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Researcher

Dr Fendy Santoso

My Expertise

Robotics/Mechatronics/Automation and Control Systems, Artificial Intelligence and Machine Learning, System Identification (Data-Driven Modelling), Cyber-Physical Systems.

Fields of Research (FoR)

Control Systems, Robotics and Automation, Aircraft Performance and Flight Control Systems, Neural, Evolutionary and Fuzzy Computation, Neural Networks, Genetic Alogrithms and Fuzzy Logi

Biography

I am a dedicated and passionate roboticist committed to advancing the field of robotics through innovative research and development. With a profound interest in creating intelligent and autonomous systems, I leverage my interdisciplinary background to contribute to the intersection of robotics/mechatronics, control engineering, artificial intelligence, and cybersecurity.

I hold a PhD in Electrical Engineering from The University of New South...view more

I am a dedicated and passionate roboticist committed to advancing the field of robotics through innovative research and development. With a profound interest in creating intelligent and autonomous systems, I leverage my interdisciplinary background to contribute to the intersection of robotics/mechatronics, control engineering, artificial intelligence, and cybersecurity.

I hold a PhD in Electrical Engineering from The University of New South Wales, Sydney, Australia. My academic journey has equipped me with a strong foundation in autonomous systems, providing me with the essential knowledge to address complex challenges in robotics.

My research primarily revolves around the development of intelligent robotic systems capable of perception, decision-making, and action in dynamic and unstructured environments. I am particularly interested in biomimetic intelligent learning techniques by means of neural networks and fuzzy systems to facilitate intelligent learning in aerial robotics.

Throughout my career, I have actively contributed to advancements in intelligent learning. My work on intelligent robotics stands out. I have developed a strong international reputation in the area of Unmanned Aerial Vehicles (UAVs) as evidenced by highly competitive research-intensive fellowship positions, some external and internal research funding as well as numerous publications in numerous high-impact Q1 publications in prestigious high-impact IEEE Trans journals, namely, IEEE Trans on Systems, Man, and Cybernetics: Systems, IEEE Trans on Control Systems Technology, IEEE Trans on Dependable and Secure Computing, IEEE Trans. On Fuzzy Systems, IEEE/ASME Trans on Mechatronics, to name a few, showcasing my commitment to disseminating knowledge and contributing to the academic community.

I have a successful track record in managing and delivering industrial and end-user-focused research. To date, I have secured multiple highly competitive research projects, namely, The ARC Linkage Project from the Australian Government, The US Army Ground Vehicle Systems Centre, and The Defence Science and Training Group (DSTG), Australia, for multiple research projects in the domains of AI, robotics, and cybersecurity.

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An ARC-Funded PhD Position for a domestic student is now available under my supervision. Please visit:

https://researchoutput.csu.edu.au/en/persons/fendy-santoso


My Grants

Robust Defenses Against Adversarial Machine Learning for UAV Systems - ARC Linkage Project, 2023.

An ARC-Funded PhD Position for a domestic student is now available under my supervision. Please visit:

https://researchoutput.csu.edu.au/en/persons/fendy-santoso

 

 


My Qualifications

PhD (Electrical Engineering) - UNSW Sydney, Australia

Master of Engineering(Elec and Comp Systems) - Monash University, VIC, Australia

 


My Awards

Distinguished Early Career Travel Fellowship 2019, University of Wollongong, NSW, Australia

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Location

Autonomous System Laboratory (Building 17, R 131)
School of Engineering and Information Technology, The University of New South Wales, Canberra ACT 2610, AUSTRALIA.