Haytham Fayek

Haytham

Artificial Intelligence / Machine Learning Research / Science.
Senior Lecturer, School of Computing Technologies,
Royal Melbourne Institute of Technology (RMIT University).
Alumnus, Meta/Facebook Research, Oculus Research, & WorleyParsons.
SMIEEE, MACM, MIEAust.
Scholar | Github | LinkedIn | X | ORCID

Recent

Sep 2024:	Paper: SEMUS - An Open-Source RF-Level SAR Emulator for Interference Modelling in Spaceborne Applications, accepted in IEEE TAES.
Aug 2024:	Paper: Comparing Subjective Measures of Workload in Video Game Play: Evaluating the Test-Retest Reliability of the VGDS and NASA-TLX, accepted at ICMI’24.
Jul 2024:	Teaching COSC2960 Foundations of Artificial Intelligence, Jul’24.
Jun 2024:	Congratulations to Dr Yameng Peng for completing his Ph.D.
Jun 2024:	Paper: Application of Natural Language Processing for Aircraft Defect Tracking in Maintenance Operations, accepted at ICAS’24.
May 2024:	Book: Towards Human Brain Inspired Lifelong Learning, out now.
May 2024:	Paper: Multimodal Measurement of Cognitive Load in a Video Game Context: A Comparative Study Between Subjective and Objective Metrics, accepted in IEEE Transactions on Games.
May 2024:	Paper: Interference localization and mitigation in synthetic aperture radars using variable space-frequency filter, posted on TechRxiv.
May 2024:	At ICLR’24, Vienna, to present SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS.
Apr 2024:	Paper: Optimising Fatigue Crack Growth Predictions for Small Cracks Under Variable Amplitude Loading, accepted in International Journal of Fatigue.
Mar 2024:	Teaching COSC2960 Foundations of Artificial Intelligence, Mar’24.
Jan 2024:	Paper: Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias, accepted at EACL’24.
Jan 2024:	Paper: SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS, accepted at ICLR’24 (Spotlight).
Nov 2023:	Paper: SEMUS - An Open-Source RF-Level SAR Emulator for Interference Modelling in Spaceborne Applications, posted on TechRxiv.
Sep 2023:	Awarded STEM Early-Career Research Excellence Award at RMIT.

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About

I am a Senior Lecturer in the Data Science and Artificial Intelligence Discipline in the School of Computing Technologies at the Royal Melbourne Institute of Technology (RMIT University) in Melbourne, VIC, where I lead the machine learning and intelligence group and affiliate with the Evolutionary Computing and Machine Learning (ECML) Group, the AI Innovation Lab, and the Centre for Industrial AI Research & Innovation (CIARI).

I was a Postdoctoral Research Scientist at Meta/Facebook Research in Seattle, WA, from August 2018 to January 2020. Prior, I received a PhD from RMIT in 2019. My PhD thesis is titled, Continual Deep Learning via Progressive Learning. During my PhD, I was a Research Intern at Facebook with Facebook Reality Labs (Oculus VR Research) and Facebook AI Research (FAIR). Formerly, I received an MSc (Research) and a BEng (Hons) in Electrical and Electronics Engineering, and worked as an Electrical/Electronics Engineer in the engineering consulting industry for three years.

Research

My research interests are broadly in artificial intelligence, machine learning, deep learning, and machine perception.

I am primarily interested in learning systems that systematically generalize from limited labelled data. This includes learning algorithms that can learn from a limited number of samples by drawing on prior experiences in other tasks and those that can learn despite limitations in labels in uni-modal and multi-modal data.

Selected Publications (Full List)

Yameng Peng, Andy Song, Haytham M. Fayek, Vic Ciesielski, and Xiaojun Chang.
SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS.
In International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024.
link bib
Spotlight.

Nannan Huang, Haytham M. Fayek, and Xiuzhen Zhang.
Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias.
In European Chapter of the Association for Computational Linguistics (EACL), Malta, Mar 2024.
pdf arXiv bib

Jarry Chen and Haytham M. Fayek.
The Structurally Complex with Additive Parent Causality (SCARY) Dataset.
In 2nd Conference on Causal Learning and Reasoning (CLeaR), 2023.
pdf bib

Haytham M. Fayek and Justin Johnson.
Temporal reasoning via audio question answering.
IEEE/ACM Transactions on Audio, Speech, and Language Processing, Jul 2020.
link arXiv code bib

Haytham M. Fayek and Anurag Kumar.
Large scale audiovisual learning of sounds with weakly labeled data.
In 29th International Joint Conference on Artificial Intelligence (IJCAI), Yokohama, Japan, Jul 2020.
link pdf arXiv bib

Haytham M. Fayek, Lawrence Cavedon, and Hong Ren Wu.
Progressive learning: A deep learning framework for continual learning.
Neural Networks, vol. 128, pp. 345–357, May 2020.
link bib

Full list of publications

Selected Talks

From First Principles to ChatGPT.
Centre for Higher Education Studies (CHES).
Australia, Jul 2023.

Beyond Supervised Deep Learning.
Centre for Industrial AI Research & Innovation (CIARI), RMIT.
Australia, Apr 2022.
link recording

Will Deep Learning Lead to AI?
Melbourne Machine Learning & AI Meetup.
Melbourne, Australia, Aug 2017.
link slides

On the Transferability of Representations in Neural Networks Between Datasets and Tasks.
Continual Learning Workshop, 32nd Neural Information Processing Systems (NeurIPS 2018).
Montréal, Canada, Dec 2018.
poster

On the Correlation and Transferability of Features between Automatic Speech Recognition and Speech Emotion Recognition.
17th Annual Conference of the International Speech Communication Association (Interspeech).
San Francisco, USA, Sep 2016.
slides

Research Students

Current

Emma Pretty, Ph.D. Student, RMIT, 2021–Present.
Nermine Hendy, Ph.D. Student, RMIT, 2021–Present.
Halide Göknur Aydoğan, Ph.D. Student, RMIT, 2021–Present.
Sitthichart (Mark) Tohmuang, Ph.D. Student, 2022-Present.
Nannan (Amber) Huang, Ph.D. Student, 2022–Present.
Parin Sanpetchnarong, M.Sc. Student, 2023–Present.
Rinaldo Gagiano, Ph.D. Student, 2023–Present.
Jing Ren, Ph.D. Student, 2024–Present.
Arturo Sandoval Rodríguez, Ph.D. Student, 2024–Present.

Alumni

Yameng Peng, Ph.D., RMIT, 2024. (Research Fellow, RMIT)
Kathiravan Thangavel, Ph.D., RMIT, 2023. (Postdoc, Khalifa University)
Jarry Chen, M.Sc., RMIT, 2023. (IBM)
Fitrio Pakana, M.Sc., RMIT, 2021. (Ph.D., RMIT)
Lior Madmoni, Research Intern, Facebook Reality Labs, 2019. (Ben-Gurion University)
Shengjie Bi, Research Intern, Facebook Reality Labs, 2019. (Dartmouth College)
Sharath Adavanne, Research Intern, Facebook Reality Labs, 2018. (Tampere University)

Teaching

Courses

COSC2959/COSC2960 Foundations of Artificial Intelligence.
RMIT, Australia, July 2021, March 2022, July 2022, March 2023, July 2023, March 2024, July 2024.

COSC2676/COSC2752 Programming Fundamentals for Scientists.
RMIT, Australia, March 2020, July 2020, March 2021.

Guest Lectures

Digital Image Watermarking.
EEET2169/EEE1255 Image Processing / Image Systems Engineering.
RMIT, Australia, April 2018.

Sampling and Reconstruction.
EEET2113 Signals and Systems II.
RMIT, Australia, March 2016.

Signals in Noise.
EEET2113 Digital Signal Processing.
RMIT, Australia, April 2015.

Contact

Dr Haytham Fayek
School of Computing Technologies
Royal Melbourne Institute of Technology (RMIT University)
Building 14, Level 11, Room 03
124 La Trobe Street, Melbourne VIC 3000
Australia

Email:
Phone:
Postal:

Aug 2023:	Paper: Continual Deep Learning for Time Series Modeling, accepted in Sensors.
Jul 2023:	Teaching COSC2960 Foundations of Artificial Intelligence, Jul’23.
Jun 2023:	Paper: IberLEF 2023 AuTexTification: Automated Text Identification Shared Task – Team OD-21, accepted at IberLEF’23. Congrats Rinaldo!
May 2023:	Paper: Examining Bias in Opinion Summarisation through the Perspective of Opinion Diversity, accepted at WASSA’23. Congrats Amber!
Apr 2023:	Paper: Fast Evolutionary Neural Architecture Search by Contrastive Predictor with Linear Regions, accepted at GECCO’23.
Mar 2023:	Paper: The structurally complex with additive parent causality (SCARY) dataset, accepted at CLeaR’23. Congrats Jarry!
Mar 2023:	Paper: Trusted Autonomous Operations of Distributed Satellite Systems Using Optical Sensors, accepted in Sensors.
Feb 2023:	Paper: A Case for personalised non-player character companion design, accepted in IJHCI.
Feb 2023:	Paper: A distributed satellite system for multibaseline at-InSAR: Constellation of formations for maritime domain awareness using autonomous orbit control, accepted in Aerospace.
Feb 2023:	Teaching COSC2959/COSC2960 Foundations of Artificial Intelligence, Feb’23.
Jan 2023:	Paper: Evoking empathy with visually impaired people through an augmented reality embodiment experience, accepted at IEEE VR’23. In memory of Ron van Schyndel.
Jan 2023:	Paper: Replicability and Transparency for the Creation of Public Human User Video Game Datasets, accepted at IEEE VR’23 DATA4XR Workshop. Congrats Emma!
Jan 2023:	Paper: Autonomous Satellite Wildfire Detection Using Hyperspectral Imagery and Neural Networks: A Case Study on Australian Wildfire, accepted in Remote Sensing.
Nov 2022:	Paper: PRE-NAS: Evolutionary Neural Architecture Search with Predictor, accepted in IEEE TEVC.
Oct 2022:	Promoted to Senior Lecturer (with Tenure)!
Sep 2022:	Paper: Loads estimation from calibration test with machine learning, accepted at AIAA SciTech’23.
Sep 2022:	Paper: An innovative high-fidelity approach to structural health monitoring, accepted at AIAC’23.
Sep 2022:	Paper: Transfer learning for flight loads estimation by load calibration test data, accepted at AIAC’23. Congrats Halide!
Jul 2022:	Patent: Method for controlling a high speed DC servomotor that controls a robotic arm for the PCB industry (FT2RC) granted.
Jul 2022:	Teaching COSC2959/COSC2960 Foundations of Artificial Intelligence, Jul’22.
Jul 2022:	Elected Senior Member of the IEEE.
Jun 2022:	Paper: A Case for Personalised Non-Player Character Companion Design, is out.
Apr 2022:	Paper: Deep Learning Approaches for Air-writing Using Single UWB Radar, accepted in IEEE Sensors. Congrats Nermine!
Apr 2022:	Talk: Beyond Supervised Deep Learning, Centre for Industrial AI Research & Innovation (CIARI), RMIT.
Mar 2022:	Paper: PRE-NAS: Predictor-assisted Evolutionary Neural Architecture Search, accepted at GECCO’22. Congrats Yameng!
Mar 2022:	Teaching COSC2959/COSC2960 Foundations of Artificial Intelligence, Mar’22.
Jan 2022:	Paper: Advanced Multi-Input System Identification for Next Generation Aircraft Loads Monitoring using Linear Regression, Neural Networks and Deep Learning, accepted in MSSP.
Nov 2021:	At CIKM’21, virtual, chairing Session 2C: Machine Learning.
Oct 2021:	Paper: Knowledge capture and replay for continual learning, accepted at WACV’22.
Sep 2021:	Paper: Recent developments in the implementation of a bidirectional LSTM deep neural network for aircraft operational loads monitoring, accepted at AIAA SciTech’22.
Sep 2021:	Paper: Data-driven flight load prediction using modal decomposition techniques, accepted at AIAA SciTech’22.
Aug 2021:	Call for Papers for Neural Networks Special Issue on Lifelong Learning due 28 Feb 2022.
Jul 2021:	Patent: Systems and methods for hearing assessment and audio adjustment granted.
Jul 2021:	Teaching COSC2959/COSC2960 Foundations of Artificial Intelligence, Jul’21.
Jul 2021:	Our Special Issue on Lifelong Learning was accepted in Neural Networks.
May 2021:	Paper: Deep learning airframe load prediction: A data-driven system for aircraft structural health management, accepted at AIAC’21.
May 2021:	Paper: Buffet load prediction via frequency response functions, accepted at AIAC’21.
Mar 2021:	Teaching COSC2676/COSC2752 Programming Fundamentals for Scientists, Mar’21.
Jan 2021:	At IJCAI’20, virtual, to present Large scale audiovisual learning of sounds with weakly labeled data.
Dec 2020:	Paper: Knowledge capture and replay for continual learning, on arXiv.
Dec 2020:	At NeurIPS’20, virtual.
Aug 2020:	Paper: Temporal reasoning via audio question answering, published in IEEE/ACM TASLP.
Jul 2020:	At ICML’20, virtual.
Jul 2020:	Program for our Workshop on Continual Learning on 17 Jul at ICML’20.
Jul 2020:	Teaching COSC2676/COSC2752 Programming Fundamentals for Scientists, Jul’20.
May 2020:	Paper: Progressive learning: A deep learning framework for continual learning, published in Neural Networks.
Apr 2020:	Paper: Large scale audiovisual learning of sounds with weakly labeled data, accepted at IJCAI’20.
Apr 2020:	Call for Papers for our Workshop on Continual Learning at ICML’20.
Mar 2020:	Our Workshop on Continual Learning was accepted at ICML’20.
Mar 2020:	Teaching COSC2676/COSC2752 Programming Fundamentals for Scientists, Mar’20.
Feb 2020:	Joined the faculty of Computer Science and Software Engineering, RMIT University.
Dec 2019:	At NeurIPS’19, Vancouver.
Nov 2019:	Paper: Temporal reasoning via audio question answering, on arXiv.
Oct 2019:	Paper: Sound event classification and detection with weakly labeled data, at DCASE’19.
Jul 2019:	At ICML’19, Long Beach.
Feb 2019:	PhD Thesis: Continual deep learning via progressive learning!
Dec 2018:	At NeurIPS’18, Montréal, to present On the transferability of representations in neural networks between datasets and tasks at the Continual Learning Workshop.
Aug 2018:	Postdoctoral Research Scientist, Facebook Research, Seattle.
Jun 2018:	Panel discussion at ACMI X, Melbourne, on Talking Computers: How Voice Technology is Changing the Human Machine Interaction.
Feb 2018:	Teaching Assistant at RMIT for postgraduate COSC1295 Advanced Programming and undergraduate EEET2169 Image Processing.
Dec 2017:	At NIPS’17, Long Beach.
Nov 2017:	Paper: MatDL: A lightweight deep learning library in MATLAB, in JOSS.
Nov 2017:	At World Youth Forum (WYF’17), Sharm El Sheikh.
Oct 2017:	At AES’17, New York, to present On data-driven approaches to head-related transfer function personalization.
Sep 2017:	Talk at Swinburne University, Melbourne, on Will Deep Learning Lead to AI?
Aug 2017:	Talk at the ML / AI Melbourne Meetup, on Will Deep Learning Lead to AI?
Aug 2017:	At ICML’17, Sydney and IJCAI’17, Melbourne.