Peter van der Putten
Assistant professor
- Name
- Dr. P.W.H. van der Putten
- Telephone
- +31 71 527 7033
- p.w.h.van.der.putten@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-6507-6896
How can machines learn from interaction? Or how can phenomena such as intelligence, creativity or more in general, complex behaviour emerge from simple parts? Big questions of course, but nonetheless fascinating. I enjoy studying these questions as a researcher in the Data Mining Group as well as in the Media Technology program at the Leiden Institute of Advanced Computer Science at Leiden University in the Netherlands. Next to that I apply these methods in industry, most recently as the Director of Decisioning Solutions at Pegasystems, and I also have experience with start-ups, both as an employee and as an informal advisor. I am a member of the interdisciplinary research programme Society, Artificial Intelligence and Life Sciences (SAILS).
More information about Peter van der Putten
News
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Hollywood strike: Is AI really a threat to actors? -
Five tips for Museum Night Leiden -
Peter van der Putten on Robo Rabbi and a robot that performs funeral rituals -
Leiden researchers work on exhibition about growth addiction -
SAILS Summer Conference on Law & AI -
BNAIC/Benelearn conference big success -
Bots like you -
CRITTERS Exposition: a photo impression -
What robots can teach us about humans -
Media Technology lecturers in NVON's magazine Terugkoppeling
See also
Former PhD candidates
Peter van der Putten is a part time researcher at LIACS. He is a member of the interdisciplinary research programme Society, Artificial Intelligence and Life Sciences (SAILS). His background is in artificial intelligence and he is particularly interested how intelligence can evolve through learning, in man or machines. Peter has a MSc in Cognitive Artificial Intelligence from Utrecht University and a PhD in data mining from Leiden University, and combines academic research with applying these technologies in business. He teaches New Media New Technology ( 2011, 2012, 2013, 2014, 2015) and supervises MSc thesis projects.
Peter holds office in room 123 of the Snellius building. He works part-time for the Media Technology MSc program, so schedule an appointment if you want to meet.
Assistant professor
- Science
- Leiden Inst of Advanced Computer Science
- Duijn M.J. van, Dijk B.M.A. van, Kouwenhoven T., Valk W. de, Spruit M. & Putten P.W.H. van der (2023), Theory of mind in large language models: examining performance of 11 state-of-the-art models vs. children aged 7-10 on advanced tests. Jiang J., Reitter D. & Deng S. (Eds.), Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL). 27th Conference on Computational Natural Language Learning (CoNLL) 6 December 2023 - 7 December 2023. Singapore: Association for Computational Linguistics. 389–402.
- Tseng R., Verberne S. & Putten P.W.H. van der (2023), ChatGPT as a commenter to the news: can LLMs generate human-like opinions?. Ceolin D., Caselli T. & Tulin M. (Eds.), Disinformation in Open Online Media. MISDOOM 2023: lecture notes in computer science. MISDOOM 2023: Disinformation in Open Online Media 21 November 2023 - 22 November 2023 no. 14397. Cham: Springer. 160–174.
- Congleton C., Putten P.W.H. van der & Verberne S. (2022), Tracing political positioning of Dutch newspapers. Spezzano F., Amaral A., Ceolin D., Fazio L. & Serra E. (Eds.), Disinformation in Open Online Media. MISDOOM 2022. 4th Multidisciplinary International Symposium, MISDOOM 2022 11 October 2022 - 12 October 2022. Lecture Notes in Computer Science no. 13545. Cham: Springer. 27-43.
- Fragkiadakis M., Nyst V.A.S. & Putten P.W.H. van der (2021), Towards a user-friendly tool for automated sign annotation: identification and annotation of time slots, number of hands, and handshape, Digital Humanities Quarterly 15(1): .
- Fragkiadakis M. & Putten P.W.H. van der (2021), Sign and search: sign search functionality for sign language lexica. In: Shterionov D. (Ed.) Proceedings of machine translation summit VXIII. East Stroudsburg: Association for Machine Translation in the Americas. 23-32.
- Siebelt M., Das D., Moosdijk A. van den, Warren T., Putten P.W.H. van der & Weegen W. van der (2021), Machine learning algorithms trained with pre-hospital acquired history-taking data can accurately differentiate diagnoses in patients with hip complaints, Acta Orthopaedica 92(3): 254-257.
- Schreuter D., Putten P.W.H. van der & Lamers M.H. (2021), Trust me on this one: conforming to conversational assistants, Minds and Machines 31: 535-562.
- Mason C., Putten P.W.H. van der & Duijn M. van (2020), How identity and uncertainty affect online social influence. Duijn M.J. van, Preuss M., Spaiser V., Takes F. & Verberne S. (Eds.), Disinformation in open online media. Second Multidisciplinary International Symposium. MISDOOM 2020 26 October 2020 - 27 October 2020. Lecture Notes in Computer Science no. 12259. Cham: Springer. 174-190.
- Fragkiadakis M., Nyst V.A.S. & Putten P.W.H. van der (2020), Signing as input for a dictionary query: matching signs based on joint positions of the dominant hand, Proceedings of the 9th Workshop on the Representation and Processing of Sign Languages. The 12th Language Resources and Evaluation Conference (LREC) 2020 11 May 2020 - 16 May 2020. Marseille: European Language Resources Association (ELRA). 69-74.
- Lamers M.H., Putten P.W.H. van der & Azurin K.A. 28 February 2019, ROBOpod: Part 1 – Eccentric Electric. Ars Leonardocast. Leonardo/ISAST [podcast].
- Putten P.W.H. van der & Lamers M.H. (2018), Bots Like You, Terugkoppeling, periodiek van de Nederlandse Vereniging voor het Onderwijs in de Natuurwetenschappen 27(1): 14-16.
- Lamers M.H. & Putten P.W.H. van der (2018), Speels Onderzoek, Terugkoppeling, periodiek van de Nederlandse Vereniging voor het Onderwijs in de Natuurwetenschappen 27(1): 6-8.
- Hees M. van, Putten P.W.H. van der & Lamers M.H. (2018), "Disciples of the Heinous Path: Exploring Label Structure in Heavy Metal Genres". Atzmueller M. & Duivestein W. (Eds.), 30th Benelux Conference on Artificial Intelligence. Benelearn 2018: The annual machine learning conference of the Benelux 8 November 2018 - 9 November 2018.
- Strang B., Putten P.W.H. van der, Rijn J.N. van & Hutter F. (2018), Don't Rule Out Simple Models Prematurely: A Large Scale Benchmark Comparing Linear and Non-linear Classifiers in OpenML. Duivesteijn W., Siebes A. & Ukkonen A. (Eds.), Advances in Intelligent Data Analysis XVII 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. International Symposium on Intelligent Data Analysis IDA 2018 24 October 2018 - 26 October 2018 no. Lecture Notes in Computer Science, volume 11191. Cham: Springer. 303-315.
- Boven B. van, Putten P.H.W. van der, Åström A., Khalafi H. & Plaat A. (2018), Real-Time Excavation Detection at Construction Sites using Deep Learning. Duivesteijn W., Siebes A. & Ukkonen A. (Eds.), Advances in Intelligent Data Analysis XVII 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. International Symposium on Intelligent Data Analysis IDA 2018 24 October 2018 - 26 October 2018 no. Lecture Notes in Computer Science, volume 11191. Cham: Springer International Publishing. 340-352.
- Verkoelen S.D., Lamers M.H. & Putten P.W.H. van der (2017), Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines. Correia J., Ciesielski V. & Liapis A. (Eds.), Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017). Lecture Notes in Computer Science. 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017) 19 April 2017 - 21 April 2017 no. 10198. Cham: Springer. 321-337.
- Arenas Rebolledo Y.S., Putten P.W.H. van der & Lamers M.H. (2017), Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation Through a Human Creativity Test. Correia J., Ciesielski V. & Liapis A. (Eds.), Computational Intelligence in Music, Sound, Art and Design. 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017) 19 April 2017 - 21 April 2017 no. LNCS 10198. Cham: Springer. 262-274.
- Radosavljevik D. & Putten P.W.H. van der (2017), Service Revenue Forecasting in Telecommunications: A Data Science Approach. Duivesteijn W., Pechenizkiy M., Fletcher G., Menkovski V., Postma E., Vanschoren J. & Putten P.W.H. van der (Eds.), Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning.. Benelearn 2017: The annual machine learning conference of the Benelux 9 June 2017 - 10 June 2017 187-189.
- Duivesteijn W., Pechenizkiy M., Fletcher G., Menkovski V., Postma E., Vanschoren J. & Putten P.W.H. van der (Eds.) (2017), Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning. Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning (Benelearn 2017).
- Soekhoe D., Putten P. van der & Plaat A. (2016), On the Impact of Data Set Size in Transfer Learning Using Deep Neural Networks. Boström H., Knobbe A., Soares C. & Papapetrou P. (Eds.), Advances in Intelligent Data Analysis XV - 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings. The 15th International Symposium on Intelligent Data Analysis 13 October 2016 - 15 October 2016 no. 9897. Cham: Springer International Publishers. 50-60.
- Post M.J., Putten P.W.H. van der. & Rijn J.N. van (2016), Does Feature Selection Improve Classification? A Large Scale Experiment in OpenML. Boström H., Knobbe A., Soares C. & Papapetrou P. (Eds.), Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings (Lecture Notes in Computer Science). The 15th International Symposium on Intelligent Data Analysis 13 October 2016 - 15 October 2016 no. 9897. Cham: Springer International Publishing. 158-170.
- Teernstra L., Putten P.W.H. van der, Noordegraaf-Eelens L. & Verbeek F.J. (2016), The morality machine: tracking moral values in tweets. Boström H., Knobbe A., Soares C. & Papapetrou P. (Eds.), Advances in intelligent data analysis XV. The 15th International Symposium on Intelligent Data Analysis 13 October 2016 - 15 October 2016. Lecture Notes in Computer Science no. 9897. Cham: Springer International Publishing. 26-37.
- Lamers M.H., Putten P.W.H. van der & Verbeek F.J. (2014), Observations on Tinkering in Scientific Education. In: Cheok A.D., Nijholt A. & Romão T. (Eds.), Entertaining the Whole World. Human-Computer Interaction Series. London: Springer-Verlag. 137-145.
- Mohd Hafeez Bin Osman H., Chaudron M.R.V., Putten P.W.H. van der & Ho-Quang Truong (2014), Condensing Reverse Engineered Class Diagrams through Class Name Based Abstraction, Proceedings 2014 World Congress on Information and Communication Technologies (WICT). .
- Radosavljevikj D. & Putten P.W.H. van der (2014), Large Scale Predictive Modeling for Micro-Simulation of 3G Air Interface Load, Proceedings 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2014). 1620-1629.
- Mohd Hafeez Bin Osman H., Chaudron M.R.V. & Putten P.W.H. van der (2014), Interactive Scalable Abstraction of Reverse Engineered UML Class Diagrams, Proceedings 21st Asia-Pacific Software Engineering Conference (APSEC 2014). .
- Li H., Putten P.W.H. van der & Keijzer M. (2014), Improving Preference Based Modeling By Capturing Correlations Among Features [Abstract], Proceedings 23rd Annual Belgian Dutch Conference on Machine Learning (BENELEARN 2014). 6.
- Mohd Hafeez Bin Osman H., Chaudron M.R.V. & Putten P.W.H. van der (2014), Condensing Reverse Engineered Class Diagram using Text Mining no. TR 2014-02. Leiden, The Netherlands: LIACS, Leiden University.
- Mohd Hafeez Bin Osman H., Chaudron M.R.V. & Putten P.W.H. van der (2013), An Analysis of Machine Learning Algorithms for Condensing Reverse Engineered Class Diagrams, 29th IEEE International Conference on Software Maintenance (ICSM), 2013. International Conference on Software Maintenance 22 September 2013 - 28 September 2013: IEEE. 140-149.
- Lamers Maarten H., Verbeek F.J. & Putten P.W.H. van der (2013), Tinkering in Scientific Education. Reidsma D., Katayose H. & Nijholt A. (Eds.), Advances in Computer Entertainment. no. Lecture Notes in Computer Science 8253: Springer-Verlag. 568-571.
- Kusuma P.D., Radosavljevic D., Takes F.W. & Van der Putten P.W.H. (2013), Combining Customer Attributes and Social Network Mining for Prepaid Mobile Churn Prediction, Proceedings of the 22th Belgian Dutch Conference on Machine Learning (Benelearn). 22th Belgian Dutch Conference on Machine Learning 50-58.
- Li H., Putten P.W.H. van der & Keijzer M. (2013), Recommending Products using Preference Based Modeling, Proceedings 23rd Annual Belgian Dutch Conference on Machine Learning (Benelearn 2013). 59-67.
- Radosavljevik D. & Putten P.W.H. van der (2013), Preventing Churn in Telecommunications: The Forgotten Network, Proceedings Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013. no. Lecture Notes in Computer Science 357-368.
- Radosavljevik D., Putten P.W.H. van der & Kyllesbech Larsen K. (2012), Mass Scale Modeling and Simulation of the Air-Interface Load in 3G Radio Access Networks, Proceedings The Eleventh International Symposium on Intelligent Data Analysis (IDA 2012). 25-27.
- Osman Hafeez, Chaudron M.R.V. & Putten P.W.H. van der (2012), Classifying Presence of Classes in UML Design using Software Metrics, Proceedings BENELEARN 2012. 76-76.
- Heijer G.J. den, Putten P.W.H. van der, Benard E.L., Meijer A.H. & Verbeek F.J. (2012), Explorations in Texture Based Classification for Bacterial Infection in Zebrafish. Baets B. de, Manderick B., Rademaker M. & Waegeman W. (Eds.), BeneLearn 2012 : proceedings of the 21st Belgian-Dutch conference on machine learning. 21st Belgian-Dutch conference on Machine Learning (BeneLearn 2012) 24 May 2012 - 25 May 2012 13-18.
- Putten P.W.H. van der, Kok J.N. & Meng L.J. (2011), Profiling Novel Classification Algorithms: Artificial Immune Systems, Proceedings Seventh IEEE International Conference on Cybernetic Intelligent Systems 2008 (CIS 2008). .
- Kentsch A., Kosters W.A., Putten P.W.H. van der & Takes F.W. (2011), Exploratory Recommendations using Wikipedia's Linking Structure, Proceedings of 20th Belgian Netherlands Conference on Machine Learning (Benelearn). 61-68.
- Radosavljevik D., Putten P.W.H. van der & Kyllesbech Larsen K. (2011), Customer Satisfaction and Network Experience in Mobile Telecommunications, Proceedings 20th Annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2011). 91-92.
- Putten P.W.H. van der, Veenman C., Vanschoren J., Israel M. & Blockeel H. (Eds.) (2011), Proceedings of the 20th Annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2011). The Hague: Universiteit Leiden.
- Radosavljevik D., Putten P.W.H. van der & Kyllesbech Larsen K. (2010), The Impact of Experimental Setup in Prepaid Churn Prediction for Mobile Telecommunications: What to Predict, from Whom and does the Customer Experience Matter?, Transactions on Machine Learning and Data Mining 3(2): 80-99.
- Putten P.W.H. van der & Kok J.N. (2010), Using Data Fusion to Enrich Customer Databases with Survey Data for Database Marketing. In: Casillas Jorge & Martinez Lopez Francisco Jose (Eds.), Marketing Intelligent Systems Using Soft Computing.
- Putten P.W.H. van der (2010), Data Fusion for Direct Marketing, Joint Meeting GfKl - CLADAG 2010. CLADAG 2010.
- Israel M., Schaar J. van der, Broek E.L. van den, Uyl M. den & Putten P.W.H. van der (2010), Multi-Level Visual Alphabets, Proceedings International Conference on Image Processing Theory, Tools and Applications (IPTA 2010). International Conference on Image Processing Theory, Tools and Applications (IPTA 2010).
- Radosavljevik D., Putten P.W.H. van der & Kyllesbech Larsen K. (2010), The Impact of Experimental Setup on Prepaid Churn Modeling: Data, Population and Outcome Definition, Workshop on Data Mining in Marketing (DMM 2010). Workshop on Data Mining in Marketing (DMM 2010), Berlin, Germany.
- Putten P.W.H. van der (19 January 2010), On data mining in context : cases, fusion and evaluation (Dissertatie. Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University). Supervisor(s): Kok J.N.
- Putten P.W.H. van der, Melli G. & Kitts B. (2009), Proceedings of the Third International Workshop on Data Mining Case Studies (DMCS 2009). New Jersey: ACM SIGKDD.
- Putten P.W.H. van der, Bertens L.M.F., Liu J., Hagen F., Boekhout T. & Verbeek F.J. (2007), Classification of yeast cells from image features to evaluate pathogen conditions. Hanjalic A., Schettini R. & Sebe N. (Eds.), Proc. SPIE 6506: Multimedia content access: algorithms and systems. MultiMedia Content Access: Algorithms & Systems. SPIE Proceedings no. 6506: SPIE.
- Paauwe P., Putten P.W.H. van der & Wezel M.C. van (2007), DMTC: An Actionable e-Customer Lifetime Value Model Based on Markov Chains and Decision Trees, Proceedings of the Ninth International Conference on Electronic Commerce: The Wireless World of Electronic Commerce 2007. . ACM International Conference Proceedings Series.
- Israel M., Broek E.L. van den, Putten P.W.H. van der & Uyl M. den (2006), Visual Alphabets: Video Classification by End Users. In: Petrushin V.A. & Khan L. (Eds.), Multimedia Data Mining and Knowledge Discovery: Springer.
- Liu J., Putten P.W.H. van der, Hagen F., Chen X., Boekhout T. & Verbeek F.J. (2006), Detecting virulent cells of Cryptococcus neoformans yeast: clustering experiments. Tang Y., Wang P., Lorette G. & So Yeung D. (Eds.), Proceedings of the 18th international conference on pattern recognition ICPR2006. 18th International Conference on Pattern Recognition (ICPR'06) 20 August 2006 - 20 August 2006 no. 4: IEEE. 1112-1115.
- Putten P.W.H. van der, Koudijs A.E. & Walker R. (2006), A Decision Management Approach to Basel II Compliant Credit Risk Management, KDD-2006 Workshop Data Mining for Business Applications. .
- Putten P.W.H. van der & Kok J.N. (2005), Data mining and knowledge discovery. In: Baatenburg de Jong R.J. (Ed.), Prognosis in Head and Neck Cancer: Taylor and Francis.
- Meng L.J., Putten P.W.H. van der & Wang H. (2005), A Comprehensive Benchmark of the Artificial Immune Recognition System (AIRS). Li X., Wang S. & Yang Dong Z. (Eds.), Proceedings of the First International Conference on Advanced Data Mining and Applications (ADMA 2005). 575-582.
- Putten P.W.H. van der & Meng L.J. (2005), Benchmarking the AIRS Artificial Immune System for Classification. Verbeeck K., Tuyls K., Nowé A., Manderick B. & Kuijpers B. (Eds.), Proceedings of the 17th Belgian-Dutch Conference on Artificial Inteligence (BNAIC 2005). 393-394.
- Putten P.W.H. van der (2002), Advertising Strategy Discovery. In: Meij J. (Ed.), Dealing with the Data Flood: Mining Data, Text and Multimedia. The Hague: STT Netherlands. 247-261.
- Putten P.W.H. van der (2002), Matching. In: Meij J. (Ed.), Dealing with the Data Flood: Mining Data, Text and Multimedia. The Hague: STT. 308-319.
- Putten P.W.H. van der (2002), Analytical Customer Relationship Management for Insurance Policy Prospects. In: Meij J. (Ed.), Dealing with the Data Flood: Mining Data, Text and Multimedia. The Hague: STT Netherlands. 293-297.
- Putten P.W.H. van der, Ramaekers M., Uyl M. den & Kok J.N. (2002), A Process Model for a Data Fusion Factory, Proc. 14th Belgian-Dutch Conference on Artificial Intelligence. 251-258.
- Putten P.W.H. van der, Kok J.N. & Gupta G. (2002), Why the Information Explosion Can Be Bad for Data Mining and How Data Fusion Provides a Way Out, Second SIAM International Conference on Data Mining. .
- Putten P.W.H. van der & Wurff A. van der (1998), De invoering van database marketing systemen. In: Hoogers J. (Ed.), CustomerBase Jaarboek '99. Amersfoort: F&G Publishing. 119-128.
- Director Decisioning Solutions