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Prof. dr. M.J. (Marjan) Sjerps

Faculty of Science
KDV
Photographer: xxx

Visiting address
  • Science Park 107
  • Room number: F3.26
Postal address
  • Postbus 94248
    1090 GE Amsterdam
  • Publications

    2020

    • Vergeer, P., Alberink, I., Sjerps, M., & Ypma, R. (2020). Why calibrating LR-systems is best practice. A reaction to “The evaluation of evidence for microspectrophotometry data using functional data analysis”, in FSI 305. Forensic Science International, 314, [110388]. https://doi.org/10.1016/j.forsciint.2020.110388 [details]
    • de Koeijer, J. A., Sjerps, M. J., Vergeer, P., & Berger, C. E. H. (2020). Combining evidence in complex cases: a practical approach to interdisciplinary casework. Science and Justice, 60(1), 20-29. https://doi.org/10.1016/j.scijus.2019.09.001 [details]

    2019

    2018

    2017

    • Alberink, I., Bolck, A., Sjerps, M., & Vergeer, P. (2017). Comment to “A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation”. Forensic Science International, 276, 154. https://doi.org/10.1016/j.forsciint.2017.03.011 [details]
    • Leegwater, A. J., Meuwly, D., Sjerps, M. J., Vergeer, P., & Alberink, I. (2017). Performance Study of a Score-based Likelihood Ratio System for Forensic Fingermark Comparison. Journal of Forensic Sciences, 62(3), 626-640. https://doi.org/10.1111/1556-4029.13339 [details]
    • Lopatka, M., Sampat, A. A., Jonkers, S., Adutwum, L. A., Mol, H. G. J., van der Weg, G., ... Vivó-Truyols, G. (2017). Local Ion Signatures (LIS) for the examination of comprehensive two-dimensional gas chromatography applied to fire debris analysis. Forensic Chemistry, 3, 1-13. https://doi.org/10.1016/j.forc.2016.10.003 [details]
    • de Zoete, J., Sjerps, M., & Meester, R. (2017). Evaluating evidence in linked crimes with multiple offenders. Science & justice, 57(3), 228-238. https://doi.org/10.1016/j.scijus.2017.01.003 [details]

    2016

    • Lopatka, M., Barcaru, A., Sjerps, M. J., & Vivó-Truyols, G. (2016). Leveraging probabilistic peak detection to estimate baseline drift in complex chromatographic samples. Journal of Chromatography A, 1431, 122-130. https://doi.org/10.1016/j.chroma.2015.12.063 [details]
    • Sampat, A., Lopatka, M., Sjerps, M., Vivo-Truyols, G., Schoenmakers, P., & van Asten, A. (2016). Forensic potential of comprehensive two-dimensional gas chromatography. Trends in Analytical Chemistry, 80, 345-363. https://doi.org/10.1016/j.trac.2015.10.011 [details]
    • Sjerps, M. J., Alberink, I., Bolck, A., Stoel, R. D., Vergeer, P., & van Zanten, J. H. (2016). Uncertainty and LR: to integrate or not to integrate, that’s the question. Law, probability and risk, 15(1), 23-29. https://doi.org/10.1093/lpr/mgv005 [details]
    • de Rijke, E., Schoorl, J. C., Cerli, C., Vonhof, H. B., Verdegaal, S. J. A., Vivó-Truyols, G., ... de Koster, C. G. (2016). The use of δ2H and δ18O isotopic analyses combined with chemometrics as a traceability tool for the geographical origin of bell peppers. Food Chemistry, 204, 122-128. https://doi.org/10.1016/j.foodchem.2016.01.134 [details]
    • de Zoete, J., Curran, J., & Sjerps, M. (2016). A probabilistic approach for the interpretation of RNA profiles as cell type evidence. Forensic Science International. Genetics, 20, 30-44. https://doi.org/10.1016/j.fsigen.2015.09.007 [details]

    2015

    2014

    • Kloosterman, A., Sjerps, M., & Quak, A. (2014). Error rates in forensic DNA analysis: Definition, numbers, impact and communication. Forensic Science International. Genetics, 12, 77-85. https://doi.org/10.1016/j.fsigen.2014.04.014 [details]
    • Lopatka, M., Vivó-Truyols, G., & Sjerps, M. J. (2014). Probabilistic peak detection for first-order chromatographic data. Analytica Chimica Acta, 817, 9-16. https://doi.org/10.1016/j.aca.2014.02.015 [details]
    • de Zoete, J., Sjerps, M., Meester, R., & Cator, E. (2014). The combined evidential value of autosomal and Y-chromosomal DNA profiles obtained from the same sample. International Journal of Legal Medicine, 128(6), 897-904. https://doi.org/10.1007/s00414-014-0971-7 [details]
    • de Zoete, J., Vriend, K., Dolman, M., Meester, R., & Sjerps, M. (2014). Het gebruik van schakelbewijs; juridische en kans-theoretische gezichtspunten. Expertise en Recht, 2014(5), 153-167. [details]

    2013

    • Haraksim, R., Meuwly, D., Doekhie, G., Vergeer, P., & Sjerps, M. (2013). Assignment of the evidential value of a fingermark general pattern using a Bayesian network. In A. Brömme, & C. Busch (Eds.), BIOSIG 2013: proceedings of the 12th International Conference of the Biometrics Special Interest Group : 04.-06. September 2013 in Darmstadt, Germany (pp. 99-109). (GI-Edition : Lecture notes in informatics ; Vol. 212). Bonn: Gesellschaft für Informatik. [details]

    2012

    • Berger, C. E. H., & Sjerps, M. J. (2012). Discussion paper: Reaction to Hamer and Thompson in LPR. Law, probability and risk, 11(4), 373-375. https://doi.org/10.1093/lpr/mgs024 [details]
    • Bolck, A., Stoel, R., Alberink, I., & Sjerps, M. J. (2012). LR models for evidence evaluation. Chinese Journal of Forensic Sciences, 4, 28-42. [details]
    • Sjerps, M. J., & Berger, C. E. H. (2012). How clear is transparent? Reporting expert reasoning in legal cases. Law, probability and risk, 11(4), 317-329. https://doi.org/10.1093/lpr/mgs017 [details]
    • Stoel, R. D., & Sjerps, M. (2012). Interpretation of Forensic Evidence. In S. Roeser, R. Hillerbrand, P. Sandin, & M. Peterson (Eds.), Handbook of risk theory: epistemology, decision theory, ethics, and social implications of risk (pp. 135-158). Dordrecht: Springer. https://doi.org/10.1007/978-94-007-1433-5 [details]

    2011

    • van der Beek, C. P., Kloosterman, A. D., & Sjerps, M. J. (2011). De detectie van vals positieve en de preventie van vals negatieve matches bij grootschalige DNA-databankvergelijkingen. Expertise en Recht, 2011(6), 219-221. [details]

    2014

    • Harris, H. A., Sjerps, M. J., Kloosterman, A. D., Quak, A., & Geradts, Z. J. (2014). Framework for Registration, Classification, and evaluation of errors in the Forensic DNA Typing Process. Proceedings of the American Academy of Forensic Sciences, 20, 19. [W13]. [details]

    2011

    • van der Peijl, G. J. Q., & Sjerps, M. J. (2011). Combination of evidence in complex casework using Bayesian networks. Proceedings of the American Academy of Forensic Sciences, 17, 133-134. [details]

    2015

    • Berger, C., & Sjerps, M. (2015). International Conference on Forensic Inference and Statistics 2014. Expertise en Recht, 2015(3), 96-97. [details]

    2012

    • Sjerps, M. (2012). Bewijskracht 10, volle vaart recht vooruit. (Oratiereeks; No. 417). Amsterdam: Universiteit van Amsterdam. [details]

    2011

    • Sjerps, M. J. (2011). [Review of: D.H. Kaye (2010) The double helix and the law of evidence]. Journal of the American Statistical Association, 106(494), 769. https://doi.org/10.1198/jasa.2011.br1106 [details]
    • Sjerps, M., & Berger, C. (2011). Het Bayesiaanse model biedt een helder zicht op een complexe werkelijkheid. Den Haag: Nederlands Forensisch Instituut. [details]

    2010

    • Sjerps, M., & Kloosterman, A. (2010). Het gebruik van Bayesiaanse netwerken in de forensische (DNA-)statistiek. Ars Aequi, 59(7), 502-508. [details]
    • Sjerps, M., Kloosterman, A., & van der Beek, K. (2010). De interpretatie van een DNA-databankmatch. Delikt en Delinkwent, 40(2), 138-155. [details]

    2016

    • Stols-Witlox, M. J. N., Sjerps, M. J., Hendriks, E., Wallert, A., van Tilborgh, J. L., de Zoete, J. C., & Hermens, E. (2016). Scientific Reasoning in Art: Evaluating Evidence in Paintings Research using a Bayesian Approach. Poster session presented at NICAS 2016 projects presentations, Amsterdam, Netherlands.
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  • Ancillary activities
    • Nederlands Forensisch Instituut
      Werknemer