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



Jul 2025: Teaching COSC2960 Foundations of Artificial Intelligence, Jul’25.
Jun 2025: Paper: LiteFat: Lightweight Spatio-Temporal Graph Learning for Real-Time Driver Fatigue Detection, accepted at IEEE/RSJ IROS 2025.
May 2025: Congratulations to Dr Nermine Hendy for completing her Ph.D.
May 2025: Paper: Mode Shape Identification Using Graph Neural Networks for Vehicle Structure Design won Best Written Paper Award at SAE Noise & Vibration Conference & Exhibition 2025, Michigan.
May 2025: At SAE Noise & Vibration Conference & Exhibition 2025, Michigan, for Mode Shape Identification Using Graph Neural Networks for Vehicle Structure Design.
Apr 2025: Paper: Structure Mode Shapes Classification using Graph Convolutional Networks in Automotive Application, accepted in Computers and Structures.
Mar 2025: Paper: Mode Shape Identification Using Graph Neural Networks for Vehicle Structure Design, accepted at SAE Noise & Vibration Conference & Exhibition 2025.
Mar 2025: Paper: RFI Mitigation on Raw SAR Data Using U-Net for Enhanced Signal Reconstruction, accepted at IEEE IGARSS’25.
Mar 2025: Teaching COSC2960 Foundations of Artificial Intelligence, Mar’25.
Feb 2025: Paper: Detection of Radio Frequency Interference in Raw SAR Data Using U-Net Segmentation, accepted at IEEE Radar’25.
Feb 2025: Paper: Mode Shape Identification Using Graph Neural Networks for Aircraft Structure Design, accepted at AIAC ‘25.
Jan 2025: Elected Action Editor on the Editorial Board of Neural Networks.
Nov 2024: Paper: Interference localization and mitigation in synthetic aperture radars using variable space-frequency filter, accepted in IEEE GRSL.
Sep 2024: Paper: SEMUS - An Open-Source RF-Level SAR Emulator for Interference Modelling in Spaceborne Applications, accepted in IEEE TAES.
Sep 2024: Local Arrangement Chair on the Committee of AJCAI’24, Melbourne.

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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, and 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

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.
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.
Jing Ren, Ph.D. Student, 2024–Present.
Arturo Sandoval Rodríguez, Ph.D. Student, 2024–Present.
Parin Sanpetchnarong, Ph.D. Student, 2025–Present.
Ricardo Hernandez Lopez, Ph.D. Student, 2025–Present.

Alumni

Parin Sanpetchnarong, M.Sc., 2025. (Ph.D. Student, RMIT)
Nermine Hendy, Ph.D., RMIT, 2025.
Yameng Peng, Ph.D., RMIT, 2024. (Research Fellow, RMIT)
Kathiravan Thangavel, Ph.D., RMIT, 2023. (Postdoc, Khalifa University)
Jarry Chen, M.Sc., RMIT, 2023. (Data Scientist, IBM)
Fitrio Pakana, M.Sc., RMIT, 2021. (Ph.D. Student, 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, March 2025, July 2025.

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

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