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Short biography

Currently, I am an assistant professor at University of Plymouth, and a principle research scientist at Stealth start-up. Prior to these roles, I was a postdoctoral research associate at Imperial College London working on a project which is a part of the UKRI Trustworthy Autonomous Systems Hub. The main role is to build a knowledge-based reasoning framework in order to infer trust between humans and robots, personalisation methodologies, and transfer trust between different agents.

I received my Ph.D. degree in robotics and AI in January 2021. My Ph.D. thesis title is "Perception and Knowledge representation and reasoning for manipulation planning", which uses the TOP-DOWN (TOP: knowledge-driven and DOWN is robotics applications) approach to deal with different types of robotic mobile manipulation problems.

I did my Master's degree in robotics in a topic entitled "Design and Development of 5-DOF Color Sorting Manipulator for Industrial Applications”. Moreover, I studied Mechatronics Engineering for my Bachelor's degree.

My research interests include:

  • Knowledge representation and reasoning

  • Knowledge graphs and ontologies

  • Cognitive robotics

  • Robot manipulation planning

  • Artificial Intelligence in Robotics

  • Human-Robot Interactions

  • Robot-robot collaborations

  • Marine and offshore Robotics

  • Healthcare robotics

  • Generative AI-based model for Explainable AI

 

 

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Programming Skills
Ph.D. thesis

My Ph.D. thesis title is "Knowledge representation and reasoning for Perception-based manipulation planning", which deals with different types of robotic manipulation problems such as table-top and navigation.  During his Ph.D., he developed:

 

  1.  A framework called, PMK - Perception and Manipulation Knowledge, which modeled under standardized foundations, Suggested Upper Merged Ontology (SUMO), and Core Ontology for Robotics and Automation(CORA). Also, some reasoning predicates which facilitate the manipulation planning process that involve the integration of symbolic and geometric levels of planning.

  2. A framework called, FailRecOnt - An ontology-based approach for failure interpretation and recovery in automated planning and execution, which increases the capabilities of the robot to interpret failures and provide recovery strategies. 

  3. A framework called, SkillMaN - A Skill-based Robotic Manipulation Framework based on Perception and Reasoning, which uses a multi-model sensory system contains Camera and Radio Frequency Identification (RFID). Moreover, Reasoning, which uses learning-based techniques of adaptation m to increase the use of experiential knowledge in the planning system.

Some of these frameworks were a part of joint works during my visits to other labs. The visited labs are IAI (Institute for Artificial Intelligence), Bremen, Germany, and Third Institute of Physics Biophysics, Georg-August University Göttingen.

The aforementioned works have been tested in simulation, and also with practical examples in real environments. The robots used are YuMi, TIAGo-PAL.

C

C++

Python

Prolog

RAPID

Web Ontology Language (OWL)

MATLAB

General Tools

CMAKE

GIT

SVN

Robotics Tools

GAZEBO

RVIZ

Robot Operating System (ROS)

Navigation Stack

Sensor Tools
Short stay

Vision

RFID

Speech recognition

Institute for Artificial Intelligence (IAI), Bremen University

Supervisor: Prof. Michael Beetz

City/Country: Bremen - Germany

Type of visit: Short research scholar

Starting date 21-January-2019

Ending date: 07-March-2019

Duration: 45 days

Skills

LaTeX

Microsoft Office

Linux

Windows

Third Institute of Physics Biophysics, Georg-August University Göttingen

Supervisor: Prof. Florentin Wörgötter and Dr. Tomas Kulvicius

City/Country: Göttingen - Germany

Type of visit: Short research scholar

Starting date1-November-2019

Ending date: 21-December-2019

Duration: 50 days

Languages

Arabic (Fluent)

English (Professional)

Spanish (Beginner)

German (Beginner)

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