Indir Jaganjac


Education: MSc.E.E., major computer engineering, 1995
Faculty of Electrical and Computer Engineering,
Zagreb, Croatia.

Personal Statement: A researcher with strong knowledge in big data, predictive modeling, technical systems diagnostics and prognostics.

Skills & Abilities:
•  Software development life cycle
•  Radio-frequency planning
•  WAN, Cisco routers, switches
•  Big data, predictive modeling
•  Technical systems diagnostics and prognostics

Work Experience:

1990-1995                                                                                                                               Participated at conferences: American Association for Artificial Intelligence (AAAI) 1990 in Boston, AAAI ’91 in Anaheim and AAAI ’92 in San Jose.  Attended workshops on machine learning and computer-aided diagnostics of technical systems.

1995 – 1998
Malaysian Embassy, Zagreb, Croatia
•  Assistant to Charge d’Affaires
•  Business continuity planning
•  Disaster recover planning

1999 – 2002
Independent Media Commission, Sarajevo
•  Radio-frequency planning in ICS telecom on digital elevation model of 10-m resolution
2003 – 2007
Technical High School, Zenica
Professor for informatics, computer networks

2007 – 2009
Mittal Steel, Zenica
•  SCADA, predictive maintenance

2009 – present
•  Consulting, PHP, JavaScript, MySQL
•  Consulting, ArcGIS, QGIS
•  Kaggle data science competitions
Currently solving on Kaggle:
– DSTL Satellite Imagery Feature Detection
– The Nature Conservancy Fishery Monitoring
– Two Sigma Financial Modeling Challenge
– Participating in NIJ Real-Time Crime Forecasting Challenge
– Participating in computational biometrics science projects:
•  Unconstrained facial recognition, latent fingerprint image super-resolution enhancement, voice stress analysis (prototypes in MATLAB).

Programming Languages and Applications:
•  MATLAB, LabVIEW, R, Python
•  WEKA data mining software in Java
•  RapidMiner data mining software in Java
•  SkyTree machine learning software for big data
•  BayesiaLab belief networks modeling software in Java
•  PHP, JavaScript, MySQL
•  Python TensorFlow deep learning library for big images and big data
•  NVIDIA GPUs deep learning in Linux Ubuntu 14.04, libraries: CUDA, cuDNN, DIGITS

Computing with Cellular Automata, Reed-Muller workshop, Trier, Germany

Long-term prediction of nonlinear time series with recurrent least squares support
vector machines, ESTSP ’08, Helsinki, Finland

Radial Basis Function Networks for Classification and Prediction, ISP ’05, San Antonio, Texas, USA

Automatic identification of causal knowledge and causal graphs in technical systems
of process ventilators