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

Publications Teaching   



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

    Journals and Book Chapters

  • D.A. Sanchez, S.G. Bulon, L. Moreno, A. Birlutiu, M. Kadar. Automatic Character Recognition in Porcelain Ware. ACTA TECHNICA NAPOCENSIS – Electronica - telecomunicatii (Electronics and Telecommunications) ISSN 1221 – 6542, vol. 59, nr.3/2018-seria electronica.
  • 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

  • D. Onita, L.P. Dinu, A. Birlutiu. From Image to Text in Sentiment Analysis via Regression and Deep Learning. 12th biennial Recent Advances in Neural Language Processing - RANLP, September 2019, Varna, Bulgaria. [poster]
  • D. Onita, N. Vartan, M. Kadar, A. Birlutiu. Quality Control in Porcelain Industry based on Computer Vision Techniques. YEF-ECE 2018 - 2nd International Young Engineers Forum on Electrical and Computer Engineering, 4th May 2018, Lisbon, Portugal. [slides]
  • D. Onita, A. Birlutiu. Active Learning based on Transfer Learning Techniques for Image Classification European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges (Belgium), 25 - 27 April 2018. [poster] [slide]
  • 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. [slides]
  • 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]

  • Presentations

  • Machine Learning and Computer Vision Techniques for Optimizing the Manufacturing Process of Porcelain. Erasmus staff mobility grant - Data Science Group, Institute for Computing and Information Sciences, Radboud University Nijmegen, The Netherlands, 21-25 May 2019. [slides]
  • Transfer and Active Learning for Efficient Machine Learning. RAAI 2018 - 2nd Conference on Recent Advances in Artificial Intelligence RAAI, June, 25, 2018, Bucharest. [slides]
  • Towards Automated Defect Detection in Porcelain Industry. SATEE 2018 - Smart Applications & Technologies for Electronic Engineering, June, 21-23, 2018, Alba Iulia. [slides] [abstract]
  • Transfer Learning from a Machine Learning Perspective. ICTAMI- International Conference on Theory and Applications in Mathematics and Informatics, 17 - 20 September 2015, in Alba Iulia, Romania [slides] [abstract]
  • Transfer Learning from a Machine Learning Perspective. Pattern Recognition Lab, FAU University, Erlangen, Germany, September, 2015. [slides]