Projects per year
Personal profile
Biography
Naim is a Senior Research Fellow in the Department of Data Science and AI, Faculty of Information Technology at Monash University. His research focuses on advancing human–machine teaming through the development of trustworthy and adaptive AI systems, particularly in high-stakes and dynamic environments.
With extensive experience across academia and industry, He leads and contributes to multidisciplinary research initiatives. He has published in top-tier venues including Expert Systems with Applications, IEEE Transactions on Affective Computing, and ACM Computing Surveys.
He has secured over $3 million in competitive research funding from academic, government, and industry sources, and collaborates closely with partners across these sectors. In addition to his research, Naim is actively involved in postgraduate supervision and mentoring, and plays a leading role in shaping applied AI education through curriculum innovation and industry-aligned program development. To explore his work and collaborations in more detail, please visit his Research Profile.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Computer Science, Doctor of Philosophy, Queensland University of Technology (QUT)
3 Mar 2015 → 1 Nov 2018
Award Date: 10 Dec 2019
Artificial Intelligence , Master Degree, Universiti Kebangsaan Malaysia (National University of Malaysia)
6 Sept 2011 → 7 Oct 2013
Award Date: 7 May 2014
Research area keywords
- Human-Machine Teaming
- Autonomous Systems
- AI Trust and Explainability
- Machine Learning & Deep Learning
- Affective Computing
Collaborations and top research areas from the last five years
Projects
- 1 Active
-
Bidirectional trust modelling: Bidirectional trust modelling in Human-machine teaming in dynamic environments
Rastgoo, N. (Primary Chief Investigator (PCI)) & Haffari, R. (Chief Investigator (CI))
10/01/25 → 9/01/27
Project: Research
-
Driver stress levels detection system using hyperparameter optimization
Rastgoo, M. N., Nakisa, B., Rakotonirainy, A., Maire, F. & Chandran, V., 2024, In: Journal of Intelligent Transportation Systems: technology, planning, and operations. 28, 4, p. 443-458 16 p.Research output: Contribution to journal › Article › Research › peer-review
2 Citations (Scopus) -
Driver Emotion Recognition With a Hybrid Attentional Multimodal Fusion Framework
Mou, L., Zhao, Y., Zhou, C., Nakisa, B., Rastgoo, M. N., Ma, L., Huang, T., Yin, B., Jain, R. & Gao, W., 1 Oct 2023, In: IEEE Transactions on Affective Computing. 14, 4, p. 2970-2981 12 p.Research output: Contribution to journal › Article › Research › peer-review
36 Citations (Scopus) -
Audio based depression detection using Convolutional Autoencoder
Sardari, S., Nakisa, B., Rastgoo, M. N. & Eklund, P., 1 Mar 2022, In: Expert Systems with Applications. 189, 13 p., 116076.Research output: Contribution to journal › Article › Research › peer-review
81 Citations (Scopus) -
Driver stress detection via multimodal fusion using attention-based CNN-LSTM
Mou, L., Zhou, C., Zhao, P., Nakisa, B., Rastgoo, M. N., Jain, R. & Gao, W., 1 Jul 2021, In: Expert Systems with Applications. 173, 11 p., 114693.Research output: Contribution to journal › Article › Research › peer-review
145 Citations (Scopus) -
Multiomics, virtual reality and artificial intelligence in heart failure
Gladding, P. A., Loader, S., Smith, K., Zarate, E., Green, S., Villas-Boas, S., Shepherd, P., Kakadiya, P., Hewitt, W., Thorstensen, E., Keven, C., Coe, M., Nakisa, B., Vuong, T., Rastgoo, M. N., Jüllig, M., Starc, V. & Schlegel, T. T., Nov 2021, In: Future Cardiology. 17, 8, p. 1335-1347 14 p.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile14 Citations (Scopus)