Dottorando in Bioingegneria E Scienze Medico-chirurgiche , 37o ciclo (2021-2024)
Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS)
Collaboratore Esterno
Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS)
Profilo
Dottorato di ricerca
Titolo della tesi
Multimodal AI Tools for Predicting Developmental and Health Outcomes
Argomento di ricerca
Explainable machine learning aided computer vision targeting pathology dynamics
Tutori
Interessi di ricerca
Biografia
Syed Taimoor Hussain Shah (Pakistan, born in 1992) is currently a PhD scholar (Marie Curie Fellow; PARENT Project, Horizon 2020) at Politecnico di Torino (Turin, Italy) under the supervision of prof. Marco Agostino Deriu. He is currently working on explainable machine learning aided computer vision targeting pathology dynamics. He received his bachelor degree in Computer Science from Bahauddin Zakariya University, Multan, Pakistan in 2016. During this period, he focused on different computer courses such as programming languages, Operating Systems (Windows and Linux), Datastructure, Databases, Artificial Intelligence, etc. After that, he completed his master in Computer Science from Pakistan Institute of Engineering and applied sciences. During which, he specialized in Artificial Intelligence and Machine Vision including related areas such as Computer and Mobile Vision, Bioinformatics, Pattern Recognition, and Machine and Deep learning. Moreover, during his master thesis (Title: “Classification and Segmentation Models for Hyperspectral Imaging”), he employed the semi-supervised technique by using active learning and multinomial logistic regression on AVIRIS and INDIAN PINES datasets (3D Cubes: Spectral and Spatial information) for classification and segmentation of land regions.
Competenze
Settori ERC
SDG
Ricerca
Gruppi di ricerca
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Chaudhary, Qurat-ul-ain; Ahmad Qureshi, Shahzad; Sadiq, Touseef; Usman, Anila; Khawar, ... (2025)
SAlexNet: Superimposed AlexNet using Residual Attention Mechanism for Accurate and Efficient Automatic Primary Brain Tumor Detection and Classification. In: RESULTS IN ENGINEERING, vol. 25. ISSN 2590-1230
Contributo su Rivista - Dr Shahzad Ahmad Qureshi, Prof; Aziz ul Rehman, Dr.; Hussain, Lal; Sadiq, Touseef; Shah, ... (2024)
Breast Cancer Detection using Mammography: Image Processing to Deep Learning. In: IEEE ACCESS. ISSN 2169-3536
Contributo su Rivista - Shah, SYED ADIL HUSSAIN; Shah, SYED TAIMOOR HUSSAIN; Khaled, Roa’A; Buccoliero, Andrea; ... (2024)
Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning. In: JOURNAL OF IMAGING, vol. 10. ISSN 2313-433X
Contributo su Rivista - Pigueiras-del-Real, J.; Ruiz-Zafra, A.; Benavente-Fernandez, I.; Lubian-Lopez, S. P.; ... (2024)
NeoVault: empowering neonatal research through a neonate data hub. In: BMC PEDIATRICS, vol. 24. ISSN 1471-2431
Contributo su Rivista - Shah, SYED TAIMOOR HUSSAIN; Ahmad Qureshi, Shahzad; ul Rehman, Aziz; Shah, SYED ADIL ... (2021)
Classification and Segmentation Models for Hyperspectral Imaging - An Overview. In: Intelligent Technologies and Applications: Third International Conference, INTAP 2020, Grimstad, Norway, September 28–30, 2020
Contributo in Atti di Convegno (Proceeding)