Reza Hoseinnezhad
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Reza Hoseinnezhad (born 1973 in Tehran, Iran) is an Iranian electrical engineer.
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[edit] Education
Hoseinnezhad received his B. Eng., M. Eng., and Ph. D. degrees from the University of Tehran, Iran in 1994, 1996, and 2002, respectively, all in electrical engineering. From 2002 to 2003, he was an assistant professor at the University of Tehran. From July 2003 to October 2005, he was a postdoctoral research fellow, and since October 2005 he has been a senior research fellow, at Swinburne University of Technology, Victoria, Australia.
[edit] Research Activities and Current Interests
Hoseinnezhad's research has been focused on data fusion, brake-by-wire and robust statistics in computer vision. His current research interests are detailed as follows:
[edit] Data fusion in brake-by-wire systems
Mainly focuses on development of data fusion techniques used in brake-by-wire systems for different purposes such as brake control, clamp force estimation and utilisation of redundant information to enhance vehicle safety and reliability. Efficient integration of redundant information in a brake‑by‑wire system is expected to significantly improve the reliability and fault tolerance of such systems. The research is also intended to eliminate the need for costly and complicated clamp force measurement sensors by developing new techniques that can accurately estimate the clamp force signal. Such techniques will need to fuse more readily available measurements such as the electric current and the rotor angular position of the main electro-mechanical actuator, wheel speed and internal temperatures to calculate the clamp force without direct measurement. Brake‑by‑wire is the core component of a drive-by-wire system and many automobile manufacturers worldwide actively pursue its development. Development of the proposed data fusion techniques enhances the functionality of existing brake-by-wire systems and more importantly will influence the design of future brake‑by‑wire systems.
[edit] Robust estimation techniques in computer vision
Robust estimation theory has been widely applied to solve different types of computer vision problems. This research project focuses at studying various properties of state-of-art robust estimators developed in computer vision literature. Some of such properties are the consistency, finite sample bias, convergence rate and computational complexity of the estimation techniques in different vision problems. Particularly, the robust estimators are evaluated for their performance in solving the problems that involve parameter estimation for multiple data structures. This project also aims at developing new robust estimation techniques that outperform current methods in terms of bias, consistency of convergence rate.
[edit] Awards
December, 2006, Vice-Chancellor’s Research Award by Swinburne University of Technology
December, 2003, Distinguished PhD thesis award by University of Tehran
January, 2000, Japanese Government Monbusho scholarship
1990, Distinguished student in the 2nd Iranian Physics Olympiad
1990, Distinguished student in the 5th Iranian Math Olympiad
[edit] Teaching
[edit] University of Tehran
Engineering Statistics and Probability
Electric Circuits
Electronic Circuits
Signals and systems
Linear Control Systems
Modern Control Systems
Data Fusion
[edit] Swinburne University of Technology
Robotic Project 1
Robotic Project 2
Advanced Technologies
