By Dr Reza Argha

Conference Papers

Argha A; Li L; Su SW; Nguyen H, 2015, 'Robust output-feedback discrete-time sliding mode control utilizing disturbance observer', in Proceedings of the IEEE Conference on Decision and Control, pp. 5671 - 5676, http://dx.doi.org/10.1109/CDC.2015.7403109

Argha A; Su SW; Lee S; Nguyen H; Celler BG, 2014, 'On heart rate regulation in cycle-ergometer exercise', in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Embc 2014, pp. 3390 - 3393, http://dx.doi.org/10.1109/EMBC.2014.6944350

Argha A; Li L; Su SW; Nguyen H, 2014, 'A new LMI-based robust Sliding Mode Control for the uncertain discrete-time systems', in Proceedings of the IEEE Conference on Decision and Control, pp. 4747 - 4752, http://dx.doi.org/10.1109/CDC.2014.7040129

Argha A; Li L; Su SW; Nguyen H, 2014, 'Controllability analysis of the first FM model of 2D systems: A row (column) process', in Proceedings of the IEEE Conference on Decision and Control, pp. 2414 - 2419, http://dx.doi.org/10.1109/CDC.2014.7039757

Argha A; Li L; Su SW; Nguyen H, 2013, 'The application of Discrete sliding mode control in parabolic PDE dynamics', in 2013 3rd Australian Control Conference Aucc 2013, pp. 152 - 157, http://dx.doi.org/10.1109/AUCC.2013.6697264

Argha A; Li L; Su SW, 2013, 'A new approach to applying discrete sliding mode control to 2D systems', in Proceedings of the IEEE Conference on Decision and Control, pp. 3584 - 3589, http://dx.doi.org/10.1109/CDC.2013.6760434

Sarvestani ZM; Argha A; Roopaei M, 2011, 'Using Iterative Learning Control methods for 2-D systems', in Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering Urke 2011, pp. 124 - 128, http://dx.doi.org/10.1109/URKE.2011.6007862

Afkhami H; Argha A, 2010, 'An optimal ILC method for two-dimensional systems', in Siisy 2010 8th IEEE International Symposium on Intelligent Systems and Informatics, pp. 511 - 517, http://dx.doi.org/10.1109/SISY.2010.5647072

Moattari M; Ahrari Nouri M; Argha A, 2010, 'Adopting fuzzy iterative learning control method for reactive power planning in distribution systems', in Peoco 2010 4th International Power Engineering and Optimization Conference Program and Abstracts, pp. 528 - 532, http://dx.doi.org/10.1109/PEOCO.2010.5559193

Argha A; Karimaghaee P; Roopaei M; Jahromi MZ, 2008, 'Fuzzy Iterative Learning Control in 2-D systems', in Ao SI; Gelman L; Hukins DWL; Hunter A; Korsunsky AM (eds.), WORLD CONGRESS ON ENGINEERING 2008, VOLS I-II, INT ASSOC ENGINEERS-IAENG, ENGLAND, Imperial Coll London, London, pp. 58 - +, presented at World Congress on Engineering 2008, ENGLAND, Imperial Coll London, London, 02 July 2008 - 04 July 2008, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000259580600010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Argha A; Karimaghaee P; Roopaei M, 2008, 'Iterative learning control for 2-D systems', in Proceedings of the International Joint Conference on Neural Networks, pp. 2164 - 2168, http://dx.doi.org/10.1109/IJCNN.2008.4634096

Conference Presentations

Celler B; Yong A; Rubenis I; Butlin M; Argha R; Rehan R; Avolio A, 2023, 'CAN RECORDING KOROTKOFF SOUNDS DURING BRACHIAL CUFF INFLATION PROVIDE MORE ACCURATE NON-INVASIVE ESTIMATES OF INTRA-ARTERIAL BLOOD PRESSURE?', http://dx.doi.org/10.1097/01.hjh.0000938960.09338.01

Preprints

Sadeghi A; Hajati F; Argha A; Lovell NH; Yang M; Alinejad-Rokny H, 2025, Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking, http://arxiv.org/abs/2505.01696v1

Lee S; Ni S; Wei C; Li S; Fan L; Argha A; Alinejad-Rokny H; Xu R; Gong Y; Yang M, 2025, xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking, http://dx.doi.org/10.48550/arxiv.2501.16727

Hansun S; Argha A; Bakhshayeshi I; Wicaksana A; Alinejad-Rokny H; Fox GJ; Liaw S-T; Celler BG; Marks GB, 2024, Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review (Preprint), http://dx.doi.org/10.2196/preprints.69068

Luo J; Chen L; Luo R; Zhu L; Ao C; Li J; Chen Y; Cheng X; Yang W; Su J; Argha A; Alinejad-Rokny H; Li C; Ni S; Yang M, 2024, PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation, http://dx.doi.org/10.48550/arxiv.2410.01504

Shamsi A; Becirovic R; Argha A; Abbasnejad E; Alinejad-Rokny H; Mohammadi A, 2024, ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance, http://dx.doi.org/10.48550/arxiv.2409.09251

Karami M; Jahanian K; Alizadehsani R; Argha A; Dehzangi I; Gorriz JM; Zhang Y; Hajati F; Yang M; Alinejad-Rokny H, 2023, Revolutionizing Genomics with Reinforcement Learning Techniques, http://dx.doi.org/10.48550/arxiv.2302.13268

Labani M; Beheshti A; Argha A; Alinejad H, 2023, An Integrative Analysis of Chromatin Interactions, Gene Expression and Genomic Variants Identifies 30 Likely Regulatory Variants in Prostate Cancer, http://dx.doi.org/10.20944/preprints202301.0343.v1

Nasab RZ; Ghamsari MRE; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2022, Deep Learning in Spatially Resolved Transcriptomics: A Comprehensive Technical View, http://arxiv.org/abs/2210.04453v3

Hansun S; Argha A; Liaw S-T; Celler BG; Marks GB, 2022, Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review (Preprint), http://dx.doi.org/10.2196/preprints.43154

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