Adriana Birlutiu

Computer Science Department
"1 December 1918" University of Alba Iulia
Str. Gabriel Bethlen nr.5, 510009, Alba Iulia, Romania
Email: adriana DOT birlutiu AT uab DOT ro

CV     Education Publications Teaching   



Ph.D.: Radboud University Nijmegen, Institute for Computing and Information Sciences, Netherlands, 2011
M.Sc.: Babes-Bolyai University of Cluj-Napoca, Romania and University of Lorraine (Erasmus scholarship), France, 2005
B.Sc.: Babes-Bolyai University of Cluj-Napoca, Romania, 2004



    Google scholar.
    Web of Science (ResearcherID: C-2699-2011)
    Research Gate

    Journals and Book Chapters

  • T. Grubinger, A. Birlutiu, H. Schoner, T. Natschlager, T. Heskes. Multi-Domain Transfer Component Analysis for Domain Generalization. Neural Processing Letters (2017). doi:10.1007/s11063-017-9612-8.
  • B. Malli, A. Birlutiu, T. Natschlaeger. Standard-free calibration transfer-An evaluation of different techniques. Chemometrics and Intelligent Laboratory Systems, vol. 161, pp. 49–60, 2017.
  • A. Birlutiu, F. d Alche-Buc, T. Heskes. A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12(3), pp. 538-550, ISSN: 1545-5963, 2015.
  • A. Birlutiu, P. Groot, T. Heskes. Efficiently Learning the Preferences of People. Machine Learning Journal, ISSN: 0885-6125, pp. 1-28, 2012.
  • A. Floares, A. Birlutiu. Reverse Engineering Networks as Ordinary Differential Equations Systems. In A. Floares (ed.) Computational Intelligence, NOVA Science Publishers Inc, 2012, ISBN: 978-1-62081-901-2 (print), ISBN: 978-1-62081-959-3 (ebook).
  • T.E. De Boer, A. Birlutiu , Z. Bochdanovits, M.J.T.N. Timmerman, T.M.H. Dikstra, N.M. van Straalen, B. Ylstra, D. Roelofs. Transcriptional Plasticity of a Soil Arthropod Across Different Ecological Conditions. Molecular Ecology, ISSN: 0962-1083, vol: 20, issue: 6, pp. 1144-1154, 2011.
  • A. Birlutiu, P. Groot, T. Heskes. Multi-Task Preference Learning with an Application to Hearing-Aid Personalization. Neurocomputing, ISSN: 0925-2312, vol: 73, issue: 7-9, pp. 1177-1185, 2010.

  • Conferences and Workshops

  • A. Birlutiu, A. Burlacu, M. Kadar, D. Onita. Defect Detection in Porcelain Industry based on Deep Learning Techniques. 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, Timisoara, September 21- 24, 2017. (accepted)
  • O. Bagdasar, A. Birlutiu, M. Chen, I.L. Popa. Qualitative case study methodology: Automatic design and correction of ceramic colors. System Theory, Control and Computing (ICSTCC), 2017 21st International Conference on), Sinaia, October 19-21, 2017.
  • T. Geimer, M. Unberath, A. Birlutiu, O. Taubmann, J. Wolfelschneider, C. Bert, A. Maier. A Kernel-Based Framework for Intra-Fractional Respiratory Motion Estimation in Radiation Therapy. International Symposium on Biomedical Imaging (ISBI'17), Australia, April 18 - 21, 2017.
  • T. Geimer, A. Birlutiu, M. Unberath, O. Taubmann, C. Bert, A. Maier. A Kernel Ridge Regression Model for Respiratory Motion Estimation in Radiotherapy. Bildverarbeitung für die Medizin 2017 pp 155-160. 2017. [poster]
  • T. Grubinger, A. Birlutiu, H. Schoner, T. Natschlager, T. Heskes. Domain Generalization based on Transfer Component Analysis. IWANN International Work Conference on Artificial Neural Networks, 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015. Proceedings, Part I. Series Volume: 9094, pp. 325-334. Series ISSN 0302-9743, 2015.
  • A. Birlutiu, T. Heskes. Using Topology Information for Protein-Protein Interaction Prediction. Pattern Recognition in Bioinformatics (PRIB), 9th IAPR International Conference, volume 8626 of Lecture Notes in Computer Science, pages 10-22, Springer International Publishing, Stockholm, Sweden, 2014. [slides]
  • A. Birlutiu, P. Bulzu, I. Iereminciuc, A. Floares. Identifying relevant microRNAs in bladder cancer using multi-task learning. Eleventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, University of Cambdridge, UK, June 2014.
  • A. Birlutiu, D. Ardevan, P. Bulzu, C. Pintea, A. Floares. Integration of Clinico-Pathological and microRNA Data for Intelligent Breast Cancer Relapse Prediction Systems. Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB) - 10th International Meeting, pp. 178—193, Nice, France, 2013.
  • A. Floares, A. Birlutiu. Decision tree models for developing molecular classifiers for cancer diagnosis. International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 10-15, 2012, pp. 1-7. Publisher: IEEE. ISSN: 2161-4393, Print ISBN: 978-1-4673-1488-6, 2012.
  • P. Groot, A. Birlutiu, T. Heskes. Learning from Multiple Annotators with Gaussian Processes. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN), Espoo, Finland, Lecture Notes in Computer Science, Springer, vol 6792, Part II, pp. 159-164, ISBN: 978-3-642-21737-1, 2011. [poster]
  • F. d'Alche-Buc, A. Birlutiu, C. Brouard, T. Heskes, M. Szafranski. Regularized Output Kernel Regression for Protein-Protein Interaction Prediction: Application to Link Transfer and Transduction. Machine Learning in Computational Biology workshop at Neural Information Processins Systems conference, Vancouver, Canada, December 2010.
  • P. Groot, A. Birlutiu, T. Heskes. Bayesian Monte Carlo for the Global Optimization of Expensive Functions. Proceedings of the 19th European Conference on Artificial Intelligence (ECAI), Lisbon, Portugal, IOS Press, Frontiers in Artificial Intelligence and Applications, vol. 215, pp. 249-254, 2010, ISBN: 978-1-60750-605-8, 2010. [BNAIC 2010 abstract]
  • A. Birlutiu, T. Dijkstra, M. van Gerven, T. Heskes. Does the immune system have an influence on malaria parasite gene expression? In The 5th Netherlands Institute for Systems Biology Symposium, Netherlands, 2009. [poster]
  • A. Birlutiu, P. Groot, T. Heskes. Multi-Task Preference Learning with Gaussian Processes. ESANN 2009, 17th European Symposium on Artificial Neural Networks, Bruges, Belgium, online proceedings, pp. 123-128, 2009. [BNAIC 2009 abstract]
  • A. Birlutiu, T. Heskes. Optimal Experimental Design in a Hierarchical Setting for Probabilistic Choice Models. Workshop on Cost-Sensitive Learning at the Neural Information Processing Systems conference, Vancouver, Canada, December 2008. [slides]
  • A. Birlutiu, T. Heskes, B. de Vries, A. Ypma, T. Dijkstra. Bayesian Incremental Utility Elicitation with Application to Hearing Aids Personalization Scientific ICT-Research Event Netherlands (SIREN), Amsterdam, Netherlands, September 2008. [poster]
  • A. Birlutiu, T. Heskes. Expectation Propagation for Rating Players in Sports Competitions. Proceedings of Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, Lecture Notes in Computer Science, vol. 4702, pp. 374-381, Springer, ISBN: 978-3-540-74975-2, 2007. [BNAIC 2007 abstract]

  • Thesis

  • A. Birlutiu Machine learning for pairwise data: applications for preference learning and supervised network inference. Ph.D. Dissertation, Radboud University Nijmegen, Netherlands, ISBN: 9789088913303, pp. 135, 2011.