Mr Ivan Iankov

He commenced working at TSC in November 2005. He is involved in several projects which investigate the environmental impact of transport. He has in-depth knowledge of mathematics, statistics and computer science. He has experience in statistical analyses in the fields of sample and survey design, regression analyses, goodness of fit tests, t-tests, ki-square tests, nonparametric tests, correlation analyses and time series analyses. He has some experience in development of simultaneous and simulation optimisation models (AMPL, SIDRA). He also has strong skills in the development of a quality assured software project (Java, C++).

2006 Honours in Computer and Information Science - University of South Australia, Division of Information Technology, Engineering and the Environment, School of Computer and Information Science

2003 Bachelor of Applied Science (Mathematical and Computer Modelling) - University of South Australia, Division of Information Technology, Engineering and the Environment, School of Mathematics

1996 Bachelor in Agricultural Economics - University of National and World Economy, Sofia Bulgaria

• Environmental impact of transport, Sustainable transport, Emission Trading Schemes (ETS)
• Selected projects
• National In-Service vehicle Emissions study 2 (NISE2) - This project provides the opportunity to gather widespread real vehicle data regarding the condition of the Australian light duty vehicle fleet to allow the assessment of the impact on air quality
• Diesel NEPM Test and Repair Demonstration Program - This project evaluates and reports on the South Australian diesel fleet emissions performance on the basis of results on emission testing of representitive vehicle sample. The project aims to evaluate and report on the effectiveness of an inspection and repair program for on-going management of diesel emissions to achieve improved emissions performance.
• Derivation of Emissions Models for Commercial Vehicles - This research project develops emissions models for commercial vehicles that are capable of modelling changes in driver behaviour. Second by second emissions data from certification tests is disaggregated into their component phases of acceleration, cruise, deceleration and idle. The emissions characteristics of these phases is established and analysed to produce empirical models of emissions per unit time versus mode of operation. These models will then be able to describe the changes in emission characteristics under different commercial vehicle operating modes for a range of commercial vehicle types.

Iankov, II & Zito, R 2008, ‘Correlation Between New Vehicle Emissions Standards and In-service Emissions Levels’ International Conference on Sustainable Automotive Technologies, Melbourne, 5-7 Nov 2008

Iankov, II & Zito, R 2008, ‘Designing Emissions Trading Scheme for Transport Sector – solutions and outcomes’ Austrasia Transport Research Forum, Brisbane, 4-5 Oct 2008

Iankov , II & Zito, R 2007, ‘Impact of Emission Trading Schemes on Transport’ Conference of Australian Institutes for Transport Research, Adelaide, Dec 2007

Gadzhanova, S., Iankov, I., Warren, J., Stanek, J., Misan, G., Baig, Z. and Ponte, L., “Developing High-specificity Anti-hypertensive Alerts by Therapeutic State Analysis of Electronic Prescribing Records.”, Journal of American Medical Informatics Association. Vol 14, No 1, Jan/Feb 2007, p. 100-109.

J. Warren, S. Gadzhanova, J. Stanek and I. Iankov. Understanding Caseload and Practice through Analysis of Therapeutic State Transitions. (AMIA 2005), Washington DC, USA

J. Stanek, I. Iankov, S. Gadzhanova, J. Warren and G. Misan. Guideline-based general practice data mining. (HEC 2005), Melbourne, Australia

J. Warren, J. Stanek, S. Gadzhanova, I. Iankov and Gary Misan. Inferring “Therapeutic states” of Patients from Community Electronic Prescribing Data. Health Data Mining Workshop, April 2005, Adelaide, Australia