Biography summary
Dr. Bahareh Nakisa is a Senior Lecturer of Applied AI and the course director of Applied AI at School of Information Technology, Deakin University, She received a B.Sc. degree in Soft Engineering from Iran in 2008, Master of Computer Science from the National Univeristy of Malaysia in 2014, and a PhD in Computer Science (Artificial Intelligence) from the Queensland University of Technology (QUT), Australia in 2019. She started working in Industry as AI scientist and Lead AI scientist and then she joined School of Information Technology, Deakin University as a Lecturer of Applied AI in 2019.
Her research spans a broad range of topics related to the Artificial Intelligence, Human-AI collaboration, Machine learning, deep learning. She has applied analytic and algorithmic tools from these fields to solve real-world problems related to diverse domains specially in Transportation, Health, Affective Computing, and air quality.
Research interests
Applied Artificial Intelligence, Pattern recognition, Affective Computing, Human-Computer interaction, Signal Processing, Time-series data analysis
Publications
LightPRA: A Lightweight Temporal Convolutional Network for Automatic Physical Rehabilitation Exercise Assessment
S Sardari, S Sharifzadeh, A Daneshkhah, S Loke, V Palade, M Duncan, B Nakisa
(2024), Vol. 173, pp. 1-13, Computers in Biology and Medicine, Amsterdam, The Netherlands, C1
A Wearable Multi-Sensor Fusion Approach for Gender Recognition based on Deep Learning
Supriya Roy, Bahareh Nakisa, Pubudu Pathirana, Richard Dazeley
(2024), pp. 114-119, ICBRA 2023 : Proceedings of the 10th International Conference on Bioinformatics Research and Applications 2023, Barcelona, Spain, E1
Driver Emotion Recognition with a Hybrid Attentional Multimodal Fusion Framework
L Mou, Y Zhao, C Zhou, B Nakisa, M Rastgoo, L Ma, T Huang, B Yin, R Jain, W Gao
(2023), Vol. 14, pp. 2790-2981, IEEE Transactions on Affective Computing, Piscataway, N.J., C1
S Sardari, S Sharifzadeh, A Daneshkhah, B Nakisa, S Loke, V Palade, M Duncan
(2023), Vol. 158, pp. 1-21, Computers in Biology and Medicine, Amsterdam, The Netherlands, C1
AI apology: interactive multi-objective reinforcement learning for human-aligned AI
H Harland, R Dazeley, B Nakisa, F Cruz, P Vamplew
(2023), Vol. 35, pp. 16917-16930, Neural Computing and Applications, Berlin, Germany, C1
Aaron Casey, Saba Ansari, Bahareh Nakisa, Blair Kelly, Pieta Brown, Paul Cooper, Imran Muhammad, Steven Livingstone, Sandeep Reddy, Ville-Petteri Makinen
(2023), Vol. 2, pp. 1-13, JMIR AI, Toronto, Ont., C1
W Yu, B Nakisa, E Ali, S Loke, S Stevanovic, Y Guo
(2023), Vol. 51, pp. 1-14, Urban Climate, Amsterdam, The Netherlands, C1
Using an extended technology acceptance model to investigate facial authentication
B Nakisa, F Ansarizadeh, P Oommen, R Kumar
(2023), Vol. 12, pp. 100099-100099, Telematics and Informatics Reports, C1
Kaja Antlej, Annahita Nezami, Bahareh Nakisa, Kaori Becerril, Tyson Yunkaporta, Gabrielle Fletcher, John Davis
(2023), AIAA SCITECH 2023 Forum, E1
A Multi-Activity Fusion Approach for Gender Recognition based on Human Activity
H Koralege, T Ngo, P Pathirana, B Nakisa
(2023), pp. 1-4, EMBC 2023 : Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sydney, N.S.W., E1
Audio based depression detection using Convolutional Autoencoder
S Sardari, B Nakisa, M Rastgoo, P Eklund
(2022), Vol. 189, pp. 1-13, Expert Systems with Applications, Amsterdam, The Netherlands, C1
Solar irradiance forecasting using a novel hybrid deep ensemble reinforcement learning algorithm
Seyed Jalali, Sajad Ahmadian, Bahareh Nakisa, Mahdi Khodayar, Abbas Khosravi, Saeid Nahavandi, Syed Islam, Miadreza Shafie-khah, João Catalão
(2022), Vol. 32, pp. 1-12, Sustainable Energy, Grids and Networks, Amsterdam, The Netherlands, C1
Technology Acceptance Model: A Case Study of Palm Vein Authentication Technology
B Nakisa, F Ansarizadeh, P Oommen, S Shrestha
(2022), Vol. 10, pp. 120436-120449, IEEE Access, C1
Driver stress levels detection system using hyperparameter optimization
M Rastgoo, B Nakisa, A Rakotonirainy, F Maire, V Chandran
(2022), Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, C1
Kaja Antlej
(2022), IAA 2022 : Proceedings of the International Academy of Astronautics Symposium on Space and Society 2022, Paris, France, E1
Driver stress detection via multimodal fusion using attention-based CNN-LSTM
L Mou, C Zhou, P Zhao, B Nakisa, M Rastgoo, R Jain, W Gao
(2021), Vol. 173, Expert Systems with Applications, C1
Multiomics, virtual reality and artificial intelligence in heart failure
P Gladding, S Loader, K Smith, E Zarate, S Green, S Villas-Boas, P Shepherd, P Kakadiya, W Hewitt, E Thorstensen, C Keven, M Coe, B Nakisa, T Vuong, M Rastgoo, M Jüllig, V Starc, T Schlegel
(2021), Vol. 17, pp. 1335-1347, Future Cardiology, England, C1
Personalized Health Navigation for Drivers
L Mou, C Zhou, Y Zhao, P Zhao, B Nakisa, R Jain, B Yin
(2021), Vol. 47, pp. 508-519, Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology, Beijing, China, C1
Automatic Emotion Recognition Using Temporal Multimodal Deep Learning
B Nakisa, M Rastgoo, A Rakotonirainy, F Maire, V Chandran
(2020), Vol. 8, pp. 225463-225474, IEEE Access, C1
M Abbasi, M Rastgoo, B Nakisa
(2019), Vol. 38, Environmental Progress and Sustainable Energy, C1-1
A critical review of proactive detection of driver stress levels based on multimodal measurements
M Rastgoo, B Nakisa, A Rakotonirainy, V Chandran, D Tjondronegoro
(2019), Vol. 51, pp. 1-35, ACM Computing Surveys, New York, N.Y., C1-1
Automatic driver stress level classification using multimodal deep learning
M Rastgoo, B Nakisa, F Maire, A Rakotonirainy, V Chandran
(2019), Vol. 138, Expert Systems with Applications, C1-1
B Nakisa, M Rastgoo, A Rakotonirainy, F Maire, V Chandran
(2018), Vol. 6, pp. 49325-49338, IEEE Access, Piscataway, N.J., C1-1
B Nakisa, M Rastgoo, D Tjondronegoro, V Chandran
(2018), Vol. 93, pp. 143-155, Expert Systems with Applications, Amsterdam, The Netherlands, C1-1
B Nakisa, M Rastgoo, M Nazri, M Nordin
(2018), Vol. 96, pp. 4055-4065, Journal of Theoretical and Applied Information Technology, Islamabad, Pakistan, C1-1
F Zhang, S Haddad, B Nakisa, M Rastgoo, C Candido, D Tjondronegoro, R de Dear
(2017), Vol. 123, pp. 176-188, Building and Environment, Amsterdam, The Netherlands, C1-1
A hybrid of modified PSO and local search on a multi-robot search system
M Rastgoo, B Nakisa, M Nazri
(2015), Vol. 12, pp. 1-15, International Journal of Advanced Robotic Systems, London, Eng., C1-1
A multi-swarm particle swarm optimization with local search on multi-robot search system
B Nakisa, M Rastgoo, M Nasrudin, M Nazri
(2015), Vol. 71, pp. 129-136, Journal of Theoretical and Applied Information Technology, Islamabad, Pakistan, C1-1
A modified particle swarm optimization on search tasking
Mohammad Rastgoo, Bahareh Nakisa, Mohammad Ahmadi
(2015), Vol. 9, pp. 594-600, Research Journal of Applied Sciences, Engineering and Technology, Reading, Eng., C1-1
A survey: Particle swarm optimization based algorithms to solve premature convergence problem
B Nakisa, M Nazri, M Rastgoo, S Abdullah
(2014), Vol. 10, pp. 1758-1765, Journal of Computer Science, New York, N.Y., C1-1
A critical evaluation of literature on robot path planning in Dynamic environment
M Rastgoo, B Nakisa, M Nasrudin, M Nazri
(2014), Vol. 70, pp. 177-185, Journal of Theoretical and Applied Information Technology, Islamabad, Pakistan, C1-1
Balancing exploration and exploitation in particle swarm optimization on search tasking
Bahareh Nakisa, Mohammad Rastgoo, Md Norodin
(2014), Vol. 8, pp. 1429-1434, Research Journal of Applied Sciences, Engineering and Technology, Reading, Eng., C1
B Nakisa, S Nosratabadi, A Rajabi, M Dehghani, M Molla-Ahmadi
(2014), pp. 94-99, 2014 19th Conference on Electrical Power Distribution Networks, EPDC 2014, E1-1
Funded Projects at Deakin
Other Public Sector Funding
AI Apology: Considerations for An Apologetic Approach to Socially Responsible Agents.
Prof Richard Dazeley, Dr Bahareh Nakisa, Mx Hadassah Harland
CSIRO
- 2024: $10,000
- 2023: $10,000
Industry and Other Funding
Manfacturing the next generation Palm Vein Biometric Scanning Solution.
Dr Bahareh Nakisa, Prof Antonio Robles-Kelly
Aervision t/as Aervision Technologies Pty Ltd
- 2022: $11,500
- 2021: $20,000
Air quality monitoring interpolation and prediction using low-cost outdoor air quality monitoring sensors station.
Dr Bahareh Nakisa, Dr Naim Rastgoo
Aetmos Pty Ltd
- 2023: $5,000
Empowering Agents with Human Feedback: Integrating Implicit and Explicit Signals in Deep Reinforcement Learning
Dr Bahareh Nakisa, Dr Naim Rastgoo, Prof Richard Dazeley, Dr Sunil Aryal
Asian Office of Aerospace Research and Development
- 2023: $256,742
Intelligent Table Tennis Match Analysis: Automated Insights Extraction through Machine Learning and Computer Vision.
Dr Sunil Aryal, Dr Bahareh Nakisa, Prof Richard Dazeley
Table Tennis Australia Ltd
- 2023: $20,000
Supervisions
No completed student supervisions to report