Publications & Presentations

(* student advised by Dr.Attar)

Journal Articles

1.     Nada Attar, Matthew Schneps and Marc Pomplun. Working Memory Load Predicts Visual Search Efficiency: Evidence from a Novel Pupillary Response Paradigm. Memory and Cognition, 44(7), pp.1038-1049, 2016 [Impact Factor: 2.457] 

Peer-Reviewed 

  1. [Generative AI, gender bias] Athira Kumar*, William Andreopoulos, Nada Attar. Cross-Linguistic Examination of Gender Bias Large Language Models. IEEE International Conference on AI x Humanities, Education, and Art, 2024. Accepted
  2. [CS Education] Wendy Lee, Rula Khayrallah, Nada Attar, Kathy Lam, Melody Moh, Python for Everyone as a Mathematics GE Course: Broaden Participation and Enhance Data Science Career Pipeline) 2024 IEEE Frontiers in Education Conference (FIE), Accepted
  3. [Computer vision, HCI, refugees and ethnic bias, eye-tracking] Reem Al-Baghli, Akshay Sunil Gurnaney*, and Nada Attar, Detecting Bias in Refugee Perception using Face Swapping: An Empirical Eye-Tracking Study, 2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS), Toronto, ON, Canada, 2024, pp. 1-6, doi: 10.1109/ICHMS59971.2024.10555693.
  4. [AI, computer vision, gender classification] Cheng-En Sung* and Nada Attar, Gender Classification Accuracy via Two-Dimensional Body Joints using Convolutional Neural Networks, 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 2229-2233, doi: 10.1109/BigData59044.2023.10386667.
  5. [Automated vehicles, eye-tracking] Pradeep Narayana*, Nada Attar, Analyzing the Impact of Distractions on Driver Attention: Insights from Eye Movement Behaviors in a Driving Simulator. 2023 Seventh IEEE International Conference on Robotic Computing (IRC), Laguna Hills, CA, USA, 2023, pp. 356-359, doi: 10.1109/IRC59093.2023.00064. 
  6. [AI, computer vision] Siddartha Thentu, and Nada Attar, Investigating Classification Methods Using Fixation Patterns to Predict Visual Tasks. The 15th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design, and Evaluation of Human-Machine Systems. San Jose, Sep 12-15, 2022.
  7. [HCI, gender and ethnic bias] Reem Albaghli, Chaz Chang, Sarah Almahmeed, and Nada Attar. 2022. Untraining Ethnocentric Biases about Gender Roles: A Preliminary Empirical Study Presenting Art as Stimulus. In Proceedings of Mensch und Computer 2022 (MuC '22). ACM, New York, NY, USA, 376–381.
  8. [AI, computer vision] Devangi Chinchankar, Noha Elfikry, and Nada Attar. Task Classification during Visual Search with Deep Learning Neural Networks and Machine Learning Methods. The 9th International Conference on Multimedia and Human-Computer Interaction (MHCI’22), proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS’22) Prague, Czech Republic-July 28- 30, 2022 Paper No. MHCI 110. DOI: 10.11159/mhci22.110.  https://doi.org/10.1145/3543758.3547543 [Acceptance rate: 47%]
  9. [HCI] Reem Albaghli, Yamen Jandali, Sara Almehmeed, and Nada Attar. Leveraging Initial Cognitive Load to Predict User Response to Complex Visual Tasks. The 9th International Conference on Multimedia and Human-Computer Interaction (MHCI’22), Proceedings of the 8th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS’22), Prague, Czech Republic - July 28- 30, 2022. Paper No. MHCI 103. DOI: 10.11159/mhci22.103
  10. [HCI] Sudeep Raj, Chia-Chien Wu, Shreya Raj, Nada Attar. Understanding the Relationship between Microsaccades and Pupil Dilation, ACM ETRA: 2019 Symposium on Eye Tracking Research & Applications, article No. 67, 2019 
  11. [AI]Nada Attar, Paul Fomenky, Wei Ding and Marc Pomplun. Improving Cognitive Load Level Measurement through Preprocessing of Psychophysical Data by Random Subspace Time-Series Method. Proceedings of 2nd IEEE International Conference on Human Computer Interactions (ICHCI’16), pp. 80-84. 2016 [Acceptance rate: 12.28% (135/1099)]
  12. [HCI] Nada Attar and Marc Pomplun. Enhancing Reading Interfaces and Comprehension Measurement with Eye Tracking Data. Proceedings of 2nd IEEE International Conference on Human Computer Interactions (ICHCI’16), pp. 124-129. 2016 [Acceptance rate: 12.28% (135/1099)].
  13. [HCI] Nada Attar, Chia-Chien Wu, Djamel-Eddine Sia and Marc Pomplun. A Deeper Understanding of Optimal Viewing Position Using Eye Fixations and Character Recognition on Text-Viewing and Reading Tasks. ACM ETRA: 2016 Symposium on Eye Tracking Research & Applications, pp. 209-212, ACM, Charleston, SC, USA, 2016 [Acceptance rate 34%]
  14. [HCI] Nada Attar, Chia-Chien Wu and Marc Pomplun. The Effect of Immediate Accuracy Feedback in a Multiple-Target Visual Search Task. In Proceedings of the 36th annual meeting of the cognitive science society, pp. 1868-1873, Quebec, Canada, 2014 [Acceptance rate: 41%]

Abstract Presentations

1.     Nada Attar, Paul Fomenky, Wei Ding and Marc Pomplun. Modeling an Unsupervised Time-Series Learning Method for Visual Search Leveraging Preprocessed Cognitive Load Pupil Data. The 45th Annual Meeting of the Society for Computers in Psychology (SCiP), Chicago, USA, 2015

2.     Chia-Chien Wu, Nada Attar and Marc Pomplun. Involuntary semantic bias during search for words and word pairs. The Meeting of Visual Sciences Society 2015, Journal of Vision, 15 (12), pp. 1367-1367, 2015

3.     Nada Attar, Chia-Chien Wu and Marc Pomplun. Immediate Feedback During Multiple-Target Visual Search Improves Accuracy. The Meeting of the Visual Sciences Society 2014, Journal of Vision, 14 (10), pp. 1195-1195, 2014

4.     Nada Attar, Matthew Schneps and Marc Pomplun. Pupil Size as Measure of Working Memory Load during Visual Search. The Meeting of the Visual Sciences Society 2013, Journal of Vision, 13 (9), pp. 160-160, 2013

5.     Nada Attar, Matthew Schneps and Marc Pomplun. Working Memory Load Increase Predicts Visual Search Efficiency. The Meeting of the Visual Sciences Society 2012, Journal of Vision, 12 (9), pp. 291-291, 2012

Patent

1.     Nada Attar, inventor; Apparatus, method and computer-readable medium that assign measure to an item and assist location. Publication No. US-2017-0249364-A1, Publication Date: 8/31/2017.

    https://patents.google.com/patent/US20170249364

 Press

1.     Atlas of Science: A Novel Approach to Reliability Predicting Efficient Visual Search, September 27, 2016.

http://atlasofscience.org/a-novel-approach-to-reliably-predicting-efficient-visual-search/