Dr Muneeb Ahmad

Uwch-ddarlithydd, Computer Science

+44 (0) 1792 604640

m.i.ahmad@abertawe.ac.uk

114
Llawr Cyntaf
Y Ffowndri Gyfrifiadol
Campws y Bae

Ar gael ar gyfer Goruchwyliaeth Ôl-raddedig

Dolenni Ymchwil

https://orcid.org/0000-0001-8111-9967

Trosolwg

Ymunodd Dr Muneeb Ahmad â'r Adran Gyfrifiadureg fel Darlithydd ym Mhrifysgol Abertawe yn 2020. Mae ei ymchwil yn canolbwyntio ar ddefnyddio dulliau o faes dylunio sy'n canolbwyntio ar bobl i greu systemau rhyngweithiol deallus fel robotiaid cymdeithasol, a rhyngwynebau defnyddwyr a all addasu i ddefnyddwyr drwy ddadansoddiad amser real o'u signalau cymdeithasol a data ffisiolegol. Mae ganddo ddiddordeb mewn defnyddio dysgu peirianyddol i weithredu systemau rhyngweithiol deallus. Ymhellach, mae'r gwaith yn cynnwys gwerthuso'r systemau rhyngweithiol hyn i astudio eu heffaith ar ymddygiad dynol yn bennaf i weld lefel eu hymgysylltiad cymdeithasol, llwyth gwybyddol, ymddiriedaeth ganfyddedig, a pherfformiad. Cyn ymuno â Phrifysgol Abertawe, mae wedi gweithio fel Cydymaith Ymchwil yng Nghanolfan Roboteg Caeredin yn yr Adran Gyfrifiadureg ym Mhrifysgol Heriot-Watt ar brosiect ORCA-Hub EPSRC, lle arweiniodd y gwaith o ddatblygu dull mesur llwyth Gwybyddol yn y Rhyngweithio rhwng Pobl a Chyfrifiaduron/Robotiaid.

Meysydd Arbenigedd

Rhyngweithio rhwng Pobl a Robotiaid,
Rhyngweithio rhwng Pobl a Chyfrifiaduron,
Rhyngweithio rhwng Pobl ac Asiantau,
Deallusrwydd Artiffisial/Dysgu Peiriannau ar gyfer Rhyngweithio rhwng Pobl a Robotiaid

Cyhoeddiadau

Uchafbwyntiau Ymchwil

McKenna, P., Ahmad, M., Maisva, T., Nesset, B., Lohan, K., & Hastie, H. (n.d.) A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction. ACM Transactions on Human-Robot Interaction
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65907
Tesema, K., Hill, L., Jones, M., Ahmad, M., & Tam, G. (2024). Point Cloud Completion: A Survey. IEEE Transactions on Visualization and Computer Graphics, 1-20.
https://doi.org/10.1109/tvcg.2023.3344935, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65337
http://dx.doi.org/10.1109/tvcg.2023.3344935
Ahmad, M. & Alzahrani, A. (2023). Crucial Clues: Investigating Psychophysiological Behaviors for Measuring Trust in Human-Robot Interaction. In ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction (pp. 135-143). ACM.
https://doi.org/10.1145/3577190.3614148, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64073
Ahmad, M., Alzahrani, A., Robinson, S., & Rahat, A. (2023). Modelling Human Trust in Robots During Repeated Interactions. In International Conference on Human-Agent InteractionACM.
https://doi.org/10.1145/3623809.3623892, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64046
https://doi.org/10.1145/3623809.3623892
Robb, D., Lopes, J., Ahmad, M., McKenna, P., Liu, X., Lohan, K., & Hastie, H. (n.d.) Seeing eye to eye: trustworthy embodiment for task-based conversational agents. Frontiers in Robotics and AI, 10
https://doi.org/10.3389/frobt.2023.1234767, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64061
http://dx.doi.org/10.3389/frobt.2023.1234767
Ahmad, M., Sahoo, D., & Hyde, M. (n.d.) Older Adults' Emotional Challenges and Co-design Preferences for a Social Robot after the COVID-19 Pandemic.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63591
Ahmad, M., Alzahrani, A., & Robinson, S. (2022). Exploring Factors Affecting User Trust Across Different Human-Robot Interaction Settings and Cultures. In HAI '22 - Proceedings of the 10th International Conference on Human-Agent Interaction (pp. 123-131). ACM.
https://doi.org/10.1145/3527188.3561920, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60811
Ahmad, M. & RAFIK, R. (2022). “No Chit Chat!” A Warning From a Physical Versus Virtual Robot Invigilator: Which Matters Most?. Frontiers in Robotics and AI, 9
https://doi.org/10.3389/frobt.2022.908013, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60247
Lohan, K., Ahmad, M., Dondrup, C., Ardón, P., Pairet, È., & Vinciarelli, A. (2020). Adapting Movements and Behaviour to Favour Communication in Human-Robot Interaction. Modelling Human Motion (pp. 271-297). Springer International Publishing
https://doi.org/10.1007/978-3-030-46732-6_13, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57767
Mubin, O., Wijayarathne, J., Ahmad, M., Ginige, A., & Hewapathirana, R. (2016). Using Persuasive Mobile Apps to Enhance Children's Health and Well Being. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing SystemsACM.
https://doi.org/10.1145/2851581.2892447, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57766

Holl Ymchwil

Erthyglau Cylchgronau

Tesema, K., Hill, L., Jones, M., Ahmad, M., & Tam, G. (2024). Point Cloud Completion: A Survey. IEEE Transactions on Visualization and Computer Graphics, 1-20.
https://doi.org/10.1109/tvcg.2023.3344935, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65337
http://dx.doi.org/10.1109/tvcg.2023.3344935
Ahmad, M. & RAFIK, R. (2022). “No Chit Chat!” A Warning From a Physical Versus Virtual Robot Invigilator: Which Matters Most?. Frontiers in Robotics and AI, 9
https://doi.org/10.3389/frobt.2022.908013, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60247
Ahmad, M., Gao, Y., Alnajjar, F., Shahid, S., & Mubin, O. (2021). Emotion and memory model for social robots: a reinforcement learning based behaviour selection. Behaviour & Information Technology, 2021, 1-27.
https://doi.org/10.1080/0144929x.2021.1977389, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57746
Mubin, O., Cappuccio, M., Alnajjar, F., Ahmad, M., & Shahid, S. (2020). Can a robot invigilator prevent cheating?. AI & SOCIETY, 35(4), 981-989.
https://doi.org/10.1007/s00146-020-00954-8, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57756
Ahmad, M., Keller, I., Robb, D., & Lohan, K. (2020). A framework to estimate cognitive load using physiological data. Personal and Ubiquitous Computing
https://doi.org/10.1007/s00779-020-01455-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56610
Ahmad, M., Mubin, O., Shahid, S., & Orlando, J. (2019). Robot’s adaptive emotional feedback sustains children’s social engagement and promotes their vocabulary learning: a long-term child–robot interaction study. Adaptive Behavior, 27(4), 243-266.
https://doi.org/10.1177/1059712319844182, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57754
Mubin, O., Tejlavwala, D., Arsalan, M., Ahmad, M., & Simoff, S. (2018). An assessment into the characteristics of award winning papers at CHI. Scientometrics, 116(2), 1181-1201.
https://doi.org/10.1007/s11192-018-2778-7, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57757
Ahmad, M., Mubin, O., & Orlando, J. (2017). Adaptive Social Robot for Sustaining Social Engagement during Long-Term Children–Robot Interaction. International Journal of Human–Computer Interaction, 33(12), 943-962.
https://doi.org/10.1080/10447318.2017.1300750, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55334
Ahmad, M., Mubin, O., & Orlando, J. (2017). A Systematic Review of Adaptivity in Human-Robot Interaction. Multimodal Technologies and Interaction, 1(3), 14
https://doi.org/10.3390/mti1030014, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55333
Mubin, O., Mahmud, A., & Ahmad, M. (2017). HCI down under: reflecting on a decade of the OzCHI conference. Scientometrics, 112(1), 367-382.
https://doi.org/10.1007/s11192-017-2293-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57755
McKenna, P., Ahmad, M., Maisva, T., Nesset, B., Lohan, K., & Hastie, H. (n.d.) A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction. ACM Transactions on Human-Robot Interaction
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65907
Robb, D., Lopes, J., Ahmad, M., McKenna, P., Liu, X., Lohan, K., & Hastie, H. (n.d.) Seeing eye to eye: trustworthy embodiment for task-based conversational agents. Frontiers in Robotics and AI, 10
https://doi.org/10.3389/frobt.2023.1234767, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64061
http://dx.doi.org/10.3389/frobt.2023.1234767

Penodau Llyfrau

Lohan, K., Ahmad, M., Dondrup, C., Ardón, P., Pairet, È., & Vinciarelli, A. (2020). Adapting Movements and Behaviour to Favour Communication in Human-Robot Interaction. Modelling Human Motion (pp. 271-297). Springer International Publishing
https://doi.org/10.1007/978-3-030-46732-6_13, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57767

Cyfraniadau Cynadleddau

Ahmad, M., Alzahrani, A., Robinson, S., & Rahat, A. (2023). Modelling Human Trust in Robots During Repeated Interactions. In International Conference on Human-Agent InteractionACM.
https://doi.org/10.1145/3623809.3623892, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64046
https://doi.org/10.1145/3623809.3623892
Ahmad, M. & Alzahrani, A. (2023). Crucial Clues: Investigating Psychophysiological Behaviors for Measuring Trust in Human-Robot Interaction. In ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction (pp. 135-143). ACM.
https://doi.org/10.1145/3577190.3614148, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64073
Ahmad, M., Alzahrani, A., & Robinson, S. (2022). Exploring Factors Affecting User Trust Across Different Human-Robot Interaction Settings and Cultures. In HAI '22 - Proceedings of the 10th International Conference on Human-Agent Interaction (pp. 123-131). ACM.
https://doi.org/10.1145/3527188.3561920, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60811
Ahmad, M., Robb, D., Keller, I., & Lohan, K. (2020). Towards a Multimodal Measure for Physiological Behaviours to Estimate Cognitive Load. In International Conference on Human-Computer Interaction: Engineering Psychology and Cognitive Ergonomics. Mental Workload, Human Physiology, and Human Energy (pp. 3-13). Springer International Publishing.
https://doi.org/10.1007/978-3-030-49044-7_1, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57758
Robb, D., Ahmad, M., Tiseo, C., Aracri, S., McConnell, A., Page, V., Dondrup, C., Garcia, F., Nguyen, H., Pairet, È., Ramírez, P., Semwal, T., Taylor, H., Wilson, L., Lane, D., Hastie, H., & Lohan, K. (2020). Robots in the Danger Zone: Exploring Public Perception through Engagement. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 93-102). ACM.
https://doi.org/10.1145/3319502.3374789, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57759
Ahmad, M. & Mubin, O. (2018). Emotion and Memory Model to Promote Mathematics Learning - An Exploratory Long-term Study. In Proceedings of the 6th International Conference on Human-Agent Interaction (pp. 214-221). ACM.
https://doi.org/10.1145/3284432.3284451, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57760
Mubin, O., Ahmad, M., Kaur, S., Shi, W., & Khan, A. (2018). Social Robots in Public Spaces: A Meta-review. In Social Robotics (pp. 213-220). Springer International Publishing.
https://doi.org/10.1007/978-3-030-05204-1_21, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57761
Mubin, O., Manalo, M., Ahmad, M., & Obaid, M. (2017). Scientometric Analysis of the HAI Conference. In Proceedings of the 5th International Conference on Human Agent Interaction-45). ACM.
https://doi.org/10.1145/3125739.3125747, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57762
Ahmad, M., Shahid, S., & Tahir, A. (2017). Towards the Applicability of NAO Robot for Children with Autism in Pakistan. In Human-Computer Interaction – INTERACT 2017 (pp. 463-472). Springer International Publishing.
https://doi.org/10.1007/978-3-319-67687-6_32, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57763
Ahmad, M., Mubin, O., & Orlando, J. (2016). Children views' on social robot's adaptations in education. In Proceedings of the 28th Australian Conference on Computer-Human Interaction - OzCHI '16 (pp. 145-149). ACM Press.
https://doi.org/10.1145/3010915.3010977, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57764
Ahmad, M., Mubin, O., & Orlando, J. (2016). Understanding Behaviours and Roles for Social and Adaptive Robots In Education. In Proceedings of the Fourth International Conference on Human Agent Interaction (pp. 297-304). ACM.
https://doi.org/10.1145/2974804.2974829, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57765
Mubin, O., Wijayarathne, J., Ahmad, M., Ginige, A., & Hewapathirana, R. (2016). Using Persuasive Mobile Apps to Enhance Children's Health and Well Being. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing SystemsACM.
https://doi.org/10.1145/2851581.2892447, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57766
Ahmad, M., Sahoo, D., & Hyde, M. (n.d.) Older Adults' Emotional Challenges and Co-design Preferences for a Social Robot after the COVID-19 Pandemic.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63591

Goruchwyliaeth

Investigating The Impact Of Bias Within The Reinforcement Learning Frameworks During Human-Robot Collaboration. (cyfredol)

PhD

Goruchwyliwr arall: Dr Deepak Sahoo
An Investigation into Fairness of Task Allocation in Human-Computer Interaction (cyfredol)

PhD

Goruchwyliwr arall: Prof Jen Pearson
Enabling intelligent and proactive Telecare services for elderly and vulnerable people (cyfredol)

PhD

Goruchwyliwr arall: Prof Jiaxiang Zhang
Novel human-in-the-loop 3D point cloud completion for sub sea surveying (cyfredol)

PhD

Goruchwyliwr arall: Prof Mark Jones

Goruchwyliwr arall: Dr Gary Tam
Social Robots for Older Adults’ Mental Well-being. (cyfredol)

PhD

Goruchwyliwr arall: Dr Deepak Sahoo
Developing Novel Machine Learning Techniques with Human-in-the-Loop Approach to Enable Better Decision Making on Operations Maintenance (cyfredol)

PhD

Goruchwyliwr arall: Prof Cinzia Giannetti
Measuring Trust in Real-time During Human-Robot Interaction (cyfredol)

PhD

Goruchwyliwr arall: Prof Simon Robinson
Navigating Filter Bubbles: A Multidimensional Analysis of User Behavior and Cross-Cultural Impacts«br /»«br /»«br /»«br /» «br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /» «br /»«br /»«br /»«br /»«br /»«br /» (cyfredol)

PhD

Goruchwyliwr arall: Dr Matt Roach

Modiwlau a Addysgir

CSC349 User Experience

This module presents an overview of concepts, design for and evaluation of User Experience (UX). Students will come to understand what UX is, why the concept has become so prominent, what differentiates UX from aesthetic design, and what UX practitioners do in their work. The module will examine specific design approaches, and the student will gain some practical skills applying these techniques. Techniques that will be covered include brainstorming, personas and participatory design. The module will also cover the research methods that are employed to understand specific experiences with technology and impart the beginnings of the skills needed to employ these methods and evaluate the results. This module develops practical skills through the coursework and theoretical understanding is demonstrated in the exam. The module builds on skills developed in the second year HCI module but this is not a pre-requisite for it.
CSCM39 Human Computer Interaction

This module gives an overview on the main topics in Human Computer Interaction and helps students understand research and research processes in Human Computer Interaction. Students explore the advanced literature and research results underpinning the field of HCI. Classic papers and controversies are covered, as well as recent work from the leading figures. Students achieve a clear view of the 'cutting edge' and issues in the field and where things are happening. The module is very interactive, and students will be expected to give presentations.
CSDM001 Theory of Digital Information and Society

This module gives an overview on theoretical and methodological debates contemporary Digital Economy and Society research with specific focus on Human Computer Interaction. This module helps students understand how human experience can influence the design and adoption of digital into services and the lives of individuals and communities.Students explore the advanced literature and research results underpinning the field. Understand, through a series of Classic papers, the practical application of qualitative and quantitative techniques for the study of soci-technical assemblages in a digital by default world, as well as recent work from the leading figures. Students achieve a clear view of the 'cutting edge' and issues in the field and where things are happening. The module is very interactive, and students will be expected to give presentations.

Dr Muneeb Ahmad

Rhif ffôn

Cyfeiriad ebost

Twitter Account

Dolenni Ymchwil

Trosolwg

Meysydd Arbenigedd

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Holl Ymchwil

Erthyglau Cylchgronau

Penodau Llyfrau

Cyfraniadau Cynadleddau

Goruchwyliaeth

Investigating The Impact Of Bias Within The Reinforcement Learning Frameworks During Human-Robot Collaboration. (cyfredol)

An Investigation into Fairness of Task Allocation in Human-Computer Interaction (cyfredol)

Enabling intelligent and proactive Telecare services for elderly and vulnerable people (cyfredol)

Novel human-in-the-loop 3D point cloud completion for sub sea surveying (cyfredol)

Social Robots for Older Adults’ Mental Well-being. (cyfredol)

Developing Novel Machine Learning Techniques with Human-in-the-Loop Approach to Enable Better Decision Making on Operations Maintenance (cyfredol)

Measuring Trust in Real-time During Human-Robot Interaction (cyfredol)

Navigating Filter Bubbles: A Multidimensional Analysis of User Behavior and Cross-Cultural Impacts«br /»«br /»«br /»«br /» «br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /» «br /»«br /»«br /»«br /»«br /»«br /» (cyfredol)

Modiwlau a Addysgir

CSC349 User Experience

CSCM39 Human Computer Interaction

CSDM001 Theory of Digital Information and Society