Martin Boldt
Senior lecturer/Associate professor
Department of Computer Science, Room J3120
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About Martin Boldt
I’m an associate professor (Docent/Ph.D.) in computer science at Blekinge Institute of Technology in Sweden. As a member of the Department of Computer Science my main research focus is on data analysis using various data science methods, e.g., artificial intelligence and machine learning. I was pro-perfect for the department in 2021 and am currently the unit leader for the Artificial Intelligence and Data Analytics lab (AIDA), which is one of the units within the department.
Research-wise, I’m currently working on industrial fault prediction using machine learning together with NKT, which produces power cables (mainly for underwater installation). I’m also working in two research projects funded by Swedish Research Council (2023-2025) and Länsförsäkringars forskningsfond (2021-2024), respectively. Both projects are carried out together with Malmö University and the Swedish Police. The projects focus on applied research within computational criminology, i.e., criminology and computer science (specifically applied machine learning). The projects evolve around data-driven approaches for various analyses of the relationship between crime and CCTV in a Swedish setting.
Previously I worked on a project funded by the Knowledge Foundation during 2014-2020, titled Scalable resource-efficient systems for big data analytics. In that project, I was involved in studies with Ericsson Research regarding methods for anomaly detection and fault prediction in telecom base stations (patent pending). Also, together with Telenor we analyze customer support efficiency by analyzing e-mail conversations using intelligent models. In prior research projects, I have co-operated with the Swedish Police and the Swedish National Forensic Centre by focusing on the mitigation of serial volume crime. More information about the cooperation with the police is available here (in Swedish).
I’m currently the main supervisor for two Ph.D. students. Jim Ahlstrand is an industrial Ph.D. student at Telenor who investigates the use and potential of data-driven machine learning models in customer life cycles in corporate settings. A bit more info here (in Swedish). The second Ph.D. student is Kenneth Lewenhagen, who is doing research on the intersection between computer science and criminology within the previously mentioned projects funded by Swedish Research Council and Länsförsäkringars forskningsfond. I’m also one of the supervisors for Mona Tykesson Klubien who works at the Department of Criminology at Malmö university. I have also been a supervisor for four Ph.D. students that have finished; Anton Borg (2014), Fredrik Erlandsson (2018), Ana Moraes (2020), and Khurram Shahzad (2024).
When it comes to commissions of trust commitments, I’m the general chair for the 35th Swedish Artificial Intelligence Society (SAIS’23) annual workshop in Karlskrona in June 2023. I have been the general chair for IEEE EISIC’18, and a member of the program committee for various conferences. I have had several commitments at the local university, e.g., teacher-representative on the university board, a member of the university’s teacher review committee, and the examiner for Master’s thesis projects in computer science. Currently, I’m mainly the unit leader (including personnel responsibility) of the AIDA team and the program manager for the five-year educational program in AI and machine learning. Finally, I’m peer-reviewing and have reviewed manuscripts for various journals, conferences, and workshops, e.g., ECML, NIPS, AISTATS, UAI, LOD.
Ongoing work
Martin Boldt, “GraphSpotter: A Scalable Graph-based Crime Hot Spot Predictor”, journal manuscript, 2024.
Kenneth Lewenhagen, Martin Boldt, Anton Borg, Karl Kronqvist, Manne Gerell, “A web-based system for analysis of surveillance camera placements”, conference manuscript, 2024.
Submitted
Martin Boldt, Kenneth Lewenhagen, Anton Borg, Karl Kronqvist, Manne Gerell, “A Data-Driven Graph-Based Method for Hot Spot Prediction and CCTV Camera Placement”, journal manuscript, 2024.
Accepted (in press)
Jim Ahlstrand, Martin Boldt, Anton Borg and Håkan Grahn, “Predicting B2B Customer Churn using a Time Series Approach “, accepted for publication in proceedings of the International Conference on Intelligent Data Science Technologies and Applications (IDSTA), 2024
Gustav Nilsson, Martin Boldt, Sadi Alawadi, “The Impact of Data Quality on Distributed vs. Centralized Learning”, accepted for publication in proceedings of the 9th International Conference on Fog and Mobile Edge Computing (FMEC) , 2024. DOI: 10.1109/FMEC62297.2024.10710311
Victor Arvidsson, Sadi Alawadi, Martin Boldt, Ola Angelsmark, Fanny Söderlund, “A Novel Approach for Intrusion Detection using Online Federated Learning on Streaming Data”, accepted for publication in proceedings of the 9th International Conference on Fog and Mobile Edge Computing (FMEC) , 2024. DOI: 10.1109/FMEC62297.2024.10710218
Kenneth Lewenhagen, Martin Boldt, Anton Borg, “Automated Generation of CCTV Camera Coverage Areas for Smart Cities Using Line-of-Sight Analysis”, accepted for publication in proceedings of the 14th Workshop on Management of Cloud and Smart city systems (MoCS), 2024.
Published work
In journals/books (peer-reviewed)
Karl Kronkvist, Anton Borg, Martin Boldt, Manne Gerell, “Predicting Public Violent Crime using Register and OpenStreetMap Data: A Risk Terrain Modeling Approach across Three Cities of Varying Size”, in Applied Spatial Analysis and Policy, ISI impact factor: 2.00, 2024. DOI: 10.1007/s12061-024-09609-3
Lars Lundberg, Martin Boldt, Anton Borg and Håkan Grahn, “Bibliometric Mining of Research Trends in Machine Learning”, in AI, 5(1), 2024. DOI: 10.3390/ai5010012
Martin Boldt, Anton Borg, Selim Ickin, Valentin Kulyk and Jörgen Gustafsson, “Alarm prediction in cellular base stations using data-driven methods”, in IEEE Transactions on Network and Service Management, ISI impact factor: 3.878, 2021. DOI: 10.1109/TNSM.2021.3052093
Anton Borg, Jim Ahlstrand and Martin Boldt,”Improving Corporate Support by Predicting Customer e-Mail Response Time: Experimental Evaluation and a Practical Use Case”, in Springer Lecture Notes in Business Information Processing, volume 417, 2021. DOI: 10.1007/978-3-030-75418-1_6
Anton Borg, Martin Boldt and Johan Svensson, “Using conformal prediction for multi-label document classification in e-mail support systems”, in Springer Lecture Notes in Computer Science, volume 11606, 2021. DOI: 10.1007/978-3-030-22999-3_28
Anton Borg and Martin Boldt, “Using VADER Sentiment and SVM for predicting customer response sentiment”, accepted in journal Expert Systems With Applications, ISI impact factor: 5.452, 2020. DOI: 10.1016/j.eswa.2020.113746
Anton Borg, Jim Ahlstrand and Martin Boldt, “Improving Corporate Support by Predicting Customer E-mail Response Time: Experimental Evaluation and a practical Use Case”, accepted in Springer’s Lecture Notes in Business Information Processing, 2020. DOI: 10.1007/978-3-030-75418-1_6
Ana Luiza Dallora , Ola Kvist, Johan Sanmartin Berglund, Sandra Diaz Ruiz, Martin Boldt, Carl-Erik Flodmark, Peter Anderberg, “Chronological Age Assessment in Young Individuals Using Bone Age Assessment Staging and Nonradiological Aspects: Machine Learning Multifactorial Approach”, in JMIR Medical Informatics, ISI impact factor: 2.580, 2020. DOI: 10.2196/18846
Anton Borg, Martin Boldt, Oliver Rosander and Jim Ahlstrand, “Decision support system for e-mail classification using machine learning and word embeddings for improved customer support”, accepted in journal of Neural Computing and Applications, Springer, ISI impact factor: 3.570, 2020. DOI: 10.1007/s00521-020-05058-4
Martin Boldt, Anton Borg, Selim Ickin, and Jörgen Gustafsson, “Anomaly detection of event sequences using multiple temporal resolutions and Markov chains”, in Knowledge and Information Systems, Springer, 62, ISI impact factor: 2.247, 2019. DOI: 10.1007/s10115-019-01365-y
Martin Boldt and Kaavya Rekanar, “On the analysis and binary classification of privacy policies from both rogue and top 100 Fortune global companies”, in International Journal of Information Security and Privacy, Volume 13, Issue 2, ISI impact factor: 0.550, 2019. DOI: 10.4018/IJISP.2019040104
Martin Boldt, “An evaluation of the efficiency and quality of structured crime reports”, in Nordic Journal of Policing Studies, volume 5, issue 1, 2018.,DOI: 10.18261/issn.1894-8693-2018-01-06. [PDF]
Martin Boldt, Anton Borg, Martin Svensson, and Jonas Hildeby, “Predicting burglars’ risk exposure and level of pre-crime preparation using crime scene data”, in Journal of Intelligent Data Analysis, volume 22, issue 1, ISI impact factor: 0.631, 2018. [PDF]
Martin Boldt, Andreas Jacobsson, Dejan Baca, and Bengt Carlsson, “Introducing a novel security-enhanced agile software development process”, in International Journal of Secure Software Engineering, volume 8, issue 2, 2017, DOI: 10.4018/IJSSE.2017040102.
Fredrik Erlandsson, Piotr Bródka, Martin Boldt, and Henric Johnson, “Do we really need to catch them all? User-guided social media crawling method”, in Entropy, volume 19, issue 12, ISI impact factor: 1.821, 2017. [PDF]
Martin Boldt and Anton Borg, “Evaluating temporal analysis methods using residential burglary data”, in International Journal of Geo-Information – Special Issue “Frontiers in Spatial and Spatiotemporal Crime Analytics”, ISI impact factor: 1.502, 2016, DOI: 10.3390/ijgi5090148
Anton Borg and Martin Boldt, “Clustering residential burglaries using modus operandi and spatiotemporal information”, in International Journal of Information Technology & Decision Making, World Scientific, ISI impact factor: 1.406, 2016, DOI: http://www.worldscientific.com/doi/10.1142/S0219622015500339
Andreas Jacobsson, Martin Boldt, and Bengt Carlsson, “A risk analysis of a smart home automation systems”, in Journal of Future Generation Computer Systems, Elsevier, ISI impact factor: 2.786, 2015, DOI: http://www.sciencedirect.com/science/article/pii/S0167739X15002812
Anton Borg, Martin Boldt, Niklas Lavesson, Ulf Melander, Veselka Boeva, “Detecting serial residential burglaries using clustering”, in Journal of Expert Systems with Applications, Elsevier, Vol. 44, Issue 11, ISI impact factor: 2.339, 2014, DOI: 10.1016/j.eswa.2014.02.035
Niklas Lavesson, Martin Boldt, Paul Davidsson, and Andreas Jacobsson, “Learning to detect spyware using end user license agreements”, in International Journal of Knowledge and Information Systems (KAIS), Springer, Vol. 26, Issue 2. ISI impact Factor: 2.225, 2009, DOI: 10.1007/s10115-009-0278-z
Jens Olsson and Martin Boldt, “Computer forensic timeline visualization tool”, in Journal of Digital Investigation, Elsevier, Vol. 6, ISI impact factor: 0.768, 2009, DOI: 10.1016/j.diin.2009.06.008
In conference/workshop proceedings (peer-reviewed)
Jim Ahlstrand, Martin Boldt, Håkan Grahn and Anton Borg, “Preliminary Results on the use of Artificial Intelligence for Managing Customer Life Cycles”, in proceedings of the 35th Swedish AI Society’s workshop (SAIS), 2023. DOI: 10.3384/ecp199007. [PDF]
Victor Arvidsson Ahmad Al-Mashahedi, Martin Boldt, “Evaluation of Defense Methods Against the One-Pixel Attack on Deep Neural Networks”, in proceedings of the 35th Swedish AI Society’s workshop (SAIS), 2023. DOI: 10.3384/ecp199005. [PDF]
Kenneth Lewenhagen, Martin Boldt, Anton Borg, Manne Gerell, Johan Dahlen, “An interdisciplinary web-based framework for data-driven placement analysis of CCTV cameras”, in proceedings of the 9th Swedish Workshop on Data Science (SweDS), 2022. DOI: 10.1109/SweDS53855.2021.9637719.
Anton Borg, Jim Ahlstrand, and Martin Boldt, “Predicting E-mail Response Time in Corporate Customer Support”, in proceedings of the 22nd International Conference on Enterprise Information Systems, 2020. DOI: 10.1007/978-3-030-75418-1_6.
Anton Borg, Martin Boldt, and Johan Svensson, “Using conformal prediction for multi-label document classification in e-mail support systems”, in proceedings of the 32nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, Best Paper Candidate, 2019. [PDF]
Martin Boldt, Anton Borg, and Veselka Boeva, “Multi-expert estimations of burglars’ risk exposure and level of pre-crime preparation using on crime scene data”, in proceedings of the 30th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS), 2017. [PDF]
Martin Boldt and Anton Borg, “A statistical method for detecting significant temporal hotspots using LISA statistics”, in proceedings of the 8th European Intelligence and Security Informatics Conference (EISIC), 2017. [PDF]
Anton Borg, Martin Boldt, and Johan Eliasson, “Detecting crime series based on route estimations and behavioral similarity”, in proceedings of the 8th European Intelligence and Security Informatics Conference (EISIC), 2017. [PDF]
Martin Boldt and Jaswanth Bala, “Filtering estimated crime series based on route calculations on spatiotemporal data”, in proceedings of the 7th European Intelligence and Security Informatics Conference (EISIC), 2016. DOI: 10.1109/EISIC.2016.024
Dejan Baca, Martin Boldt, Bengt Carlsson, and Andreas Jacobsson, “A novel security-enhanced agile software development process applied in an industrial setting”, in proceedings of the 10th International Conference on Availability, Reliability, and Security (ARES), Best Paper Candidate, Lecture Notes in Computer Science, 2015.
Fredrik Erlandsson, Roozbeh Nia, Martin Boldt, Henric Johnson, and Felix Wu, “Crawling online social networks”, in proceedings of the Second European Network Intelligence Conference (ENIC), 2015.
Raja Khurram Shahzad, Mehwish Fatima, Niklas Lavesson, Martin Boldt, “Consensus decision making in random forests”, in Machine Learning, Optimization, and Big Data, Lecture Notes in Computer Science 9432, 2015. DOI: 10.1007/978-3-319-27926-8_31
Martin Boldt and Anton Borg, “En strukturerad metod för registrering och automatisk analys av brott”, in proceedings of The 5th Biennial Nordic Police Research Seminar, 2014.
Martin Boldt, Andreas Jacobsson, Bengt Carlsson, “On the risk exposure of smart home automation systems”, in proceedings of the 2nd IEEE International Conference on Future Internet of Things and Cloud (FiCloud-2014), 2014.
Fredrik Erlandsson, Martin Boldt and Henric Johnson, “Privacy threats related to user profiling in online social networks”, in Proceedings of 4th IEEE International Conference on Information Privacy, Security, Risk and Trust, 2012.
Anton Borg, Martin Boldt, and Bengt Carlsson, “Simulating malicious users in a software reputation system”, Communications in Computer and Information Science, Vol. 186, 2011.
Anton Borg, Martin Boldt, and Niklas Lavesson, “Informed software installation through license agreement categorization”, in Proceedings of Information Security South Africa (ISSA), 2011.
Martin Boldt, Anton Borg and Bengt Carlsson, “On the simulation of a software reputation system”, in Proceedings of the International Conference on Availability, Reliability and Security (ARES), 2010.
Niklas Lavesson, Paul Davidsson, Martin Boldt, and Andreas Jacobsson, “Spyware prevention by classifying end user license agreements”, in Studies in Computational Intelligence, Volume 134, Springer, 2008.
Martin Boldt, Paul Davidsson, Andreas Jacobsson, and Niklas Lavesson, “Automated spyware detection using end user license agreements”, in the Proceedings of the Second International Conference on Information Security and Assurance, Busan Korea, 2008.
Martin Boldt and Bengt Carlsson, “Confidentiality aspects within road user charging systems: the Swedish case”, in Proceedings of the 15th ITS World Congress, New York, 2008.
Bengt Carlsson and Martin Boldt, “Security analysis of the Swedish road user charging system”, in Proceedings of the 15th ITS World Congress, New York, 2008.
Martin Boldt, Bengt Carlsson, Tobias Larsson, Niklas Lindén, “Preventing privacy-invasive software using online reputations”, in Lecture Notes in Computer Science, Volume 4721, Springer Verlag, Berlin Germany, 2007.
Jan Persson, Paul Davidsson, Martin Boldt, Bengt Carlsson, Marcus Fiedler, “Evaluation of road user charging systems: the Swedish case”, in Proceedings of the 14th World Congress on Intelligent Transport Systems, Beijing China, 2007.
Martin Boldt, Bengt Carlsson, Roy Martinsson, “Software vulnerability assessment – version extraction and verification”, in Proceedings of the International Conference on Systems and Networks Communications (ICSEA 2007), Cap Esterel France, 2007.
Martin Boldt and Bengt Carlsson, “Privacy-invasive software and preventive mechanisms”, in Proceedings of the International Conference on Systems and Networks Communications (ICSNC 2006), Awarded Best Paper, Papeete French Polynesia, 2006.
Martin Boldt and Bengt Carlsson, “Analysing countermeasures against privacy-invasive software”, in Proceedings of the International Conference on Systems and Networks Communications (ICSEA 2006), Papeete French Polynesia, 2006.
Martin Boldt, Bengt Carlsson, and Andreas Jacobsson, “Exploring spyware effects”, in Proceedings of the Nordic Workshop on Secure IT Systems (NordSec04), Helsinki Finland, 2004. [ PDF ]
Andreas Jacobsson, Martin Boldt, and Bengt Carlsson, “Privacy-invasive software in file-sharing tools”, in Proceedings of the IFIP World Computer Congress (WCC2004), Toulouse France, 2004.
Johan Wieslander, Martin Boldt, and Bengt Carlsson, “Investigating spyware on the internet”, in Proceedings of the Nordic Workshop on Secure IT Systems (NordSec03), Gjövik Norway, 2003.
Theses
Martin Boldt, Privacy-Invasive Software, Dissertations, 2010.
Martin Boldt, “Privacy-invasive software – exploring effects and countermeasures”, Licentiate Thesis Series, No. 2007:01, School of Engineering, Blekinge Institute of Technology, Sweden, 2007.
Other
Technical reports, white papers, etc. are not listed here.