Marin Šilić Ph.D.

Contact
E-mail: marin.silic@gmail.com
Postal address:
Faculty of Electrical Engineering and Computing Unska 3, 10 000 Zagreb, Croatia
Office: D339*

Research Interests:

  • BigData
  • Collaborative Filtering
  • Recommendation Systems
  • Machine Learning
  • Computational Photography
  • Image Processing

Teaching Experience:

  • Introduction to Theoretical Computer Science
  • Programming Language Translation
  • Operating Systems
  • Cryptography
  • Service-Oriented Computing
  • Networked Systems Middleware

Topics for B.Sc. and M.Sc. thesis:

  • ENG: The design and implementation of recommendation system for face portraits beautification
    HR: Oblikovanje i ostvarenje sustava za preporuke prilikom uljepšavanja portreta lica na fotografiji
  • ENG: The design and implementation of system for estimating face portraits attractiveness
    HR: Oblikovanje i ostvarenje sustava za predviđanje privlačnosti portreta lica na fotografiji
  • ENG: The design and implementation of system for finding similar face portraits in a large set of images
    HR: Oblikovanje i ostvarenje sustava za pronalaženje sličnih portreta lica u vrlo velikom skupu fotografija portreta lica
  • ENG: The design and implementation of system for deriving user’s personal aesthetic profile based on her interaction with images in social networks
    HR: Oblikovanje i ostvarenje sustava za izvođenje osobnog estetskog profila korisnika zasnovanog na interakciji korisnika s fotografijama na socijalnim mrežama
  • ENG: The design and implementation of system for finding attractive persons in social networks based on user’s personal aesthetic profile
    HR: Oblikovanje i ostvarenje sustava za pronalaženje privlačnih profila na socijalnim mrežama zasnovanog na osobnom estetskom profilu korisnika

Internships:

  • 2008: Google Inc., New York, USA
  • 2006: Ericsson Nikola Tesla, Zagreb, Croatia

Marin Silic CV (pdf)

Marin Silic Resume (pdf)

List of publications:
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2013
  • M. Silic, G. Delac, S. Srbljic: “Prediction of Atomic Web Services Reliability for QoS-aware Recommendation”, IEEE Transactions on Services Computing. (in review process).
  • G. Delac, M. Silic, S. Srbljic: “A Reliability Improvement Method for SOA-Based Applications”,IEEE Transactions on Dependable and Secure Computing. (2014) (accepted for publishing).
  • M. Silic, G. Delac, S. Srbljic: “Prediction of Atomic Web Services Reliability Based on k-Means Clustering”, Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering, ESEC/FSE’13, Saint Petersburg, Russia, 2013, pp. 70-80.
  • G. Delac, M. Silic, K. Vladimir: “Reliability Sensitivity Analysis for Yahoo! Pipes Mashups”, Proceedings of the 36rd International Convention , MIPRO 2013, pp. 851-856.
  • M. Silic, G. Delac, S. Srbljic: “Scalable and Accurate Prediction of Availability of Atomic Web Services”, IEEE Transactions on Services Computing. (2013) (accepted for publishing).
2012
  • G. Delac, M. Silic, S. Srbljic: “Reliability Modeling for SOA Systems”, Proceedings of the 35rd International Convention , MIPRO 2012, pp. 988-993.
  • Pavlic, Zvonimir; Lugaric, Tomislav; Silic, Marin: “Debugging in consumer-programming oriented environments”, Proceedings of the International Conference on Computers in Technical Systems.
    2012. 982-987
2011
  • G. Delac, M. Silic, J. Krolo: “Emerging Security Threats for Mobile Platforms”, Proceedings of the 34rd International Convention , MIPRO 2011 pp. 1468 -14673.
2010
  • M. Silic, J. Krolo, G. Delac: “Security Vulnerabilities in Modern Web Browser Architecture”, Proceedings of the 33rd International Convention , MIPRO 2010, pp. 1240-1245.
2009
  • Krolo, Jakov; Silic Marin; Srbljic Sinisa.
    “Security of Web Level User Identity Management” // Proceedings of the Information Systems Security, Croatian Society for Information and Communication Technology, Electronics and Microelectronics – MIPRO, 2009. 93-98

Short CV:
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Marin Šilić is a postdoctoral researcher at the Faculty of Electrical Engineering and Computing, University of Zagreb. His research interests span Service-oriented Computing, Distributed Systems and Machine Learning. More specifically, he is studying the optimization of nonfunctional properties (such as reliability, availability etc.) while creating composite service-oriented applications in the cloud. In particular, his research is primarily focused on applying advanced machine learning techniques in order to predict the nonfunctional properties of dynamic software artifacts (i.e. web services) using the available past invocation data as training examples. As part of his dissertation thesis, he proposed two prediction algorithms, LUCS and CLUS, that estimate the reliability for an ongoing service invocation based on the history invocation data. In 2008., as a Google intern in the Google Spreadsheets team he designed and developed a lightweight version of application intended for mobile devices and low bandwidth network connections.

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