Dipl.-Inf. Nico Schlitter

Dipl.-Inf. Nico Schlitter


Short CV:

05/2011 - today

Research Associate at Faculty of Computer Science, University of Applied Science Zittau/Görlitz

06/2008 - today

Founder, Project Manager and Researcher in the distributedDataMining project

11/2010 - 04/2011
6 months

IT Consultant for an Internet Start-Up in Melbourne, Australia
Management of the company's IT Infrastructure

04/2009 - 10/2010
1.5 years

Freelancer as IT Consultant & Trainer in the field of Data Analysis

09/2006 - 03/2009
2.5 years

Research Associate in the NGM BMWi project Ko-RFID at Faculty of Computer Science, Otto-von-Guericke-University Magdeburg
Conceptual Design of RFID-based Data Analysis for Process Optimization in a Global Supply Chain (including Organizational & IT Requirements, Data Privacy Protection, and Prototype Implementation)

04/2004 - 03/2006
2 years

Tutor at Faculty of Computer Science, Technical University Chemnitz
Conceptual Design and Implementation of Exercises and Hands-on Trainings in the field of Artificial Intelligence, Machine Learning, and Software Development

10/2004 - 03/2005
6 months

Data Analysis at enviaM AG
Modeling, Implementation, and Evaluation of Failure Prediction in the high-voltage power grid

02/2002 - 03/2004
2 years

Data Analysis at prudsys AG
Benchmarking & Comparison of non-linear Classification Methods (prudsys Discoverer vs. SAS Enterprise Miner)

Publications:

Schlitter N, Lässig J. Distributed Privacy Preserving Classification Based on Local Cluster Identifiers.; Submitted.

Schlitter N, Lässig J. Market Simulation of Smart Grids with Adaptive Transmission Fees; In Press.

Schlitter N, Falkowski T, Lässig J. DenGraph-HO: Density-based Hierarchical Community Detection for Explorative Visual Network Analysis. In: Proceedings of the 31st SGAI International Conference on Artificial Intelligence (AI 2011). Cambridge, UK; In Press.

Schlitter N, Falkowski T. Mining the Dynamics of Music Preferences from a Social Networking Site. In: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining. Athens: IEEE Computer Society; 2009. p. 243-8. 

Schlitter N. A Protocol for Privacy Preserving Neural Network Learning on Horizontal Partitioned Data. In: Privacy Statistics in Databases (PSD) 2008. Istanbul,Turkey; 2008. on CD.

Falkowski T, Schlitter N. Analyzing the Music Listening Behavior and its Temporal Dynamics Using Data from a Social Networking Site. Zurich; 2008. Presented at The 5th conference on Applications of Social Network Analysis (ASNA)

Schlitter N, Schilz ST. Strategischer IKT-Einsatz schafft Wettbewerbsvorteile durch unternehmensübergreifendes Data Mining. In: Teich T, Schumann C, Dürr H, Gäse T, editors. Tagungsband ZFPro'08. Plauen: M&S-Verlags-OHG; 2008. p. 25-34. download Schlitter N. Analyse und Prognose ökonomischer Zeitreihen: Neuronale Netze zur Aktienkursprognose. Saarbrücken: VDM Verlag Dr. Müller; 2008.

Möller M, Schlitter N. Analyse und Prognose ökonomischer Zeitreihen mit Support Vector Machines. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Jahre Künstliche Intelligenz an der Fakultät für Informatik. Chemnitz: Techn. Univ. Chemnitz, Fak. für Informatik; 2008. p. 189-201. (Chemnitzer Informatik-Berichte).

Schlitter N. A Case Study of Time Series Forecasting with Backpropagation Networks. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Jahre Künstliche Intelligenz an der TU Chemnitz. Chemnitz: Techn. Univ. Chemnitz, Fak. für Informatik; 2008. p. 203-17. (Chemnitzer Informatik-Berichte). 

Schlitter N, Schilz ST, Kähne F. Funkchips liefern Produktdaten - Kategorisierung durch Datamining vereinfacht die Qualitätskontrolle. Computer Zeitung. 2008.

Rauch-Gebbensleben B, Kähne F, Horton G, Schlitter N, Schilz ST, Neike M. Ein Simulationsmodell zur Nachbildung von unternehmensübergreifenden Produktionsfehlern. In: Advances in simulation for production and logistics applications.; 2008. p. 309-18.

Schlitter N. RFID-basiertes integriertes Data Mining zur Manufakturfehlerprognose.; 2008. Presented at Research-/VDI Seminar of department of Mechanical Engineering, Chemnitz University of Technology 2007

Schlitter N. Improving Time Series Forecasting With Backpropagation Networks. Freiburg; 2007. Presented at The 31st Annual Conference of the GfKl on Data Analysis, Machine Learning, and Applications

Schlitter N, Kähne F, Schilz ST, Mattke H. Potentials and problems of RFID-based cooperations in supply chains. In: Kersten W, Blecker T, Herstatt C, editors. Innovative Logistics Management: Competitive Advantages through new Processes and Services. Berlin: Erich Schmidt Verlag GmbH & Co.; 2007. p. 147-64. 

Schilz ST, Schlitter N, Kähne F, Genc E. RFID Rollout – What Can We Learn From EDI? In: Blecker T, Huang GQ, Salvador F, editors. Key Factors for Successful Logistics: Services, Transportation Concepts, IT and Management Tools. Berlin: Erich Schmidt Verlag GmbH & Co.; 2007. p. 153-68.

Short CV

05/2011 - 04/2012

Research Associate at Faculty of Computer Science, University of Applied Science Zittau/Görlitz

06/2008 - today

Founder, Project Manager and Researcher in the distributedDataMining project

11/2010 - 04/2011
6 months

IT Consultant for an Internet Start-Up in Melbourne, Australia
Management of the company's IT Infrastructure

04/2009 - 10/2010
1.5 years

Freelancer as IT Consultant & Trainer in the field of Data Analysis

09/2006 - 03/2009
2.5 years

Research Associate in the NGM BMWi project Ko-RFID at Faculty of Computer Science, Otto-von-Guericke-University Magdeburg
Conceptual Design of RFID-based Data Analysis for Process Optimization in a Global Supply Chain (including Organizational & IT Requirements, Data Privacy Protection, and Prototype Implementation)

04/2004 - 03/2006
2 years

Tutor at Faculty of Computer Science, Technical University Chemnitz
Conceptual Design and Implementation of Exercises and Hands-on Trainings in the field of Artificial Intelligence, Machine Learning, and Software Development

10/2004 - 03/2005
6 months

Data Analysis at enviaM AG
Modeling, Implementation, and Evaluation of Failure Prediction in the high-voltage power grid

02/2002 - 03/2004
2 years

Data Analysis at prudsys AG
Benchmarking & Comparison of non-linear Classification Methods (prudsys Discoverer vs. SAS Enterprise Miner)

Publications

Schlitter N, Lässig J. Distributed Privacy Preserving Classification Based on Local Cluster Identifiers; Submitted.

Schlitter N, Lässig J. Market Simulation of Smart Grids with Adaptive Transmission Fees; In Press.

Schlitter N, Falkowski T, Lässig J. DenGraph-HO: Density-based Hierarchical Community Detection for Explorative Visual Network Analysis. In: Proceedings of the 31st SGAI International Conference on Artificial Intelligence (AI 2011). Cambridge, UK; In Press.

Schlitter N, Falkowski T. Mining the Dynamics of Music Preferences from a Social Networking Site. In: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining. Athens: IEEE Computer Society; 2009. p. 243-8. 

Schlitter N. A Protocol for Privacy Preserving Neural Network Learning on Horizontal Partitioned Data. In: Privacy Statistics in Databases (PSD) 2008. Istanbul,Turkey; 2008. on CD.

Falkowski T, Schlitter N. Analyzing the Music Listening Behavior and its Temporal Dynamics Using Data from a Social Networking Site. Zurich; 2008. Presented at The 5th conference on Applications of Social Network Analysis (ASNA)

Schlitter N, Schilz ST. Strategic use of ICT creates competitive advantages through cross-company data mining. In: Teich T, Schumann C, Dürr H, Gäse T, editors. Proceedings ZFPro'08. Plauen: M&S-Verlags-OHG; 2008. p. 25-34. download Schlitter N. Analysis and forecasting of economic time series: Neural Networks for Stock Price Forecasting. Saarbrücken: VDM Verlag Dr. Müller; 2008.

Möller M, Schlitter N. Analysis and forecasting of economic time series with support vector machines. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Years of Artificial Intelligence at the Faculty of Computer Science. Chemnitz: Chemnitz University of Technology, Faculty of Computer Science; 2008. p. 189-201. (Chemnitzer Informatik-Berichte).

Schlitter N. A Case Study of Time Series Forecasting with Backpropagation Networks. In: Steinmüller J, Langner H, Ritter M, Zeidler J, editors. 15 Years of Artificial Intelligence at the TU Chemnitz. Chemnitz: Chemnitz University of Technology, Faculty of Computer Science; 2008. p. 203-17. (Chemnitzer Informatik-Berichte). 

Schlitter N, Schilz ST, Kähne F. Radio chips provide product data - categorization through data mining simplifies quality control. Computer Zeitung. 2008.

Rauch-Gebbensleben B, Kähne F, Horton G, Schlitter N, Schilz ST, Neike M. A simulation model for the simulation of cross-company production errors. In: Advances in simulation for production and logistics applications; 2008. p. 309-18.

Schlitter N. RFID-based integrated data mining for manufacturing defect prediction; 2008. Presented at Research-/VDI Seminar of department of Mechanical Engineering, Chemnitz University of Technology 2007

Schlitter N. Improving Time Series Forecasting With Backpropagation Networks. Freiburg; 2007. Presented at The 31st Annual Conference of the GfKl on Data Analysis, Machine Learning, and Applications

Schlitter N, Kähne F, Schilz ST, Mattke H. Potentials and problems of RFID-based cooperations in supply chains. In: Kersten W, Blecker T, Herstatt C, editors. Innovative Logistics Management: Competitive Advantages through new Processes and Services. Berlin: Erich Schmidt Verlag GmbH & Co; 2007. p. 147-64. 

Schilz ST, Schlitter N, Kähne F, Genc E. RFID Rollout - What Can We Learn From EDI? In: Blecker T, Huang GQ, Salvador F, editors. Key Factors for Successful Logistics: Services, Transportation Concepts, IT and Management Tools. Berlin: Erich Schmidt Verlag GmbH & Co; 2007. p. 153-68.