Hasso-Plattner-Institut
Prof. Dr. Christoph Lippert
 

Dr.-Ing. Matthieu-P. Schapranow

Group Leader, Lecturer, and Scientific Manager Digital Health Innovations

Click to view a high-res picture of Matthieu-P. Schapranow
 Phone:+49 (331) 55 09 - 1331
 Fax:+49 (331) 55 09 - 163
 E-Mail:schapranow(at)hpi.de,
schapranow(at)ieee.org
 Organization:Hasso Plattner Insitute
 Address:Rudolf-Breitscheid-Str. 187 Potsdam, Brandenburg, 14482 Germany
 Room:Hasso Plattner Institute Campus III, Room: G2.-2.15
 Profiles:XING, LinkedIn, Plaxo, University of Potsdam, Research Gate

Committees and Memberships

Awards

Dr. Matthieu-P. Schapranow is heading the working group "In-Memory Computing for Digital Health", lecturer and Scientific Manager Digital Health Innovations at the Hasso Plattner Institute (HPI). He is a valued member of the Platform Learning Systems and contributes to the Federal Association for Information Technology, Telecommunications and New Media (BITKOM) and the European GAIA-X cloud initiative. Dr. Schapranow holds a PhD as well as the MSc and BSc degrees in Software Engineering. He was named as one of the top Elite Researchers in Life Sciences in 2016 and one of Germany's Top 10 Junior Scientists in 2015. Furthermore, he was honored with the Personalized Medicine Convention Award 2015, the European Life Science Award in 2014, and the Innovation Award of the German Capital Region in 2012. Together with Prof. Dr. Plattner, he published the textbook "High-Performance In-Memory Genome Data Analysis" in 2013.

The full biography including high-res picture download are available in German and English.

Further Interests

  • Genomics
  • Life Sciences
  • Parallelization
  • Innovative Applications

Selected Patents

  • System and method for genomic data processing with an in-memory database system and real-time analysis (US20140214333, EP2759953)
  • Efficient genomic read alignment in an in-memory database (US20140214334, EP2759952)
  • Transparent control of access invoking real-time analysis of the query history (EP2667337)
  • Read more

Books

2014 (1)

  1. Hasso Plattner, Matthieu-P. Schapranow: High-Performance In-Memory Genome Data Analysis: How In-Memory Database Technology Accelerates Personalized Medicine, In-Memory Data Management Research, ISBN: 978-3-319-03034-0, 2014BibTeX

2013 (1)

  1. Matthieu-P. Schapranow: Real-time Security Extensions for EPCglobal Networks: Case Study for the Pharmaceutical Industry, In-Memory Data Management Research, Springer, ISBN: 978-3-642-36342-9, 2013BibTeX

 

 

Publications

2024

  • 1.
    Borchert, F., Llorca, I., Schapranow, M.-P.: Improving biomedical entity linking for complex entity mentions with LLM-based text simplification. Database. 2024, baae067 (2024).
     

2023

  • 1.
    Llorca, I., Borchert, F., Schapranow, M.-P.: A Meta-dataset of German Medical Corpora: Harmonization of Annotations and Cross-corpus NER Evaluation. Proceedings of the 5th Clinical Natural Language Processing Workshop. bll. 171–181. Association for Computational Linguistics, Toronto, Canada (2023).
     
  • 2.
    Schapranow, M.-P.: NephroCAGE: Wie Künstliche Intelligenz bei Nierenversagen unterstützen kann. Gesundhyte: Forschung neu vernetzen. 15, 100—102 (2023).
     
  • 3.
    Nordmeyer, S., Kraus, M., Ziehm, M., Kirchner, M., Schafstedde, M., Kelm, M., Niquet, S., Stephen, M., Baczko, I., Knosalla, C., Schapranow, M.-P., Dittmar, G., Gotthardt, M., Falcke, M., Regitz-Zagrosek, V., Kuehne, T., Mertins, P.: Disease- and sex-specific differences in patients with heart valve disease: A proteome study. Life Sci Alliance. 6, e202201411 (2023).
     
  • 4.
    Budde, K., Hiltawsky, K., Eskofier, B., Heismann, B., Kirchner, E., Klevesath, M., Lang, M., Loskill, H., Neumuth, T., Schapranow, M.-P., Schmidt-Rumposch, A., Susec, B., Welskop-Deffaa, E.M., Wolf-Ostermann, K.: KI für Gesundheitsfachkräfte: Chancen und Herausforderungen von medizinischen und pflegerischen KI-Anwendungen. Plattform Lernende Systeme (2023).
     
  • 5.
    Schapranow, M.-P., Borchert, F., Bougatf, N., Hund, H., Eils, R.: Software-Tool Support for Collaborative, Virtual, Multi-Site Molecular Tumor Boards. SN Computer Science. 4, 358 (2023).
     
  • 6.
    Steinwand, S., Borchert, F., Winkler, S., Schapranow, M.-P.: GGTWEAK: Gene Tagging with Weak Supervision for German Clinical Text. In: Juarez, J.M., Marcos, M., Stiglic, G., en Tucker, A. (reds.) Artificial Intelligence in Medicine. bll. 183–192. Springer Nature Switzerland, Cham (2023).
     
  • 7.
    Kämmer, N., and Borchert, F., and Winkler, S., and de Melo, G., and Schapranow, M.-P.: Resolving Elliptical Compounds in German Medical Text. The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks. bll. 292–305. Association for Computational Linguistics, Toronto, Canada (2023).
     
  • 8.
    Borchert, F., Llorca, I., Schapranow, M.-P.: Cross-Lingual Candidate Retrieval and Re-ranking for Biomedical Entity Linking. In: Arampatzis, A., Kanoulas, E., Tsikrika, T., Vrochidis, S., Giachanou, A., Li, D., Aliannejadi, M., Vlachos, M., Faggioli, G., en Ferro, N. (reds.) Experimental IR Meets Multilinguality, Multimodality, and Interaction. bll. 135–147. Springer Nature Switzerland, Cham (2023).
     
  • 9.
    Schapranow, M.-P.: Lernende Laborsysteme: Wie kann künstliche Intelligenz im Labor unterstützen?. In: Raem, A.M. en Rauch, P. (reds.) Immunoassays: ergänzende Methoden, Troubleshooting, regulatorische Anforderungen. bll. 755–775. Springer Berlin Heidelberg, Berlin, Heidelberg (2023).
     
  • 10.
    Borchert, F., Llorca, I., Roller, R., Arnrich, B., Schapranow, M.-P.: xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization. arXiv preprint arXiv:2310.11275. (2023).
     
  • 11.
    Borchert, F., Llorca, I., Schapranow, M.-P.: HPI-DHC @ BC8 SympTEMIST Track: Detection and Normalization of Symptom Mentions with SpanMarker and xMEN. In: Islamaj, R., Arighi, C., Campbell, I., Gonzalez-Hernandez, G., Hirschman, L., Krallinger, M., Lima-López, S., Weissenbacher, D., en Lu, Z. (reds.) Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models. , New Orleans, LA (2023).
     
  • 12.
    Fox, S., Preiß, M., Borchert, F., Rasheed, A., Schapranow, M.-P.: HPIDHC at NTCIR-17 MedNLP-SC: Data Augmentation and Ensemble Learning for Multilingual Adverse Drug Event Detection. NTCIR 17 Conference: Proceedings of the 17th NTCIR Conference on Evaluation of Information Access Technologies. bll. 185–192. , Tokyo, Japan (2023).
     
  • 13.
    Schapranow, M.-P., Bayat, M., Rasheed, A., Naik, M., Graf, V., Schmidt, D., Budde, K., Cardinal, H., Sapir-Pichhadze, R., Fenninger, F., Sherwood, K., Keown, P., Günther, O., Pandl, K., Leiser, F., Thiebes, S., Sunyaev, A., Niemann, M., Schimanski, A., Klein, T.: NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study. JMIR Res Protoc 2023. 12, (2023).
     
  • 14.
    Schapranow, M.-P.: Kann uns ChatGPT bei der Digitalisierung der Medizin helfen?. Management & Krankenhaus. 42, 10 (2023).
     

2022

  • 1.
    Beyerer, J., Müller-Quade, J., Albers, A., Houdeau, D., Tchouchenkov, I., Dzaack, J., Schapranow, M.-P., Reiner, N., Neuburger, R., Stowasser, S., Rapp, S., Terstegen, S.: KI-Systeme schützen, Missbrauch verhindern: Maßnahmen und Szenarien in fünf Anwendungsgebieten. Plattform Lernende Systeme (2022).
     
  • 2.
    Henkenjohann, R., Bergner, B., Borchert, F., Bougatf, N., Hund, H., Eils, R., Schapranow, M.-P.: An Engineering Approach towards Multi-Site Virtual Molecular Tumor Board Software Support. In: Pissaloux, E., Papadopoulos, G., Achilleos, A., en Velázquez, R. (reds.) ICT for Health, Accessibility and Wellbeing. IHAW 2021. bll. 156–170. Springer, Cham (2022).
     
  • 3.
    Budde, K., Hiltawsky, K., Kirchner, E., Klevesath, M., Lenarz, T., Neumuth, T., Melzer, A., Schapranow, M.-P., Wolf-Ostermann, K., Löbker, W., Rad, A.J., Zapf, C., Heismann, B., Kara, G., Buttjes, D., Boll, S., Faisst, W., Piller, F.T., Gülpen, C., Susec, B., Nicolay, K.: KI-Geschäftsmodelle für die Gesundheit. Plattform Lernende Systeme (2022).
     
  • 4.
    Borchert, F., Schapranow, M.-P.: HPI-DHC @ BioASQ DisTEMIST: Spanish Biomedical Entity Linking with Pre-trained Transformers and Cross-lingual Candidate Retrieval. Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. bll. 244–258. , Bologna, Italy (2022).
     
  • 5.
    Borchert, F., Lohr, C., Modersohn, L., Witt, J., Langer, T., Follmann, M., Gietzelt, M., Arnrich, B., Hahn, U., Schapranow, M.-P.: GGPONC 2.0 - The German Clinical Guideline Corpus for Oncology: Curation Workflow, Annotation Policy, Baseline NER Taggers. Proceedings of the Language Resources and Evaluation Conference. bll. 3650–3660. European Language Resources Association, Marseille, France (2022).
     

2021

  • 1.
    da Cruz, H.F., Pfahringer, B., Martensen, T., Schneider, F., Meyer, A., Bottinger, E., Schapranow, M.-P.: Using interpretability approaches to update textquotedblleftblack-boxtextquotedblright clinical prediction models: an external validation study in nephrology. Artificial Intelligence in Medicine. 111, 101982 (2021).
     
  • 2.
    Schapranow, M.-P., Loskill, H., Budde, K.: Gibt es ein Recht auf medizinische Behandlung mittels KI?. Management & Krankenhaus. 40, 1 (2021).
     
  • 3.
    Schapranow, M.-P., Loskill, H., Budde, K.: Streitsache: Gibt es ein Recht auf medizinische Behandlung mit KI?. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 14, 96–97 (2021).
     
  • 4.
    Budde, K., Schapranow, M.-P., Kirchner, E., Zahn, T.: Zwischen individualisierten Therapieoptionen und gläsernen Patienten. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 14, 32–36 (2021).
     
  • 5.
    Ganzinger, M., Schapranow, M.-P.: FAIRe Datennutzung: Erfahrungen aus Verbundprojekten. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 14, 57–61 (2021).
     
  • 6.
    Rasheed, A., Borchert, F., Kohlmeyer, L., Henkenjohann, R., Schapranow, M.-P.: A Comparison of Concept Embeddings for German Clinical Corpora. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). bll. 2314–2321 (2021).
     
  • 7.
    Borchert, F., Meister, L., Langer, T., Follmann, M., Arnrich, B., Schapranow, M.-P.: Controversial Trials First: Identifying Disagreement Between Clinical Guidelines and New Evidence. AMIA Annual Symposium Proceedings. bll. 237–246. American Medical Informatics Association (2021).
     
  • 8.
    Borchert, F., Mock, A., Tomczak, A., Hügel, J., Alkarkoukly, S., Knurr, A., Volckmar, A.-L., Stenzinger, A., Schirmacher, P., Debus, J., Jäger, D., Longerich, T., Fröhling, S., Eils, R., Bougatf, N., Sax, U., Schapranow, M.-P.: Knowledge bases and software support for variant interpretation in precision oncology. Briefings in Bioinformatics. 22, (2021).
     
  • 9.
    Schapranow, M.-P.: Schneller Impfen dank Digitalisierung?. Tagesspiegel Background. (2021).
     
  • 10.
    Ganzinger, M., Glaab, E., Kerssemakers, J., Nahnsen, S., Sax, U., Schaadt, N.S., Schapranow, M.-P., Tiede, T.: Biomedical and Clinical Research Data Management. In: Wolkenhauer, O. (red.) Systems Medicine. bll. 532–543. Academic Press, Oxford (2021).
     

2020

  • 1.
    Borchert, F., Lohr, C., Modersohn, L., Langer, T., Follmann, M., Sachs, J.P., Hahn, U., Schapranow, M.-P.: GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines. Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis. bll. 38–48. Association for Computational Linguistics, Online (2020).
     
  • 2.
    Schapranow, M.-P.: Hand in Hand: Wie KI und Ärzte in der Onkologie zusammenarbeiten. Konkrete Anwendungsfälle von KI & Big-Data in der Industrie. 69–74 (2020).
     
  • 3.
    Stegbauer, J.S., Kraus, M., Nordmeyer, S., Kirchner, M., Ziehm, M.Z., Dommisch, H., Kelle, S., Kelm, M., Baczko, I., Landmesser, U., Tschope, C., Knosalla, C., Falcke, M., Schapranow, M.-P., Regitz-Zagrosek, V., Mertins, P., Kühne, T.: Proteomic analysis reveals upregulation of ACE2, the putative SARS-CoV-2 receptor in pressure- but not volume-overloaded human hearts. Hypertension. (2020).
     
  • 4.
    da Cruz, H.F., Pfahringer, B., Martensen, T., Schneider, F., Meyer, A., Bottinger, E., Schapranow, M.-P.: Using Interpretability Approaches to Update Black-Box Clinical Prediction Models: an External Validation Study in Nephrology. Artificial Intelligence in Medicine. 101982 (2020).
     
  • 5.
    Kraus, M., Mathew Stephen, M., Schapranow, M.-P.: Eatomics: Shiny exploration of quantitative proteomics data. Journal of Proteome Research. (2020).
     
  • 6.
    Schapranow, M.-P.: #nCoVStats: Wie Data Science hilft die Coronavirus-Pandemie zu verstehen. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 13, 34–37 (2020).
     
  • 7.
    Schapranow, M.-P.: Good News: Wie Data Science dabei hilft, die Corona-Pandemie besser zu verstehen. Portal Wissen: Das Forschungsmagazin der Universität Potsdam. 9, 14–19 (2020).
     
  • 8.
    Schapranow, M.-P.: Good news: How data science helps us to better understand the Coronavirus pandemic. Portal Wissen: The research magazine of the University of Potsdam. 2, 14–19 (2020).
     
  • 9.
    Schapranow, M.-P.: Schöne neue Ärzte-Welt: Kümmern sich kluge Computer bald um unsere Gesundheitsprobleme?. F.A.Z. Sonderbeliage Gesundheit. B2 (2020).
     
  • 10.
    Borchert, F., Lohr, C., Modersohn, L., Hahn, U., Langer, T., Wenzel, G., Follmann, M., Schapranow, M.-P.: "Herr Doktor, verstehen Sie mich?“: Wie lernende Systeme helfen medizinische Fachsprache zu verstehen und welche Rolle klinische Leitlinien dabei spielen. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 13, 19–22 (2020).
     

2019

  • 1.
    Slosarek, T., Kraus, M., Schapranow, M.-P., Bottinger, E.: Qualitative Comparison of Selected Indel Detection Methods for RNA-Seq Data. International Work-Conference on Bioinformatics and Biomedical Engineering. bll. 166–177. Springer (2019).
     
  • 2.
    Freitas da Cruz, H., Pfahringer, B., Schneider, F., Meyer, A., Schapranow, M.-P.: External Validation of a Black-Box Clinical Predictive Model in Nephrology: Can Interpretability Methods Help Illuminate Performance Differences?. Proceedings of 17th Conference on Artificial Intelligence in Medicine. bll. 191–201 (2019).
     
  • 3.
    Konak, O., Freitas Da Cruz, H., Thiele, M., Golla, D., Schapranow, M.-P.: An Information and Communication Platform Supporting Analytics for Elderly Care. 5th International Conference on Information for Ageing Well, Communication Technologies e Health (2019).
     
  • 4.
    Freitas da Cruz, H., Schneider, F., Schapranow, M.-P.: Prediction of Acute Kidney Injury in Cardiac Surgery Patients: Interpretation using Local Interpretable Model-agnostic Explanations. Proceedings of the 12th International Conference on Biomedical Engineering Systems and Technologies. bll. 380–387. , Prague, Czech Republic (2019).
     
  • 5.
    Konak, O., Freitas Da Cruz, H., Thiele, M., Golla, D., Schapranow, M.-P.: An Information and Communication Platform Supporting Analytics for Elderly Care. 5th International Conference on Information for Ageing Well, Communication Technologies e Health (2019).
     
  • 6.
    Freitas da Cruz, H., Horschig, S., Nusshag, C., Schapranow, M.-P.: Knowledge Distillation from Machine Learning Models for Prediction of Hemodialysis Outcomes. International Journal On Advances in Life Sciences. 11, 33–43 (2019).
     
  • 7.
    Freitas da Cruz, H., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., Schapranow, M.-P.: MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. Proceedings of the 19th IEEE International Conference on Bioinformatics and Biomedicine. , Athens, Greece (2019).
     
  • 8.
    Freitas da Cruz, H., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., Schapranow, M.-P.: MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. Proceedings of the 19th IEEE International Conference on Bioinformatics and Biomedicine (2019).
     
  • 9.
    Schapranow, M.-P.: Für bessere Diagnosen und Therapien: Wie Ärzte und KI in der Krebsbehandlung zusammenarbeiten, https://www.wissenschaftsjahr.de/2019/neues-aus-der-wissenschaft/das-sagt-die-wissenschaft/wie-kuenstliche-intelligenz-das-gesundheitswesen-nachhaltig-unterstuetzt/, (2019).
     
  • 10.
    Schapranow, M.-P., others, and: A Federated In-memory Database System for Life Sciences. In: Castellanos, M., Chrysanthis, P., en Pelechrinis, K. (reds.) Real-Time Business Intelligence and Analytics. BIRTE 2015, BIRTE 2016, BIRTE 2017. Springer, Cham (2019).
     

2018

  • 1.
    Kraus, M., Hesse, G., Slosarek, T., Danner, M., Kesar, A., Bhushan, A., Schapranow, M.-P.: DEAME-Differential Expression Analysis Made Easy. Heterogeneous Data Management, Polystores, and Analytics for Healthcare. bll. 162–174. Springer (2018).
     
  • 2.
    Freitas da Cruz, H., Gebhardt, M., Becher, F., Schapranow, M.-P.: Interactive Data Exploration Supporting Elderly Care Planning. Proceedings of the 10th International Conference on eHealth, Telemedicine, and Social Medicine (2018).
     
  • 3.
    Freitas da Cruz, H., Horschig, S., Nusshag, C., Schapranow, M.-P.: Prediction of Patient Outcomes after Renal Replacement Therapy in Intensive Care. Proceedings of the 3rd International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing (2018).
     

2017

  • 1.
    Schapranow, M.-P.: Die digitale Transformation mitgestalten — Der Datenspendeausweis: Souveräner Umgang mit persönlichen Gesundheitsdaten. Plattform Life Sciences. 38–39 (2017).
     
  • 2.
    Kraus, M., Schapranow, M.-P.: An In-Memory Database Platform for Systems Medicine. Proceedings of the International Conference on Bioinformatics and Computational Biology. bll. 93–100. The International Society for Computers and Their Applications (ISCA) (2017).
     
  • 3.
    Schapranow, M.-P., Brauer, J., Plattner, H.: The Data Donation Pass: Enabling Sovereign Control of Personal Healthcare Data. Proceedings of the World Congress in Computer Science, Computer Engineering, and Applied Computing. CSCE (2017).
     

2016

  • 1.
    Schapranow, M.-P.: Datenspendeausweis für ­Bürger: Ein Plädoyer für mündige Patienten, die die eigenen Gesundheitsdaten am besten verstehen. Management & Krankenhaus. (2016).
     
  • 2.
    Schapranow, M.-P., Uflacker, M., Sariyar, M., Semler, S., Fichte, J., Schielke, D., Ekinci, K., Zahn, T.: Towards An Integrated Health Research Process: A Cloud-based Approach. Proceedings of The IEEE International Conference on Big Data. 2813–2818 (2016).
     
  • 3.
    Schapranow, M.-P.: Die In-Memory-Technologie in der personalisierten Medizin, https://news.sap.com/germany/die-in-memory-technologie-in-der-personalisierten-medizin/, (2016).
     
  • 4.
    Schapranow, M.-P., Kraus, M., Danner, M., Plattner, H.: IMDBfs: Bridging the Gap between In-Memory Database Technology and File-Based Tools for Life Sciences. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine. bll. 1133–1139. IEEE (2016).
     

2015

  • 1.
    Schapranow, M.-P., Perscheid, C., Wachsmann, A., Siegert, M., Bock, C., Horschig, F., Liedke, F., Brauer, J., Plattner, H.: A Federated In-Memory Database System For Life Sciences. Proceedings of the 9th International Workshop on Business Intelligence for the Real Time Enterprise (BIRTE) (2015).
     
  • 2.
    Denecke, K., Mall, S., Fähnrich, C., Perscheid, C., Adeoye, O.O., Benzler, J., Claus, H., Kirchner, G., Richter, R., Schapranow, M.-P., Schwarz, N., Reigl, L., Tom-Aba, D., Gidado, S., Waziri, N.E., Uflacker, M., Krause, G., Poggensee, G.: „Surveillance and Outbreak Response Management and Analysis System (SORMAS)“ ermöglicht Kontrolle von Ebola-Infizierten in Westafrika. 10. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi) (2015).
     
  • 3.
    Fähnrich, C., Schapranow, M.-P., Plattner, H.: Facing the Genome Data Deluge: Efficiently Identifying Genetic Variants with In-Memory Database Technology. Proceedings of the ACM Symposium on Applied Computing (2015).
     
  • 4.
    Schapranow, M.-P., Perscheid, C., Plattner, H.: IT-Aided Business Process Enabling Real-time Analysis of Candidates for Clinical Trials. Proceedings of the 4th International Conference on Global Health Challenges. bll. 67–73. IARIA (2015).
     
  • 5.
    Schapranow, M.-P., Kraus, M., Perscheid, C., Bock, C., Liedtke, F., Plattner, H.: The Medical Knowledge Cockpit: Real-time Analysis of Big Medical Data Enabling Precision Medicine. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM). bll. 770–775 (2015).
     
  • 6.
    Fähnrich, C., Denecke, K., Adeoye, O., Benzler, J., Claus, H., Kirchner, G., Mall, S., Richter, R., Schapranow, M.-P., Schwarz, N.G., Tom-Aba, D., Uflacker, M., Poggensee, G., Krause, G.: Surveillance and Outbreak Response Management System (SORMAS) to support the control of the Ebola virus disease outbreak in West Africa. Euro Surveillance. (2015).
     

2014

  • 1.
    Fähnrich, C., Schapranow, M.-P., Plattner, H.: Towards Integrating the Detection of Genetic Variants into an In-Memory Database. Proceedings of the International Conference on Big Data (2014).
     
  • 2.
    Schapranow, M.-P., Klinghammer, K., Fähnrich, C., Plattner, H.: An Optimized Research Process for Real-time Drug Response Analysis. The Third International Conference on Global Health Challenges (2014).
     
  • 3.
    Schapranow, M.-P., Klinghammer, K., Fähnrich, C., Plattner, H.: In-Memory Technology Enables Interactive Drug Response Analysis. 16th International Conference on e-Health Networking, Applications and Services (Healthcom 2014) (2014).
     
  • 4.
    Haeger, F., Schapranow, M.-P., Fähnrich, C., Ziegler, E., Plattner, H.: In-Memory Computing Enabling Real-time Genome Data Analysis. International Journal on Advances in Life Sciences, Vol 6, Nr 1-2. (2014).
     
  • 5.
    Herbst, K., Fähnrich, C., Neves, M., Schapranow, M.-P.: Applying In-Memory Technology for Automatic Template Filling in the Clinical Domain. CLEF 2014 Evaluation Labs and Workshop, Online Working Notes (2014).
     
  • 6.
    Schapranow, M.-P., Plattner, H.: High-Performance In-Memory Genome Data Analysis: How In-Memory Database Technology Accelerates Personalized Medicine. Springer (2014).
     

2013

  • 1.
    Schapranow, M.-P.: Krebsdatenbank auf Tablet und Smartphone. Best Practice Wireless in der Hauptstadtregion Berlin-Brandenburg, pp. 48-49 (2013).
     
  • 2.
    Schapranow, M.-P., Plattner, H., Meinel, C.: Applied In-Memory Technology for High-Throughput Genome Data Processing and Real-time Analysis. System on Chip (!SoC) Devices in Telemedicine from !LABoC to High Resolution Images, pp. 35-42 (2013).
     
  • 3.
    Haeger, F., Plattner, H., Schapranow, M.-P.: High-Performance In-Memory Genome Project: A Platform for Integrated Real-Time Genome Data Analysis. Proceedings of the 2nd International Conference on Global Health Challenges. bll. 5–10 (2013).
     
  • 4.
    Schapranow, M.-P.: Real-time Security Extensions for EPCglobal Networks: Case Study for the Pharmaceutical Industry. In-Memory Data Management Research, Springer (2013).
     
  • 5.
    Schapranow, M.-P., Meinel, C., Plattner, H.: Applied In-Memory Technology to High Throughput Genome Data Processing. Proceedings of XXI Winter Course of the CATAI (CATAI 2013). bll. 35–42. , Canary Islands, Spain (2013).
     
  • 6.
    Schapranow, M.-P., Plattner, H.: HIG – An In-memory Database Platform Enabling Real-time Analyses of Genome Data. Proceedings of the International Conference on Big Data. bll. 691–696 (2013).
     
  • 7.
    Schapranow, M.-P., Meinel, C., Plattner, H.: Big Data soll Genom-Analysen schneller voranbringen. Krankenhaus-IT Journal, p. 26. (2013).
     
  • 8.
    Schapranow, M.-P., Plattner, H.: In-Memory Technology Enables History-Based Access Control for RFID-Aided Supply Chains. The Secure Information Society: Ethical, Legal and Political Challenges, pp. 187-213 (2013).
     
  • 9.
    Schapranow, M.-P., Plattner, H., Tosun, C., Regenbrecht, C.: Mobile Real-time Analysis of Patient Data for Advanced Decision Support in Personalized Medicine. The 5th International Conference on eHealth, Telemedicine, and Social Medicine, pp. 129-136 (2013).
     

2012

  • 1.
    Plattner, H., Meinel, C., Schapranow, M.-P.: Blitzschnelle Datenanalysen für die personalisierte Medizin der Zukunft – Interdisziplinäre Impulse aus Potsdam und Berlin. Themenbroschüre 2012 Gesundheitsstandort Berlin-Brandenburg. (2012).
     
  • 2.
    Müller, J., Schapranow, M.-P., Zeier, A., Plattner, H.: Secure RFID-Enablement in Modern Companies: A Case Study of the Pharmaceutical Industry. Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and Solutions, pp. 507-539, IGI Global (2012).
     
  • 3.
    Schapranow, M.-P., Meinel, C., Plattner, H.: Datenbanktechnologie beflügelt personalisierte Medizin. Laborwelt Nr. 4/2012, 13. Jahrgang. (2012).
     

2011

  • 1.
    Schapranow, M.-P., Müller, J., Zeier, A., Plattner, H.: What are Authentic Pharmaceuticals Worth?. Designing and Deploying RFID Applications, pp. 204-220, INTECH Press (2011).
     
  • 2.
    Schapranow, M.-P., Zeier, A., Plattner, H.: A Formal Model for Enabling RFID in Pharmaceutical Supply Chains. 44th Hawaii International Conference on System Sciences (HICSS). IEEE (2011).
     
  • 3.
    Schapranow, M.-P., Lorenz, M., Zeier, A., Plattner, H.: License-based Access Control in EPCglobal Networks. The 7th European Workshop on RFID Systems and Technologies, pp. 1-7 (2011).
     
  • 4.
    Schapranow, M.-P., Zeier, A., Plattner, H., Müller, J., Lorenz, M.: Discovery Services in the EPC Network. Designing and Deploying RFID Applications, pp. 109-130, INTECH Press (2011).
     
  • 5.
    Schapranow, M.-P., Zeier, A., Leupold, F., Schubotz, T.: Securing EPCglobal Object Name Service -- Privacy Enhancements for Anti-counterfeiting. 2nd International Conference on Intelligent Systems, Modeling and Simulation, pp. 332-337 (2011).
     
  • 6.
    Zeier, A., Plattner, H., Schapranow, M.-P., Müller, J.: Costs of Authentic Pharmaceuticals: Research on Qualitative and Quantitative Aspects of Enabling Anti-counterfeiting in RFID-aided Supply Chains. Personal and Ubiquitous Computing, Volume 16, Issue 3. 271–289 (2011).
     
  • 7.
    Schapranow, M.-P., Fähnrich, C., Zeier, A., Plattner, H.: Simulation of RFID-aided Supply Chains: Case Study of the Pharmaceutical Supply Chain. Third International Conference on Computational Intelligence, Modelling and Simulation, pp. 340-345 (2011).
     
  • 8.
    Lorenz, M., Müller, J., Schapranow, M.-P., Zeier, A.: A Distributed EPC Discovery Service based on Peer-to-peer Technology. Proceedings of the RFID SysTech 2011, 7th European Workshop on Smart Objects: Systems, Technologies and Applications, Dresden. bll. 1–7. VDE (2011).
     
  • 9.
    Schapranow, M.-P., Zeier, A., Plattner, H.: Security Extensions for Improving Data Security of Event Repositories in EPCglobal Networks. The 9th International Conference on Embedded and Ubiquitous Computing pp. 213-220 (2011).
     

2010

  • 1.
    Schapranow, M.-P., Nagora, M., Zeier, A.: CoMoSeR: Cost Model for Security-Enhanced RFID-Aided Supply Chains. The 18th International Conference on Software, Telecommunication and Computer Networks, pp. 11-16 (2010).
     
  • 2.
    Schapranow, M.-P., Kühne, R., Zeier, A.: Real-Time Billing in Smart Grid Infrastructures. Power and Energy Student Summit 2010 - Integration of Renewable Energies into the Grid (2010).
     
  • 3.
    Müller, J., Schapranow, M.-P., Pöpke, C., Urbat, M., Zeier, A., Plattner, H.: Best Practices for Rigorous Evaluation of RFID Software Components. Proceedings of the 6th European Workshop on RFID Systems and Technologies (RFID !SysTech’10), Ciudad Real, Spain (2010).
     
  • 4.
    Schapranow, M.-P., Zeier, A., Plattner, H.: A Dynamic Mutual RFID Authentication Model Preventing Unauthorized Third Party Access. The 4th International Conference on Network and System Security, , pp. 371-376 (2010).
     
  • 5.
    Schapranow, M.-P., Kühne, R., Zeier, A.: Enabling Real-Time Charging for Smart Grid Infrastructures using In-Memory Databases. 1st IEEE LCN Workshop on Smart Grid Networking Infrastructure (2010).
     
  • 6.
    Schapranow, M.-P., Geller, F., Lorenz, M., Müller, J., Kowark, T., Zeier, A.: Assessment of Communication Protocols in the EPC Network: Replacing Textual SOAP and XML with Binary Google Protocol Buffers Encoding. 17th IEEE International Conference on Industrial Engineering and Engineering Management (IE&EM), Xiamen, China (2010).
     
  • 7.
    Schapranow, M.-P., Müller, J., Zeier, A., Plattner, H.: RFID Event Data Processing -- An Architecture for Storing and Searching. Proceedings of the 4th International Workshop on RFID Technology - Concepts, Applications, Challenges, Funchal, Madeira, Portugal (2010).
     

2009

  • 1.
    Schapranow, M.-P., Müller, J., Zeier, A., Plattner, H.: Security Aspects in Vulnerable RFID-Aided Supply Chains. Proceedings of the 5th European Workshop on RFID Systems and Technologies, Bremen (2009).
     
  • 2.
    Borovskiy, V., Müller, J., Schapranow, M.-P., Zeier, A.: Ensuring Service Backwards Compatibility with Generic Web Services. Proceedings of ICSE 2009, PESOS Workshop, Vancouver, Canada (2009).
     
  • 3.
    Schapranow, M.-P., Müller, J., Krüger, J., Hofmann, P., Zeier, A.: Integration of RFID Technology is a Key Enabler for Demand-Driven Supply Network. The IUP Journal of Supply Chain Management, Volume 6, Nos. 3 & 4, pp. 57-74. (2009).
     
  • 4.
    Müller, J., Faust, M., Schwalb, D., Schapranow, M.-P., Zeier, A., Plattner, H.: A Software as a Service RFID Middleware for Small and Medium-sized Enterprises. Proceedings of the 5th European Workshop on RFID Systems and Technologies (RFID !SysTech’09), Bremen, Germany (2009).
     
  • 5.
    Müller, J., Schapranow, M.-P., Helmich, M., Enderlein, S., Zeier, A.: RFID Middleware as a Service - Enabling Small and Medium-sized Enterprises to Participate in the EPC Network. 16th International Conference on Industrial Engineering and Engineering Management (IE&EM), Beijing, China (2009).
     
  • 6.
    Schapranow, M.-P., Krüger, J., Borovskiy, V., Zeier, A., Plattner, H.: Data Loading & Caching Strategies in Service-Oriented Enterprise Applications. Proceedings of IEEE Congress on Services (SERVICES 2009), Los Angeles, CA, USA (2009).
     
  • 7.
    Schapranow, M.-P., Zeier, A., Borovskiy, V., Müller, J.: Binary Search Tree Visualization Algorithm. 16th International Conference on Industrial Engineering and Engineering Management (IE&EM), Beijing, China (2009).
     
  • 8.
    Zeier, A., Schapranow, M.-P., Krüger, J., Uflacker, M., Müller, J.: noFilis CrossTalk 2.0 as Device Management Solution, Experiences while Integrating RFID Hardware into SAP Auto-ID Infrastructure. Proceedings of the 16th International Conference on Industrial Engineering and Engineering Management (IE&EM), Beijing, China (2009).
     
  • 9.
    Schapranow, M.-P., Müller, J., Enderlein, S., Helmich, M., Zeier, A.: Low-Cost Mutual RFID Authentication Model Using Predefined Password Lists. The 16th International Conference on Industrial Engineering and Engineering Management, pp. 889-893 (2009).
     

2008

  • 1.
    Schapranow, M.-P., Grund, M., Krüger, J., Schaffner, J., Bog, A.: Combining Advantages - Unified Data Stores in Global Enterprises. IEEE Symposium on Advanced Management of Information for Globalized Enterprises (AMIGE’08), Tianjin, China (2008).
     
  • 2.
    Grund, M., Schaffner, J., Schapranow, M.-P., Bog, A., Krüger, J.: Operational Reporting Using Navigational SQL. IEEE Symposium on Advanced Management of Information for Globalized Enterprises (AMIGE’08), Tianjin, China (2008).
     
  • 3.
    Schapranow, M.-P., Krüger, J.: HPI Students Learn with SAP Enterprise Services. SAP INFO (online). (2008).
     
  • 4.
    Krüger, J., Grund, M., Schaffner, J., Schapranow, M.-P., Bog, A.: Shared Table Access Pattern Analysis for Multi-Tenant Applications. IEEE Symposium on Advanced Management of Information for Globalized Enterprises (AMIGE’08), Tianjin, China (2008).
     
  • 5.
    Schapranow, M.-P., Krüger, J., Müller, J.: Smart Enterprise Widgets: Little Helpers with a Big Impact. SAP INFO (online). (2008).
     

Teaching Activities

Theses Topics

Miscellaneous