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Dr Abolfazl Zaraki

Dr Abolfazl Zaraki

Lecturer

School of Engineering

Email
zarakia (at) cardiff.ac.uk
Telephone
+44 (0) 29 2087 4278
Campuses
Room C1.08, Queen's Buildings, 5 The Parade, Newport Road, Cardiff, CF24 3AA
Users
Available for postgraduate supervision

Overview

Dr. Abolfazl Zaraki is Lecturer at the School of Engineering and a member of the Research Centre in AI, Robotics and Human-Machine Systems (IROHMS) at Cardiff University, Cardiff. He is the Co-chair of Human-Like Artificial Intelligence (AI) working group and a member of IROHMS leadership team.

He received a master’s degree in mechatronics and automatic control engineering from University Technology Malaysia, Malaysia in 2010, and a Ph.D. degree in automatic robotic and bioengineering from University of Pisa, Italy in 2014. Between 2014 and 2019, he worked as Research Fellow/Senior Research Fellow at different research institutions in Italy and the UK. 

In the past, Abolfazl worked on European projects EASEL (Expressive Agents for Symbiotic Education and Learning), BabyRobot - NextGen Social Robotics, JAMES (Joint Action for Multimodal Embodied Social Systems) and an Innovate UK funded project Piglet – Snake Robot Solution for Inspection in collaboration with industry.

Before joining the Cardiff University, Abolfazl pursued his career at different institutes including University Technology Malaysia, University of Pisa, fortiss GmbH in Germany, University of Hertfordshire, and University of Reading, in the UK.

Abolfazl’s research interests include the development of autonomous systems for social and industrial robotic platforms, trusted autonomy, closed-loop Human-Robot Interaction studies, and brain-computer interface (BCI) for research and assistive applications.

Biography

Dr. Abolfazl Zaraki received a master’s degree in mechatronics and automatic control engineering in 2010, and a Ph.D. degree in automatic robotic and bioengineering in 2014. Between 2014 and 2019, he worked as Research Fellow/Senior Research Fellow at different research institutions in Italy and the UK.

Education

PhD in Automatic Robotic and Bioengineering (Jan. 2011– Jan. 2014) Engineering Department of University of Pisa, Italy
Master of Mechatronics and Automatic Control (Dec. 2007 – March. 2010) Universiti Teknologi Malaysia, Malaysia
Visiting Researcher (PhD internship) Fortiss GmbH – An - Institut Technische Universität München Germany

Past projects involved

  • EASEL (Expressive Agents for Symbiotic Education and Learning) - European project  
  • BabyRobot - NextGen Social Robotics - European project  
  • JAMES (Joint Action for Multimodal Embodied Social Systems) - European project  
  • Piglet – Snake Robot Solution for Inspection in collaboration with industry -Innovate UK funded project

Academic positions

  • Jan. 2020 – Present: Lecturer (Teaching and Research), School of Engineering, Cardiff University
  • Dec 2018 –  Dec 2019: Postdoctoral Researcher,  Department of Biomedical Engineering University of Reading
  • July 2016 – April 2019: Research Fellow/Senior Research Fellow, Computer Science Department of University of Hertfordshire
  • Feb. 2015 – July 2016: Postdoctoral Research Fellow  Centro di Ricerca “E. Piaggio”, Engineering Department of University of Pisa, Italy
  • Jan. 2014 – Feb. 2015: Research Assistant, Engineering Department of University of Pisa, Italy

Publications

2021

2020

2019

2018

2017

2016

2015

2014

2013

2009

Teaching

EN2037: Control and Instrumentation - Spring Semester

EN3062: Robotics and Image Processing - Autumn Semester

EN4062: Advanced Robotics - Spring Semester

Thanks to the recent advancement of robotic solutions and computational intelligence, autonomous robots that interact with humans are nowadays becoming more available to the public offering different benefits to support people in various organizational contexts such as education, assistive applications, customer service, home maintenance, etc. These robots are envisioned to deliver meaningful benefits through interaction with humans efficiently and effectively to fulfil our expectations. These beneficial effects, however, may not always be realised due to maladaptive forms of interaction. To establish a successful human-robot interaction (HRI), besides the perceptual and cognitive capabilities, an autonomous robot should be able to adapt its behaviour in real-time and often in partially unknown environments, to make necessary adjustments to the situation at hand which in turn leads to achieving the high-level goal, for example, assisting a person to solve a puzzle or a tricky math problem.

In contrast to automation that follows pre-programmed “rules” and limited to specific actions, autonomous robots are envisioned to have context-guided behaviour adaptation capability which would allow them to have a degree of self-governance to enable them to learn and respond actively to situations that were not pre-programmed by the developer. Although this capability of the robot would potentially promote HRIs, it raises serious concerns regarding the impact of technology adaptation on human trust as the actions of robots involved in HRI will become less predictable. Thus, It is believed that a successful and trustworthy HRI must be a trade-off between the robot’s behaviour adaptation capability as well as the robot’s capability in measuring and manipulating other community and individual-relevant factors such as trust, where the human is the trustor and the robot is the trustee, with the final aim to maximise the outcomes of the HRI.

My research goal is to design and develop an innovative context-guided artificial cognition system (ACS) which enables robots to display adaptive behaviour in an HRI context to achieve predefined goals as well as to fulfil the expectation of the person who is interacting with, by measuring and manipulating human trust on the fly.

Supervision

I am interested in supervising PhD and MSc students in the following areas:

  • Autonomous system development for Human-Robot Interaction
  • AI and Robotics
  • Computational semantics
  • Brain-Computer Interfaces
  • Mutual understanding and behavioural adaptation in closed-loop Human-Robot Interactions
  • Non-verbal signals undrestanding
  • Intention recognition based on the EEG data  
  • Safe and Trustworthy Human-Robot Interaction

Student Supervision

Supervised/Co-Supervised PhD Students: Current

  • Tong Tong 

Supervised Msc Student: Current

  • Jakub Krakowski