO 2024, July, Copenhagen, Denmark
• "Dynamic Pricing under Competition: Challenges & Opportunities", Keynote presentation at ICORES 2023, Feb 2023, Lisbon, Portugal (Invited Talk)
• "A Conceptual Framework for Studying Self-Learning Agents in Recommerce Markets", at OR 2022, Sep 2022, KIT, Germany (Invited Talk)
• "Risk-Averse Revenue Management using Mean-Variance and Mean-Semivariance Optimization", INFORMS Revenue Management & Pricing Conference, June 2021, Johns Hopkins Carey Business School, USA
• "Dynamic Pricing on Online Marketplaces – Theory and Applications", 17^th conference of the GOR working group „Pricing & Revenue Management", Feb 2020, Munich, Germany (Invited Talk)
• "Dynamic Pricing Competition in E-Commerce with Data-Driven Price Anticipations", ICIAM 2019, July 2019, Valencia, Spain (Invited Talk)
• "Risk-Sensitive Control of Markov Decision Processes in Revenue Management: A Moment-Based Approach with Target Distributions", INFORMS Revenue Management & Pricing Conference, June 2019, Stanford Graduate School of Business, CA, USA
• "Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies" and "Workload-Driven Fragment Allocation for Partially Replicated Databases Using Linear Programming", ICDE 2019, April 2019, Macao SAR, China
• "Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach", KDD 2018, Aug 2018, London, UK
• "How To Survive Dynamic Pricing Competition in E-commerce", RecSys 2016, Sep 2016, Massachusetts Institute of Technology (MIT) and the IBM Research campuses in Boston, MA, USA

• "Dynamic Pricing with Time-Dependent Elasticities", INFORMS Revenue Management & Pricing Conference, June 2015, Columbia University, New York, USA

• Ph.D. in Operations Research (summa cum laude), Humboldt-University of Berlin, Germany (05/2014), Topic: Dynamic Pricing and Advertising Models
• Master's degree (Dipl.-Math.) in Mathematics (very good), Humboldt-University of Berlin, Institute of Applied Mathematics, Germany (10/2010), Focus: Optimization, Stochastic Models, Numerical Analysis
• Master's degree (Dipl.-Kfm.) in Business Administration (very good), Humboldt-University of Berlin, School of Business and Economics, Germany (02/2010), Focus: Operations Research, Econometrics, Risk Management

• Planned Research Stay: University of Waterloo, Waterloo, Canada (2024)
• Grant Application: ORA 8 Grant Application (with UK, Canada & France):  “A Unified Approach to Green Innovation by Fossil Fuel Companies”, Nov 2023 (role: Co-Director)
• Research Stay: University of Zurich, Zurich, Switzerland (Nov 2023)
• Travel Grant: for ICORES 2023, Lisbon, Portugal (Feb 2023)
• Grant Application: BMBF Project Proposal "AI for Recommerce Markets", Feb 2022 (Role: Coordinator)
• Grant: Funding for one PhD Position over 3 years (HPI Research School, Dec 2020)
• Research Stay: KEDGE Business School, Marseille, France (Oct 2019)
• Research Stay: CESIT Center of Excellence, Bordeaux, France (Oct 2019)
• Travel Grant: for ICIAM 2019, Valencia, Spain (Invited Talk); Grant managed within CEREMADE Department of the University Paris Dauphine (July 2019)
• Best Paper Award: Schlosser, R. "Stochastic Dynamic Pricing with Strategic Customers and Reference Price Effects", 8^th International Conference on Operations Research and Enterprise Systems (ICORES 2019), Prague, Czech Republic
• Best Paper Award: Schlosser, R., Richly, K. "Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information", 7^th International Conference on Operations Research and Enterprise Systems (ICORES 2018), Funchal, Portugal
• Program: OR 2015 Emerging Scholar Program, GOR
• Grant: Postdoctoral Scholarship, 2014 - 2015, Humboldt Graduate School
• Award Nomination:  Ph.D. Thesis nominated for Humboldt Prize 2014
• Ph.D. Grant: Elsa-Neumann-Scholarship, 2011 - 2013, Berlin Senate

At HPI:

• Probabilistic Machine Learning (SS24)
• Mathematik III: Stochastik & Statistik (WS23/24, Intermediate evaluation 1.4)
• Dynamic Programming and Reinforcement Learning (SS23, Evaluation 1.2)
• Bachelor's Project 2021/22 Part II: Recommerce Market Simulation & Reinforcement Learning (SS22, Evaluation 1.1)
• Dynamic Programming and Reinforcement Learning (SS22, Evaluation 1.2)
• Bachelor's Project 2021/22 Part I: Recommerce Market Simulation & Reinforcement Learning (WS21/22, Evaluation 1.1)
• Master's Project 2021/22: GPU-Accelerated Causal Structure Learning (WS21/22, Evaluation 1.1)
• Dynamic Programming and Reinforcement Learning (SS21, Evaluation 1.2)
• Data-Driven Decision-Making in Enterprise Applications (SS20, Evaluation 1.3)
• Data-Driven Decision-Making in Enterprise Applications (SS19, Evaluation 1.3)
• Data-Driven Demand Learning and Dynamic Pricing Strategies in Competitive Markets (SS18, Evaluation 2.3)
• Data-Driven Demand Learning and Dynamic Pricing Strategies in Competitive Markets (SS17, Evaluation 1.8)
• Master Project 2016/17: How to Survive Dynamic Pricing Competition (WS16/17, Evaluation 1.2)
• Dynamic Pricing on Online Marketplaces: Strategies and Applications (SS16, Evaluation 1.2)
• Trends and Concepts Exercise: Developing In-Memory Applications (Fraud Detection) (SS16, Tutor)
• Trends and Concepts Exercise: Developing a Product Recommendation System for the Retail Industry (SS15, Tutor)

At Humboldt University Berlin, School of Business and Economics:

• Software in Operations Research (SS14, Evaluation 1,0)
• Excel Seminar (SS14, Evaluation 1,4)
• Software in Operations Research (WS13/14, Evaluation 1,4)
• Excel Seminar (WS13/14, Evaluation 1,3)
• Teaching Assistant for Revenue Management, Operations Management (WS11/12-SS14)
• Teaching Assistant for Operations Research I, II, III, IV (WS10/11-SS14)

• Jan Kossmann (finished Q2 2022)
• Christopher Hagedorn (finished Q2 2023)
• Stefan Halfpap (finished Q4 2023)
• Keven Richly (thesis submitted Q1 2023, colloquium pending)
• Martin Boissier (thesis submitted Q2 2023, colloquium pending)
• Johannes Huegle (thesis submitted Q4 2023, colloquium pending)
• Alexander Kastius (expected submission 2024)
• Marcel Weisgut (expected submission 2024)
• N.n. (apply for open position)

Analytics & Data Science

• KDD 2024
• IJCAI 2022, 2023, 2024
• ECML-PKDD 2023, 2024
• ICDE 2024
• IEEE Transactions on Knowledge & Data Engineering
• IEEE Transactions on Neural Networks & Learning Systems
• Expert Systems with Applications
• Engineering Applications of Artificial Intelligence
• The Knowledge Engineering Review
• ACM Transactions on Knowledge Discovery from Data
• Journal of the Royal Statistical Society
• Czech Science Foundation (GACR)
• Dutch Research Council (NWO)

Management Science & Economics

• Management Science
• International Journal of Production Economics
• International Journal of Production Research
• Omega
• Journal of Revenue & Pricing Management
• Transportation Research (Part E)
• International Journal of Operations & Quantitative Management
• Journal of Retailing & Consumer Services
• Applied Stochastic Models in Business & Industry
• Production Planning & Control
• Managerial & Decision Economics
• Economics E-Journal
• Journal of Economic Dynamics & Control

Operations Research

• European Journal of Operational Research
• Journal of the Operational Research Society
• Operations Research Perspectives
• IMA Journal of Management Mathematics
• Operational Research
• Optimal Control, Applications & Methods
• RAIRO - Operations Research
• TOP
• OR Spectrum
• Applied Mathematics & Computation
• Mathematical Methods of Operations Research

Information Systems & Engineering

• Business & Information Systems Engineering
• Computers & Industrial Engineering
• SIGMOD Record
• Systems Science & Control Engineering
• Journal of Systems Science & Systems Engineering
• Science China Information Sciences
• Journal of Process Mechanical Engineering
• Heliyon
• HICSS 2023
• Springer Nature Applied Sciences
• IISE Transactions
• IEEE Transactions on Systems, Man & Cybernetics
• IEEE Access
• Expert Systems
• Applied Soft Computing
• ACM Computing Surveys

Sustainability

• Journal of Cleaner Production
• Resources Conservation & Recycling
• Mathematical Biosciences & Engineering
• Maritime Policy & Management
• Green Finance
• Sustainable Computing: Informatics & Systems
• Journal of Energy Storage

Scientific Communities: INFORMS, ACM, IEEE, GOR (AG PRM), DHV

• Kossmann, J., R. Schlosser, A. Kastius, M. Perscheid, H. Plattner (2022). Training an Agent for Iterative Multi-Attribute Index Selection, Patent Submission App., HPI26526EP (EP4227821A1, pending)
• Schlosser, R., Kossmann, J., Boissier, M., Uflacker, M., Plattner, H. (2020). Iterative Multi-Attribute Index Selection for Large Database Systems, Patent SubmissionApp. (EP3719663, accepted Oct 2022; US16/838,830, pending; CN111797118, pending)
• Schlosser, R., Boissier, M., Uflacker, M., Plattner, H. (2019). Data Placement in Hybrid Data Layouts for Tiered HTAP Databases, Patent Submission App. (EP3547166,accepted Nov 2020; US11/256,718, accepted Feb 2022; CN110362566, pending)