Julio De Melo Borges

Karlsruhe Institute of Technology (KIT)
Campus Süd
Institute of Telematics
Chair for Pervasive Computing Systems / TECO
Vincenz-Prießnitz-Straße 1
76131 Karlsruhe
Germany
Building 07.07, Room 214

email: borges(at)teco.edu
LinkedIn: http://lnked.in/jborges
phone: +49 721 608-41708
fax: +49 721 608-41702

Short CV

  • Now: Data Scientist at TECO/KIT
  • 2015: Graduation with Master (MSc) of Computer Science from Karlsruhe Institute of Technology (KIT)
  • 2015: Conclusion of Software Campus Executive Training Program in cooperation with Software AG
  • 2012: Graduation with Bachelor (BSc) of Computer Science from Karlsruhe Institute of Technology (KIT)

Projects

Activities

2017

2016

2015

Teaching

Supervised Theses

  • Qianqian Cao: Enhancing Traffic Flow Forecasting with Environmental Models (Master-Thesis)
    Status: Ongoing
  • Daniel Ziehr: Leveraging Spatio-Temporal Features for Improving Predictive Policing (Master-Thesis).
    Status: Finished
  • Wei Han: Association Rules Mining for Master Data (Master-Thesis)
    Status: Finished

Research Interests

  • Data Minining
  • Machine Learning
  • Big Data Technologies
  • IoT + Smart Cities

Peer-reviewed Publications

2016

Wei Han, Peter Neumayer, Julio Borges (2016) Interestingness Classification of Association Rules for Master Data, 1st Smart Data Innovation Conference (SDIC), url

Julio Borges, Christian Bauer (2016) Analysis of highly variant, temporal data sets for condition-based maintenance, 1st Smart Data Innovation Conference (SDIC), url

Julio De Melo Borges, Matthias Budde, Oleg Peters, Till Riedel, Michael Beigl (2016) Towards Two-Tier Citizen Sensing, 2nd IEEE International Smart Cities Conference (ISC2-2016), doi:10.1109/ISC2.2016.7580771

Julio De Melo Borges, Till Riedel, Michael Beigl (2016) Urban Anomaly Detection: a Use-Case for Participatory Infra-Structure Monitoring, Proceedings of the Second International Conference on IoT in Urban Space - Urb-IoT'16, Best Note Award, url

Julio De Melo Borges, Matthias Budde, Oleg Peters, Till Riedel, Andrea Schankin, Michael Beigl (2016) EstaVis: A Real-World Interactive Platform for Crowdsourced Visual Urban Analytics, Proceedings of the Second International Conference on IoT in Urban Space - Urb-IoT'16, Best Paper Nominee, url

2015

Yong Ding, Julio Borges, Martin A. Neumann, Michael Beigl (2015) Sequential Pattern Mining – a Study to Understand Daily Activity Patterns for Load Forecasting Enhancement, 1st IEEE International Smart Cities Conference (ISC2-2015), Guadalajara, Mexico: IEEE, url

2014

Matthias Budde, Julio De Melo Borges, Stefan Tomov, Till Riedel, Michael Beigl (2014) Leveraging Spatio-Temporal Clustering for Participatory Urban Infrastructure Monitoring, The First International Conference on IoT in Urban Space (UrbIoT'14), Best Paper Award, url

Matthias Budde, Julio De Melo Borges, Stefan Tomov, Till Riedel, Michael Beigl (2014) Improving Participatory Urban Infrastructure Monitoring through Spatio-Temporal Analytics, 3rd ACM SIGKDD International Workshop on Urban Computing (UrbComp’14), pdf