Dr. Rainer Schlosser

Postdoc

Phone:	+49 (331) 5509-1309
Fax:	+49 (331) 5509-579
Email:	rainer.schlosser(at)hpi.de
Room:	Hasso-Plattner-Villa, V-2.05
	SSRN, ResearchGate, Google Scholar

Data-Driven Decision-Support for Enterprise Applications

I am working on data-driven decision-making for enterprise applications using quantitative methods of operations research and data science. I am particularly interested in the following fields:

Database Optimization

Optimal Resource Allocation
Workload-Driven Decision-Making
Robust Configurations for Stochastic Dynamic Workloads
Index Selection
Data Placement, Partial Replication

Operations Management

Optimal Control of Dynamic Systems
Stochastic Models & Simulation
Risk-Sensitive Decision-Making
Dynamic Pricing Competition, E-commerce
Inventory Management, Advertising

Machine Learning

Anticipation of Workload Scenarios
Analysis of Partially Observable Market Data
Demand Learning
Customer Choice, Strategic Customers
Estimation of Sales Probabilities

Projects

Robust Database Optimization with Stochastic Workloads
Dynamic Pricing on Amazon
Price Wars: An Interactive Simulation Platform

Education

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

Teaching

Software in Operations Research (SS14 at HU Berlin)
Revenue Management (SS14)
Software in Operations Research (WS13/14)
Operations Management (WS13/14)
Teaching Assistant for Operations Research I, II, III, IV (WS10/11-SS14)

Reviewing

IEEE Transactions on Knowledge and Data Engineering
European Journal of Operational Research
International Journal of Production Economics
Journal of the Operational Research Society
Journal of Economic Dynamics and Control
IMA Journal of Management Mathematics
Transportation Research (Part E)
OR Spectrum
Economics E-Journal
Complexity
Omega: The International Journal of Management Science
Expert Systems with Applications
Management Science

Publications

Schlosser, R., Walther, C., Boissier, M., Uflacker, M.: Automated Repricing and Ordering Strategies in Competitive Markets. AI Communications, accepted for publication. 1-15 (2019).

[ BibTeX ]

@article{schlosser2019automated, author = {Schlosser, Rainer and Walther, Carsten and Boissier, Martin and Uflacker, Matthias}, journal = {AI Communications, accepted for publication}, keywords = {myown ordering pricing}, pages = {1-15}, title = {Automated Repricing and Ordering Strategies in Competitive Markets}, year = 2019 }
Schlosser, R.: Data-Driven Stochastic Dynamic Pricing and Ordering. Operations Research Proceedings 2018, forthcoming (2019).

[ BibTeX ]

@inproceedings{schlosser2019datadriven, author = {Schlosser, Rainer}, booktitle = {Operations Research Proceedings 2018, forthcoming}, keywords = {myown ordering pricing}, title = {Data-Driven Stochastic Dynamic Pricing and Ordering}, year = 2019 }
Boissier, M., Schlosser, R., Uflacker, M.: Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements. IEEE 34th International Conference on Data Engineering (ICDE 2018). pp. 209-220 (2018).

[ BibTeX ] [ Download ]

@inproceedings{boissier2018hybrid, abstract = {Recent developments in database research intro- duced HTAP systems that are capable of handling both transactional and analytical workloads. These systems achieve their performance by storing the full data set in main memory. An open research question is how far one can reduce the main memory footprint without losing the performance superiority of main memory-resident databases. In this paper, we present a hybrid main memory-optimized database for mixed workloads that evicts cold data to less expensive storage tiers. It adapts the storage layout to mitigate the negative performance impact of secondary storage. A key challenge is to determine which data to place on which storage tier. We introduce a novel workload-driven model that determines Pareto-optimal allocations while also considering reallocation costs. We evaluate our concept for a production enterprise system as well as reproducible data sets.}, author = {Boissier, Martin and Schlosser, Rainer and Uflacker, Matthias}, booktitle = {IEEE 34th International Conference on Data Engineering (ICDE 2018)}, keywords = {myown uncompressed column}, month = 4, pages = {209-220}, title = {Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements}, year = 2018 }
Schlosser, R.: Stochastic Dynamic Multi-Product Pricing under Competition. Operations Research Proceedings 2017. pp. 527-533 (2018).

[ BibTeX ]

@inproceedings{schlosser2017stochastic, author = {Schlosser, Rainer}, booktitle = {Operations Research Proceedings 2017}, keywords = {myown pricing}, pages = {527-533}, title = {Stochastic Dynamic Multi-Product Pricing under Competition}, year = 2018 }
Schlosser, R., Richly, K.: Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information. 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018. pp. 21-30 (2018).

[ BibTeX ]

@inproceedings{schlosser2018dynamic, author = {Schlosser, Rainer and Richly, Keven}, booktitle = {7th International Conference on Operations Research and Enterprise Systems, ICORES 2018}, keywords = {Pricing}, month = {January}, pages = {21-30}, title = {Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information}, volume = {Vol. 1 - 978-989-758-285-1}, year = 2018 }
Schlosser, R., Boissier, M.: Optimal Repricing Strategies in a Stochastic Infinite Horizon Duopoly. Operations Research and Enterprise Systems. pp. 129-150. Springer (2018).

[ BibTeX ] [ Download ]

@inbook{schlosser2017optimal, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {Operations Research and Enterprise Systems}, keywords = {imported myown pricing}, pages = {129-150}, publisher = {Springer}, title = {Optimal Repricing Strategies in a Stochastic Infinite Horizon Duopoly}, volume = {Communications in Computer and Information Science book series (CCIS, volume 884)}, year = 2018 }
Schlosser, R., Walther, C., Boissier, M., Uflacker, M.: Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2018). pp. 5856-5858 (2018).

[ BibTeX ] [ Download ]

@inproceedings{schlosser2018datadriven, author = {Schlosser, Rainer and Walther, Carsten and Boissier, Martin and Uflacker, Matthias}, booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2018)}, keywords = {myown ordering pricewars pricing}, pages = {5856-5858}, title = {Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces}, year = 2018 }
Schlosser, R., Boissier, M.: Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach. KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 705-714 (2018).

[ BibTeX ] [ Download ]

@inproceedings{schlosser2018dynamic, abstract = {Most online markets are characterized by competitive settings and limited demand information. Due to the complexity of such markets, efficient pricing strategies are hard to derive. We analyze stochastic dynamic pricing models in competitive markets with multiple offer dimensions, such as price, quality, and rating. In a first step, we use a simulated test market to study how sales probabilities are affected by specific customer behaviors and the strategic interaction of price reaction strategies. Further, we show how different state-of-the-art learning techniques can be used to estimate sales probabilities from partially observable market data. In a second step, we use a dynamic programming model to compute an effective pricing strategy which circumvents the curse of dimensionality. We demonstrate that the strategy is applicable even if the number of competitors is large and their strategies are unknown. We show that our heuristic can be tuned to smoothly balance profitability and speed of sales. Further, our approach is currently applied by a large seller on Amazon for the sale of used books. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%.}, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {{KDD} '18 Proceedings of the 24th {ACM} {SIGKDD} International Conference on Knowledge Discovery & Data Mining}, keywords = {myown competition pricing}, pages = {705-714}, title = {Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach}, year = 2018 }
Schlosser, R., Richly, K.: Dynamic Pricing Competition with Unobservable Inventory Levels: A Hidden Markov Model Approach. Communications in Computer and Information Science, Springer (accepted for publication) (2018).

[ BibTeX ]

@inproceedings{schlosser2018dynamic, author = {Schlosser, Rainer and Richly, Keven}, booktitle = {Communications in Computer and Information Science, Springer (accepted for publication)}, keywords = {myown competition pricing}, title = {Dynamic Pricing Competition with Unobservable Inventory Levels: A Hidden Markov Model Approach}, year = 2018 }
Schlosser, R., Boissier, M.: Dealing with the Dimensionality Curse in Dynamic Pricing Competition: Using Frequent Repricing to Compensate Imperfect Market Anticipations. Computers and Operations Research. 100, 26-42 (2018).

[ BibTeX ] [ Download ]

@article{schlosser2018dealing, abstract = {Most sales applications are characterized by competition and limited demand information. For success- ful pricing strategies, frequent price adjustments as well as anticipation of market dynamics are crucial. Both effects are challenging as competitive markets are complex and computations of optimized pricing adjustments can be time-consuming. We analyze stochastic dynamic pricing models under oligopoly competition for the sale of perishable goods. To circumvent the curse of dimensionality, we propose a heuristic approach to efficiently compute price adjustments. To demonstrate our strategy’s applicability even if the number of competitors is large and their strategies are unknown, we consider different competitive settings in which competitors frequently and strategically adjust their prices. For all settings, we verify that our heuristic strategy yields promising results. We compare the performance of our heuristic against upper bounds, which are obtained by optimal strategies that take advantage of perfect price an- ticipations. We find that price adjustment frequencies can have a larger impact on expected profits than price anticipations. Finally, our approach has been applied on Amazon for the sale of used books. We have used a seller’s historical market data to calibrate our model. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%.}, author = {Schlosser, Rainer and Boissier, Martin}, journal = {Computers and Operations Research}, keywords = {myown competition pricing}, pages = {26-42}, title = {Dealing with the Dimensionality Curse in Dynamic Pricing Competition: Using Frequent Repricing to Compensate Imperfect Market Anticipations}, volume = 100, year = 2018 }
Uflacker, M., Schlosser, R., Meinel, C.: Ertragsmanagement im Wandel - Potentiale der In-Memory Technologie. In: Gläß, R. and Leukert, B. (eds.) Handel 4.0: Die Digitalisierung des Handels. Strategien, Technologien, Transformation. pp. 177-190. Springer Gabler (2017).

[ BibTeX ]

@inbook{Matthias2017a, author = {Uflacker, Matthias and Schlosser, Rainer and Meinel, Christoph}, booktitle = {Handel 4.0: Die Digitalisierung des Handels. Strategien, Technologien, Transformation}, edition = 1, editor = {Gläß, R. and Leukert, B.}, keywords = {imported}, pages = {177-190}, publisher = {Springer Gabler}, title = {Ertragsmanagement im Wandel - Potentiale der In-Memory Technologie}, year = 2017 }
Seiffert, M., Holstein, F., Schlosser, R., Schiller, J.: Next Generation Cooperate Wearables: Generalized Activity Assessment Computed Fully Distributed Within a Wireless Body Area Network. IEEE Access Journal. 5, 16793-16807 (2017).

[ BibTeX ]

@article{seiffert2017generation, author = {Seiffert, Martin and Holstein, Flavio and Schlosser, Rainer and Schiller, Jochen}, journal = {IEEE Access Journal}, keywords = {imported myown}, pages = {16793-16807}, title = {Next Generation Cooperate Wearables: Generalized Activity Assessment Computed Fully Distributed Within a Wireless Body Area Network}, volume = 5, year = 2017 }
Serth, S., Podlesny, N., Bornstein, M., Lindemann, J., Latt, J., Selke, J., Schlosser, R., Boissier, M., Uflacker, M.: An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces. 21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017. pp. 61-66. IEEE (2017).

[ BibTeX ] [ Download ]

@inproceedings{edoc2017pricewars, author = {Serth, Sebastian and Podlesny, Nikolai and Bornstein, Marvin and Lindemann, Jan and Latt, Johanna and Selke, Jan and Schlosser, Rainer and Boissier, Martin and Uflacker, Matthias}, booktitle = {21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017}, keywords = {myown price pricewars dynamic wars pricing platform}, month = 10, pages = {61-66}, publisher = {IEEE}, title = {An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces}, year = 2017 }
Boissier, M., Schlosser, R., Podlesny, N., Serth, S., Bornstein, M., Latt, J., Lindemann, J., Selke, J., Uflacker, M.: Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform. Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys '17). pp. 355-357. ACM, New York, NY, USA (2017).

[ BibTeX ] [ Download ]

@inproceedings{recsysdemo2017dynpri, address = {New York, NY, USA}, author = {Boissier, Martin and Schlosser, Rainer and Podlesny, Nikolai and Serth, Sebastian and Bornstein, Marvin and Latt, Johanna and Lindemann, Jan and Selke, Jan and Uflacker, Matthias}, booktitle = {Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys '17)}, keywords = {myown Dynamic Pricing RecSys Recommender pricewars Systems Demonstration}, month = 10, pages = {355-357}, publisher = {ACM}, series = {RecSys '17}, title = {Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform}, year = 2017 }
Schlosser, R., Boissier, M.: Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors. Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal. pp. 47-56 (2017).

[ BibTeX ] [ Download ]

@inproceedings{Rainer2017a, author = {Schlosser, Rainer and Boissier, Martin}, booktitle = {Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal}, keywords = {imported pricewars pricing}, month = 2, pages = {47-56}, title = {Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors}, year = 2017 }
Zimmermann, T., Djürken, T., Mayer, A., Janke, M., Boissier, M., Schwarz, C., Schlosser, R., Uflacker, M.: Detecting Fraudulent Advertisements on a Large E-Commerce Platform. Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017 (2017).

[ BibTeX ] [ Download ]

@conference{Tim2017a, author = {Zimmermann, Tim and Djürken, Timo and Mayer, Arne and Janke, Michael and Boissier, Martin and Schwarz, Christian and Schlosser, Rainer and Uflacker, Matthias}, booktitle = {Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017.}, keywords = {imported}, month = 3, title = {Detecting Fraudulent Advertisements on a Large E-Commerce Platform}, year = 2017 }
Schlosser, R.: Stochastic Dynamic Pricing and Advertising in Isoelastic Oligopoly Models. European Journal of Operational Research. 259, 1144-1155 (2017).

[ BibTeX ]

@article{Rainer2017a, author = {Schlosser, Rainer}, journal = {European Journal of Operational Research}, keywords = {imported competition pricing}, number = 3, pages = {1144-1155}, title = {Stochastic Dynamic Pricing and Advertising in Isoelastic Oligopoly Models}, volume = 259, year = 2017 }
Boissier, M., Djürken, T., Schlosser, R., Faust, M.: A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases. 22nd International Conference, ICIST 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, CCIS 639. p. 285--299 (2016).

[ BibTeX ] [ Download ]

@conference{Martin2016a, author = {Boissier, Martin and Djürken, Timo and Schlosser, Rainer and Faust, Martin}, booktitle = {22nd International Conference, {ICIST} 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, {CCIS} 639}, keywords = {imported}, month = 10, pages = {285--299}, title = {A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases}, year = 2016 }
Schlosser, R.: Joint Stochastic Dynamic Pricing and Advertising with Time-Dependent Demand. Journal of Economic Dynamics and Control. 73, 439-452 (2016).

[ BibTeX ]

@article{schlosser2016joint, author = {Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported advertising pricing}, pages = {439-452}, title = {Joint Stochastic Dynamic Pricing and Advertising with Time-Dependent Demand}, volume = 73, year = 2016 }
Schlosser, R., Boissier, M., Schober, A., Uflacker, M.: How To Survive Dynamic Pricing Competition in E-commerce. Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016 (2016).

[ BibTeX ] [ Download ]

@conference{Rainer2016a, author = {Schlosser, Rainer and Boissier, Martin and Schober, Andre and Uflacker, Matthias}, booktitle = {Proceedings of the Poster Track of the 10th {ACM} Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016}, keywords = {imported amazon pricewars pricing}, month = 9, title = {How To Survive Dynamic Pricing Competition in E-commerce}, year = 2016 }
Schlosser, R.: Stochastic Dynamic Multi-Product Pricing with Dynamic Advertising and Adoption Effects. Journal of Revenue and Pricing Management. 15, 153-169 (2016).

[ BibTeX ]

@article{Rainer2016b, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {imported pricing multi}, number = 2, pages = {153-169}, title = {Stochastic Dynamic Multi-Product Pricing with Dynamic Advertising and Adoption Effects}, volume = 15, year = 2016 }
Schlosser, R.: A Stochastic Dynamic Pricing and Advertising Model under Risk Aversion. Journal of Revenue and Pricing Management. 14, 451-468 (2015).

[ BibTeX ]

@article{Rainer2015b, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {imported risk pricing}, number = 6, pages = {451-468}, title = {A Stochastic Dynamic Pricing and Advertising Model under Risk Aversion}, volume = 14, year = 2015 }
Schlosser, R.: Dynamic Pricing and Advertising Models with Inventory Holding Costs. Journal of Economic Dynamics and Control. 57, 163-181 (2015).

[ BibTeX ]

@article{Rainer2015c, author = {Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported advertising pricing}, pages = {163-181}, title = {Dynamic Pricing and Advertising Models with Inventory Holding Costs}, volume = 57, year = 2015 }
Schlosser, R.: Dynamic Pricing with Time-Dependent Elasticities. Journal of Revenue and Pricing Management. 14, 365-383 (2015).

[ BibTeX ]

@article{Rainer2015a, author = {Schlosser, Rainer}, journal = {Journal of Revenue and Pricing Management}, keywords = {myown pricing}, number = 5, pages = {365-383}, title = {Dynamic Pricing with Time-Dependent Elasticities}, volume = 14, year = 2015 }
Helmes, K., Schlosser, R.: Oligopoly Pricing and Advertising in Isoelastic Adoption Models. Dynamic Games and Applications. 5, 334-360 (2015).

[ BibTeX ]

@article{Kurt2015a, author = {Helmes, Kurt and Schlosser, Rainer}, journal = {Dynamic Games and Applications}, keywords = {imported}, number = 3, pages = {334-360}, title = {Oligopoly Pricing and Advertising in Isoelastic Adoption Models}, volume = 5, year = 2015 }
Helmes, K., Schlosser, R., Weber, M.: Dynamic Advertising and Pricing in a Class of General New-Product Adoption Models. European Journal of Operational Research. 229, 433-443 (2013).

[ BibTeX ]

@article{Kurt2013b, author = {Helmes, Kurt and Schlosser, Rainer and Weber, Martin}, journal = {European Journal of Operational Research}, keywords = {imported}, number = 2, pages = {433-443}, title = {Dynamic Advertising and Pricing in a Class of General New-Product Adoption Models}, volume = 229, year = 2013 }
Helmes, K., Schlosser, R.: Dynamic Advertising and Pricing with Constant Demand Elasticities. Journal of Economic Dynamics and Control. 37, 2814-2832 (2013).

[ BibTeX ]

@article{Kurt2013a, author = {Helmes, Kurt and Schlosser, Rainer}, journal = {Journal of Economic Dynamics and Control}, keywords = {imported}, number = 12, pages = {2814-2832}, title = {Dynamic Advertising and Pricing with Constant Demand Elasticities}, volume = 37, year = 2013 }

Dr. Rainer Schlosser

Postdoc

Data-Driven Decision-Support for Enterprise Applications

Projects

Education

Teaching

Reviewing

Publications

Chair of Prof. Hasso Plattner

News

16.05.2018 | Top ranks at Fifth BioASQ Challenge

09.05.2018 | Paper accepted at SSDBM 2018

09.04.2018 | SORMAS technical paper published in Frontiers in ICT

28.02.2018 | Paper accepted at ICDE 2018

28.01.2018 | Best Paper Award received at ICORES'18

Open Positions

Literature