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Humboldt-Universität zu Berlin -

Prof. Dr. Stefan Lessmann

Professional homepage of Prof. Dr. Stefan Lessmann (HU Berlin)
   

Telefon: +49 30 2093-5742
Email: stefan.lessmann[at]hu-berlin.de
Raum: SPA1, 327

Sprechstunde:

  • Bachelor + Master, Mi., 10.00 - 11.00

Die Sprechstunde ist stark frequentiert. Bitte vereinbaren Sie unbedingt einen Termin bei Frau Bujarek.

 

Short-Bio

Stefan received a diploma in business administration and a PhD from the University of Hamburg in 2002 and 2007, respectively. He worked as a lecturer and senior lecture in business informatics at the Institute of Information Systems of the University of Hamburg. Since 2008, Stefan is a guest lecturer at the School of Management of the University of Southampton, where he teaches under- and postgraduate courses on quantitative methods, electronic business, and web application development. Stefan completed his habilitation in the area of predictive analytics in 2012. He then joined the Humboldt-University of Berlin in 2014, where he heads the Chair of Information Systems at the School of Business and Economics. Stefan published several papers in leading international journals and conferences, including the European Journal of Operational Research, the IEEE Transactions of Software Engineering, and the International Conference on Information Systems. He actively participates in knowledge transfer and consulting projects with industry partners; from small start-up companies to global players.

 

Research interests

Stefan’s work focuses on the analysis and support managerial decision making. Much of his research is concerned with the development, application, and validation of empirical prediction models. The degree to which such models actually support managers and how to improve their alignment with managers’ requirements represent typical research questions.

Topics of interest include, for example:

  • Artificial neural networks, deep learning, and recurrent neural network architectures
  • Big Data Analytics
  • Credit risk modeling using regression, classification and survival analysis
  • Ensemble models and forecast combination
  • Marketing and E-Commerce analytics (e.g., churn management, customer lifetime value, online marketing, customer targeting, real-time bidding)
  • Non-standard paradigms to learn from data (active learning, adversarial learning, learning with privileged information, PU learning, semi-supervised learning, …)
  • Sentiment and social network analysis
  • Time series forecasting (e.g., in finance or demand planning)

 

Social Media

View Stefan Lessmann's profile on LinkedIn View Stefan Lessmann's profile on LinkedIn View profile on Xing

 

 

Selected publications (complete list of publications)

S. Lessmann, B. Baesens, H.-V. Seow, L. C. Thomas. Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research. European Journal of Operational Research, (doi:10.1016/j.ejor.2015.05.030)

H. Brandner, S. Lessmann, S. Voß. A memetic approach to construct transductive discrete support vector machines. European Journal of Operational Research, 230(3), 581-595 (2013)

S. Lessmann, M.-C. Sung, J.E.V. Johnson, T. Ma. A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction. European Journal of Operational Research 218(1), 163-174 (2012)

S. Lessmann, M. Listiani, S. Voß. Decision Support in Car Leasing: A Forecasting Model for Residual Value Estimation. In: M. Lacity, F. Niederman, S. March (Eds.) Proc. of the Intern. Conf. on Information Systems (ICIS’10), Saint Louis, MO, USA (2010)

S. Lessmann, S. Voß. Customer-centric decision support: A bench­marking study of novel versus established classification models. Business & Information Systems Engineering 2(2), 79-93 (2010)

 

Grants and distinctions

Governmentally funded research

2014

Managing Efficiency in High Risk Environments

Andalusian Regional Government for Excellence Research Project Initiative 
(Excellence Project P12-SEJ-1933)

25.300 €

2013

Developing a State-Of-The Art Trading Dashboard

Economic and Social Research Council, Technology Strategy Board, and Star Financial Systems Ltd.
(Knowledge Transfer Partnership Project: KTP009163)

304.900 £


 

Development of a Real-Time Model of Spread-Trader Performance

Economic and Social Research Council, Technology Strategy Board, and London Capital Group Holdings plc.
(Knowledge Transfer Partnership Project: KTP8952)

148.500 £

2012

Modelling and prediction of spread-trader and contract for difference trader risk

Technology Strategy Board and Star Financial Systems Ltd.
(Knowledge Transfer Partnership Project: SKTP1000767)

59.450 £

2011

Classification and prediction of financial market trading behaviour

Technology Strategy Board and Worldspreads Ltd.
(Knowledge Transfer Partnership Project: KTP8504)

149.600 £

2008 & 2011

Funding of Technical Equipment to Facilitate Research in Predictive Analytics

University of Hamburg

~20.000 €

2002 - present

Travel Grants

Various travel grants from universities and other academic institutions to support conference attendance, research exchanges or summer schools.

~15.000 €

 

Corporate research projects and knowledge transfer

2014

Development of application scorecards using state-of-the-art classification algorithms

Customer: leading US retail bank

Development of tailor-made workshop targeted at business analysts and data scientists.

Scope:

  • Basic and advanced classification algorithms
  • Predictive modeling theory (curse of dimensionality, overfitting, bias-variance trade-off)
  • Predictive modeling process (data preparation, model selection and assessment)
  • Analytics software packages

2014

Optimization of Marketing Resource Utilization

Customer: leading company in the German DIY market

Contracted joint research project with DMC - Dialogmarketing Consulting GmbH aiming at:

  • Development of a decision-centric database to support analytical customer relationship management
  • Development of explanatory models to identify sales drivers scrutinize the effectiveness of the client’s marketing communication
  • Strategy development to enhance the client’s marketing policy and increase marketing ROI

2009 - 2010

Demand Planning in Maritime Logistics

Customer: leading international logistic services company

Contracted joint research project with the Centre for Forecasting, Lancaster Business School and RSG Software GmbH aiming at:

  • Devise a classification of demand time series,
  • Develop statistical and computational-intelligence-based forecasting models for individual time series categories,
  • Implement fully-functional forecasting support system embodying these models.

2005

Data Mining for Cross-Selling Magazine Subscriptions

Customer: leading international publishing house

Contracted research aiming at:

  • Assess in-house decision support models resulting from tree-based algorithms in SPSS Clementine,
  • Explore the potential of artificial neural networks and support vector machines to increase predictive accuracy in subscription cross-selling,
  • Examine the impact of data pre-processing procedures on prediction models and develop optimal data encoding schemes.

 

Professional activity and recognition
Editorships

  • Associate Editor of the Deparment Computational Methods and Decision Support Systems, Business Information and Systems Engineering (BISE)
  • M. Abou-Nasr, S. Lessmann, R. Stahlbock, G. M. Weiss (Eds). Real World Data Mining Applications – Special Issue in Annals of Information Systems. Vol. 17. Springer: Berlin (2015)
  • R. Stahlbock, S.F. Crone, S. Lessmann (Eds). Data Mining – Special Issue in Annals of Information Systems. Vol. 8. Springer: Berlin (2010)
  • R. Stahlbock, S.F. Crone, S. Lessmann (Eds.). Proceedings of International Conference on Data Mining (DMIN). CSREA Press: Las Vegas (2006, 2007, 2008, 2009)

Reviewing

Peer-reviewing service for various leading international journals and conferences in operational research and information systems; including: BISE, DSS, ECIS, EJOR, ICIS, IEEE TSE, IEEE TKDE, IJF, JORS, OMEGA, amongst others.