Niklas Lavesson

Professor Datateknik

Avdelningen för Datateknik och Informatik , Tekniska Högskolan i Jönköping AB

Forskning

Niklas Lavessons forskning är fokuserad mot praktisk tillämpning av verktyg och tekniker från maskininlärning i samarbete med partners från den offentliga och privata sektorn. Mer specifikt undersöker Lavesson reella problem i olika domäner och försöker modellera, utveckla, samt utvärdera prestandan hos, dataintensiva lösningar, baserat på teori och metoder från artificiell intelligens, informationsutvinning och maskininlärning.

Biografi

Niklas Lavesson är sedan den 1 november 2017 professor i datateknik vid Tekniska Högskolan i Jönköping AB. Lavesson erhöll teknologie magisterexamen i programvaruteknik (2003) samt teknologie doktorsexamen i datavetenskap (2008) från Blekinge Tekniska Högskola. Han har tidigare varit anställd som universitetslektor i datavetenskap (2009-2015) och blev utnämnd till oavlönad docent i datavetenskap (2011) vid samma lärosäte. Lavesson blev befordrad till professor i datavetenskap vid Blekinge Tekniska Högskola i maj 2015 och innehar fortfarande denna tjänst på deltid.

Lavesson har alltid närt ett starkt intresse för tredje uppgiften. Han har medverkat i Sveriges Television för att diskutera de potentiella samhälleliga konsekvenserna av AI och han har även medverkat vid flera tillfällen i Sveriges Radio för att diskutera olika ämnen. De senaste radiointervjuerna med P4 Blekinge behandlar exempelvis: maskininlärning för att minska spridningen av så kallad hämndporr i sociala medier (9 nov 2017), digitalisering och smarta hem (12 okt 2017), artificiell intelligens (16 maj 2017) samt digitalisering och AI-trender (5 jan 2017). Lavesson är flitigt anlitad i paneler samt som talare vid olika arrangemang som rör digitalisering, artificiell intelligens och maskininlärning för organisationer, stiftelser, företag, skolor och myndigheter.

Lavesson påbörjade sin karriär inom undervisning som amanuens (2003) vid Blekinge Tekniska Högskola och har sedan dess innehaft olika undervisning och ledningsroller inom ramen för över 20 kurser på högskolenivå. Parallellt med arbetet som lärare, examinator, kursansvarig och programansvarig för olika kurser och program inom datavetenskap och programvaruteknik så har Lavesson innehaft flertalet förtroendeuppdrag relaterade till akademiska rättigheter, administration och utveckling. Han var ordförande för doktorandsektionen vid Blekinge Tekniska Högskola (2007-2008) och koordinator för forskarutbildningen vid samma lärosäte, utsedd av fakultetsnämnden (2009-2013).

Lavesson underhåller ett brett nätverk inom akademin så väl som i den offentliga och privata sektorn. Han är en flitigt anlitad granskare av artiklar inskickade till välrenommerade tidskrifter, exempelvis: Data & Knowledge Engineering, Empirical Software Engineering, Information Sciences, Information & Software Technology, Knowledge & Information Systems, Machine Learning, Machine Learning Research, Neurocomputing, och Transactions on Internet Technology.

Lavesson är återkommande granskare eller medlem i programkommittén till ett större antal topprankade vetenskapliga konferenser. De senaste exemplen är: AISTATS 2018, ICLR 2018, AAAI 2017, ECML/PKDD 2017, IJCAI 2017, och NIPS 2017.

Niklas Lavesson handleder för närvarande sex doktorander, fyra som huvudhandledare och två som bihandledare (samtliga inskrivna vid Blekinge Tekniska Högskola). Han är dessutom medlem eller extern granskare i tiotalet stöd- eller utvecklingskommittéer för andra doktorander. Han har tidigare agerat som handledare för två doktorsavhandlingar och mer än 25 master-, magister- eller kandidatuppsatser. Lavesson har agerat opponent eller medverkat i betygsnämnden för 12 doktorander.

Lavesson har publicerat mer än 60 fackgranskade tidskriftsartiklar, konferensartiklar, monografier och bokkapitel. För en komplett förteckning, besök hans Google Scholar-profil.

Antologibidrag

García Martín, E., Lavesson, N., Grahn, H. (2017). Energy Efficiency Analysis of the Very Fast Decision Tree Algorithm. In: Rokia Missaoui, Talel Abdessalem, Matthieu Latapy (Ed.), Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment (pp. 229 -252). Cham, Switzerland: Springer More information
Johnson, H., Lavesson, N., Zhao, H., Wu, S. (2011). On the Concept of Trust in Online Social Networks. In: Salgarelli, Luca; Bianchi, Giuseppe; Blefari-Melazzi, Nicola (Ed.), Trustworthy Internet (pp. 143 -157). More information
Kostadinova, E., Boeva, V., Lavesson, N. (2011). Clustering of Multiple Microarray Experiments Using Information Integration. In: Böhm, C. (Ed.), Information Technology in Bio- and Medical Informatics (pp. 123 -137). More information
Lavesson, N., Davidsson, P., Boldt, M., Jacobsson, A. (2008). Spyware Prevention by Classifying End User License Agreements. In: Nguyen, Ngoc Thanh; Katarzyniak, Radoslaw (Ed.), New Challenges in Applied Intelligence Technologies (pp. 373 -382). Berlin / Heidelberg: Springer More information

Artikel

Shao, B., Lavesson, N., Boeva, V., Shahzad, R. (2016). A mixture-of-experts approach for gene regulatory network inference International Journal of Data Mining and Bioinformatics, 14(3), 258-275. More information
Martin, E., Lavesson, N., Doroud, M. (2016). Hashtags and followers An experimental study of the online social network Twitter Social Network Analysis and Mining, 6(1). More information
Unterkalmsteiner, M., Feldt, R., Gorschek, T., Lavesson, N. (2016). Large-scale Information Retrieval in Software Engineering - An Experience Report from Industrial Application Journal of Empirical Software Engineering, 21(6), 2324-2365. More information
Beyene, A., Welemariam, T., Persson, M., Lavesson, N. (2015). Improved concept drift handling in surgery prediction and other applications Knowledge and Information Systems, 44(1), 177-196. More information
Borg, A., Boldt, M., Lavesson, N., Melander, U., Boeva, V. (2014). Detecting serial residential burglaries using clustering Expert systems with applications, 41(11), 5252-5266. More information
Lavesson, N., Boeva, V., Elena, T., Davidsson, P. (2014). A method for evaluation of learning components Automated Software Engineering: An International Journal, 21(1), 41-63. More information
Shahzad, R., Lavesson, N. (2013). Comparative Analysis of Voting Schemes for Ensemble-based Malware Detection Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 4(1), 98-117. More information
Kazemi, S., Abghari, S., Lavesson, N., Johnson, H., Ryman, P. (2013). Open Data for Anomaly Detection in Maritime Surveillance Expert systems with applications, 40(14), 5719-5729. More information
Rezaee, S., Lavesson, N., Johnson, H. (2012). E-Mail Prioritization using Online Social Network Profile Distance International Journal of Computer Science and Applications, 9(1), 70-87. More information
Lavesson, N., Axelsson, S. (2012). Similarity assessment for removal of noisy end user license agreements Knowledge and Information Systems, 32(1), 167-189. More information
Lavesson, N., Boldt, M., Davidsson, P., Jacobsson, A. (2011). Learning to detect spyware using end user license agreements Knowledge and Information Systems, 26(2), 285-307. More information
Lavesson, N. (2010). Learning Machine Learning: A Case Study IEEE Transactions on Education, 53(4), 672-676. More information
Lavesson, N., Davidsson, P. (2007). Evaluating learning algorithms and classifiers International Journal of Intelligent Information and Database Systems, 1(1), 37-52. More information

Doktorsavhandling

Lavesson, N. (2008). On the Metric-based Approach to Supervised Concept Learning (Doctoral thesis, Ronneby: Blekinge Institute of Technology). More information

Konferensbidrag

Abghari, S., García Martín, E., Johansson, C., Lavesson, N., Grahn, H. (2017). Trend analysis to automatically identify heat program changes. 15th International Symposium on District Heating and Cooling (DHC2016), Seoul. More information
García Martín, E., Lavesson, N., Grahn, H. (2017). Identification of Energy Hotspots: A Case Study of the Very Fast Decision Tree. Cham, Switzerland: Springer, GPC 2017 : The 12th International Conference on Green, Pervasive and Cloud Computing, Cetara, Amalfi Coast, Italy. More information
García-Martín, E., Lavesson, N. (2017). Is it ethical to avoid error analysis?. 2017 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017). More information
Kusetogullari, H., Grahn, H., Lavesson, N. (2017). Handwriting image enhancement using local learning windowing, Gaussian Mixture Model and k-means clustering. 2016 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2016, Limassol. More information
Dasari, S., Lavesson, N., Andersson, P., Persson, M. (2015). Tree-Based Response Surface Analysis. The International Workshop on Machine learning, Optimization and big Data (MOD 2015), Taormina - Sicily, Italy. More information
Isaksson, O., Bertoni, M., Hallstedt, S., Lavesson, N. (2015). Model Based Decision Support for Value and Sustainability in Product Development. 20th International Conference on Engineering Design (ICED),Milan. More information
Shahzad, R., Mehwish, F., Lavesson, N., Boldt, M. (2015). Consensus decision making in random forests. International Workshop on Machine learning, Optimization and big Data, Taormina, Sicily. More information
García Martín, E., Lavesson, N., Grahn, H. (2015). Energy Efficiency in Data Stream Mining. Int’l Symp. on Foundations and Applications of Big Data Analytics (FAB 2015), Paris. More information
Borg, A., Lavesson, N., Boeva, V. (2013). Comparison of clustering approaches for gene expression data. Scandinavian Conference on Artificial Intelligence SCAI 2013. More information
Davidsson, P., Gustafsson Friberger, M., Lavesson, N., Persson, J. (2013). Towards a Prediction Model for People Movements in Urban Areas. MASS2013, 1st International Workshop on Multiagent-based Societal Systems, Saint Paul, Minnesota, USA, 7th May, 2013. More information
Borg, A., Lavesson, N. (2012). E-mail Classification using Social Network Information. Prague, Czech Republic: IEEE, Seventh International Conference on Availability, Reliability and Security. More information
Shahzad, R., Lavesson, N. (2012). Veto-based Malware Detection. Seventh International Conference on Availability, Reliability and Security. More information
Allahyari, H., Lavesson, N. (2011). User-oriented Assessment of Classification Model Understandability. Trondheim: IOS Press, 11th Scandinavian Conference on Artificial Intelligence. More information
Bhattacharyya, P., Rowe, J., Wu, F., Haigh, K., Lavesson, N., Johnson, H. (2011). Your Best might not be Good enough: Ranking in Collaborative Social Search Engines. Orlando: IEEE Press, Seventh International Conference on Collaborative Computing: Networking, Applications and Worksharing. More information
Borg, A., Boldt, M., Lavesson, N. (2011). Informed Software Installation through License Agreement Categorization. Johannesburg: IEEE Press, Information Security for South Africa. More information
Lavesson, N., Johnson, H. (2011). Measuring Profile Distance in Online Social Networks. Sogndal: ACM Press, International Conference on Web Intelligence, Mining and Semantics. More information
Shahzad, R., Lavesson, N. (2011). Extended Abstract: Detecting Scareware by Mining Variable Length Instruction Sequences. Trondheim: IOS Press, 11th Scandinavian Conference on Artificial Intelligence. More information
Grahn, H., Lavesson, N., Lapajne, M., Slat, D. (2011). CudaRF: A CUDA-based Implementation of Random Forests. Sharm El-Sheikh, Egypt: IEEE, 9th ACS/IEEE Int'l Conference on Computer Systems And Applications (AICCSA 2011). More information
Shahzad, R., Lavesson, N., Johnson, H. (2011). Accurate Adware Detection using Opcode Sequence Extraction. Vienna: IEEE Press, Sixth International Conference on Availability, Reliability and Security. More information
Shahzad, R., Lavesson, N. (2011). Detecting Scareware by Mining Variable Length Instruction Sequences. Johannesburg: IEEE Press, Information Security for South Africa. More information
Boeva, V., Ivanova, P., Lavesson, N. (2010). A Hybrid Computational Method for the Identification of Cell Cycle-regulated Genes. London: IEEE Press, IEEE Intelligent Systems. More information
Grahn, H., Lavesson, N., Lapajne, M., Slat, D. (2010). A CUDA Implementation of Random Forests: Early Results. Göteborg: Chalmers Institute of Technology, Third Swedish Workshop on Multi-core Computing. More information
Shahzad, R., Haider, S., Lavesson, N. (2010). Detection of Spyware by Mining Executable Files. Krakow: IEEE Computer Society, The Fifth International Conference on Availability, Reliability and Security (ARES 2010). More information
Lavesson, N., Davidsson, P. (2010). APPrOVE: Application-oriented Validation and Evaluation of Supervised Learners. London: IEEE Press, IEEE Intelligent Systems. More information
Lavesson, N. (2010). Predicting the Risk of Future Hospitalization. Bilbao: IEEE Press, Second International Workshop on Database Technology for Data Management in Life Sciences and Medicine. More information
Persson, M., Lavesson, N. (2009). Identification of Surgery Indicators by Mining Hospital Data: A Preliminary Study. Linz, Austria: IEEE Press, 20th International Workshop on Database and Expert Systems Applications. More information
Muhammad, A., Lavesson, N., Davidsson, P., Nilsson, M. (2009). Analysis of Speed Sign Classification Algorithms Using Shape Based Segmentation of Binary Images. Munster: Springer, 13th International Conference on Computer Analysis of Images and Patterns Munster, GERMANY, SEP 02-04, 2009. More information
Lavesson, N., Halling, A., Freitag, M., Odeberg, J., Odeberg, H., Davidsson, P. (2009). Classifying the Severity of an Acute Coronary Syndrome by Mining Patient Data. Linköping: Linköping University Electronic Press, 25th Annual Workshop of the Swedish Artificial Intelligence Society. More information
Boldt, M., Jacobsson, A., Lavesson, N., Davidsson, P. (2008). Automated Spyware Detection Using End User License Agreements. Busan, Korea: IEEE, 2nd International Conference on Information Security and Assurance. More information
Lavesson, N., Davidsson, P. (2008). Towards Application-specific Evaluation Metrics. Helsinki The 3rd workshop on Evaluation Methods for Machine Learning. More information
Lavesson, N., Davidsson, P. (2008). Generic Methods for Multi-criteria Evaluation. Atlanta, Georgia, USA: SIAM Press, SIAM International Conference on Data Mining. More information
Lavesson, N., Davidsson, P., Boldt, M., Jacobsson, A. (2008). Spyware Prevention by Classifying End User License Agreements. Wroclaw, Poland: Springer, 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. More information
Lavesson, N., Davidsson, P. (2007). Analysis of Multi-Criteria Methods for Classifier and Algorithm Evaluation. 24th Annual Workshop of the Swedish Artificial Intelligence Society. More information
Lavesson, N., Davidsson, P. (2006). Quantifying the Impact of Learning Algorithm Parameter Tuning. Boston, USA The Twenty-First National Conference on Artificial Intelligence (AAAI-06). More information
Lavesson, N., Davidsson, P. (2005). Quantifying the Impact of Learning Algorithm Parameter Tuning (short version). Västerås: Mälardalen University, 3rd Joint SAIS/SLSS Workshop. More information
Lavesson, N., Davidsson, P. (2004). A Multi-dimensional Measure Function for Classifier Performance. Varna, Bulgaria: IEEE, 2nd IEEE International Conference on Intelligent Systems. More information

Licentiatavhandling

Lavesson, N. (2006). Evaluation and Analysis of Supervised Learning Algorithms and Classifiers (Licentiate thesis, Karlskrona: Blekinge Institute of Technology). More information

Samlingsverk

(2013). Mining the Digital Information Networks. More information
(2012). Social Shaping of Digital Publishing: Exploring the Interplay Between Culture and Technology - Proceedings of the 16th International Conference on Electronic Publishing. Amsterdam: IOS Press More information

Övrigt

García Martín, E., Lavesson, N., Grahn, H., Casalicchio, E., Boeva, V. . Hoeffding Trees with nmin adaptation. More information






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