Artificial Intelligence, Machine Learning, Swarm Intelligence, Swarm Robotics, Trusted Autonomy, and Computational Linguistics.
Fields of Research (FoR)Artificial intelligence, Machine learning, Neural networks, Computational linguistics, Intelligent robotics, Data management and data science
Dr Heba El-Fiqi is a lecturer with the School of Engineering and Information Technology (SEIT), UNSW Canberra. Her research interest includes the areas of artificial intelligence, swarm intelligence, machine learning, and computational intelligence. Dr El-Fiqi contributions to the AI field includes a novel solution to a significant challenge in Air Traffic control using a novel AI Swarm control methodology. This first-of-its-kind solution...view more
Dr Heba El-Fiqi is a lecturer with the School of Engineering and Information Technology (SEIT), UNSW Canberra. Her research interest includes the areas of artificial intelligence, swarm intelligence, machine learning, and computational intelligence. Dr El-Fiqi contributions to the AI field includes a novel solution to a significant challenge in Air Traffic control using a novel AI Swarm control methodology. This first-of-its-kind solution will create a great impact on future concepts using AI for air traffic management of unmanned aerial vehicles. Furthermore, she developed an algorithm, Weighted Gate Layer Autoencoders (WGLAE), that transforms classic imputation and interpolation uses of relationships learning to signal recovery, where data is correlated due to the time-series nature of the problem. The impact of WGLAE is a better utilization of usually discarded samples and enhancement of samples quality.
She is an IEEE active member. She co-chaired the Women in Artificial intelligence (WAI) activities for IEEE SSCI 2020 and Canberra AI week December 2020. She was an organizing committee member and a session chair for the IEEE CIS Workshop, hosted by UNSW Canberra in April 2018. She also serves as a reviewer for IEEE Transactions on artificial intelligence, IEEE Transactions on Cybernetics, IEEE Transactions on Evolutionary Computation, and IEEE Transactions on Emerging Topics in Computational Intelligence, and a conference program committee member for a number of A/A* conferences, including AAAI, IJCAI, and ECAI.
Dr El-Fiqi actively supports the local female engineering community. She served as the Women in Engineering (WIE) coordinator for the school of SEIT at UNSW Canberra from 2018 to June 2020 and contributed to UNSW Canberra Young Women in Engineering (YoWIE) activities in 2018 and 2019. She also led UNSW Canberra Engineering Pitch to Industry, a networking event between engineering students and engineering industry representatives.
PhD in Computer Science (2009–2013)
From: University of New South Wales UNSW (Australia), School of Engineering and Information Technology
Thesis title: "Detection of Translator Stylometry using Pair-wise Comparative Classification and Network Motif Mining",
Research Areas: Artificial Intelligence, Machine Learning, Social Network Analysis, Computational linguistics, Translator Stylometry, Natural Language Processing.
Master of Computer Science (2005–2009)
From: Cairo University (Egypt), Faculty of Computers and Information
Thesis title: "An Intelligent System for Tracking Network Attacks"
Research Areas: Artificial Intelligence, Artificial Neural Network, Network Attacks, Internet Worms, Detecting Unknown Viruses.
- Dell EMC Award of Distinction (2017): Achievement: delivering data analytics for big data and supporting students through an academic alliance program to obtaining EMC Data Scientist Associate (EMCDSA) certification with a success rate of 98% (317 certified students out of 323 enrolled students).
- IBM Big Data Developer - Instructor Award for Educators (2017).
May 1, 2019, Research to Impact Program Completion, Canberra Innovation Network.
May 5, 2018, Foundations of University Learning and Teaching (FULT) Program Completion, UNSW.
Feb 2, 2017, IBM Big Data Developer 2016, Mastery Award, IBM.
Jul 21, 2016, Big Data Specialist with IBM BigInsights V2.1, IBM.
May 11, 2016, EMC Academic Associate, Data Science and Big Data Analytics, Dell EMC.
Oct 31, 2011, Graduate Teacher Training (GTTP) Program Completion, UNSW.
Sep 3, 2008, Cisco Networking Academy Instructor, Cisco.
Jul 28, 2007, Microsoft Certified Systems Engineer: Security (MCSE +Security), Microsoft.
Jul 28, 2007, Microsoft Certified Systems Administrator: Security (MCSA +Security), Microsoft.
Jul 28, 2007, Microsoft Certified Systems Engineer (MCSE), Microsoft.
Jul 28, 2007, Microsoft Certified Systems Administrator (MCSA), Microsoft.
Aug 12, 2006, Microsoft Certified Professional (MCP), Microsoft.
Jul 27, 2006, Cisco Certified Network Associate (CCNA), Cisco.
My Research Supervision
Areas of supervision
Artificial Intelligence, Machine Learning, Computational Linguistics, Neural Networks, Multi-agent Swarm Intelligence
Undergraduate- 4th Year Engineering Project Supervision.
- Rana Usama, 2022 (HD), Curriculum-based Deep Reinforcement Learning for Autonomous AlphaDogFight Air-to-Air Combat, Joint Supervisor with Aya Hussein.
- Hasan 2021 (HD), Deep Reinforcement Learning for Humanoid Robot Navigation in Unknown Environments, Joint Supervisor with Aya Hussein.
- David King, 2021, (D) Autonomous Learning of Swarm Countermeasures: An Evolutionary Neural Network Approach, Co-supervisor with Hussein Abbass, Principal Supervisor, and Aya Hussein, Co-supervisor.
- Simon Halabi, 2020, Conversational AI Approach For Conversing Sheep States From Simulated Data, Co-supervisor with Hussein Abbass, Principal Supervisor.
Undergraduate- (CDF) Engineering Research Project Supervision.
- Chris Wise, S1 2022, (D), Developing Decentralised Resilience to Malicious Influence in Collective Perception Problem, Joint Supervisor with Aya Hussein.
- Rana Usama S2, 2021, (HD), Autonomous Navigation of Humanoid Robot Using Deep Reinforcement Learning-based Visual SLAM, Joint Supervisor with Aya Hussein.
- Viet Hoang Le, S2 2021, Analysis of different tracking algorithms for four-class object tracking on limited hardware robot, Joint Supervisor with Jo Plested.
- Rana Usama Riaz, S1 2021, Application of Reinforcement Learning Based Shepherding System on Diddyborg UGV, Joint Supervisor with Aya Hussein.
- Viet Hoang Le, S1 2021, Application of Deep Learning based Object Recognition on UGV Robots, Joint Supervisor with Jo Plested.
- ZEIT4150 Fundamentals of Artificial Intelligence
- ZEIT4151 Machine Learning