Ali Haider Khan - AI - Best Researcher Award

Ziauddin University - Pakistan

AUTHOR PROFILE

SCOPUS

EXPERIENCE

Ali Haider Khan is a seasoned biomedical engineer with extensive experience across various hospitals and enterprises in Pakistan. His tenure at Bahawal Victoria Hospital involved working with clinical laboratory equipment, ensuring their optimal functionality. At Al-Qadir Enterprises, his role in Radiology, Ultrasound, and Operating Theaters showcased his commitment to enhancing patient care. His earlier internships at Doctor’s Hospital and Ziauddin Hospital provided him with a solid foundation in biomedical engineering, covering aspects from service and safety to supply chain management.

UNIVERSITY PROJECTS

Ali's academic projects demonstrate his innovative spirit and technical expertise. His pioneering work on the real-time recognition of Pakistani Sign Language through a web application highlights his proficiency in using CNN and LSTM models. Additionally, his research on the trans-vascular transport efficiency of nanoparticles in tumor microenvironments via Computational Fluid Dynamics (CFD) shows his adeptness in using Ansys software. His project on anxiety detection and massage-based control through pulse oximetry exemplifies his ability to combine technology and healthcare for therapeutic solutions.

SKILLS & INTERESTS

Ali is well-versed in frontend development, Python, Microsoft Azure, and various other technical tools like Visual Studio and Jupyter Notebook. His creative skills extend to Photoshop and Canva, and he is an effective communicator. Outside of his professional interests, Ali enjoys playing cricket and table tennis and has a keen interest in researching economic issues.

ACHIEVEMENTS

Ali's accomplishments are a testament to his dedication and continuous learning. He completed a crash course on Python by Google and participated in the 7th All Pakistan DUHS-DICE Health Innovation Exhibition. His proficiency in the German language was honed at the Goethe Institute, Karachi. He also attended the IEEE Asia Pacific Comsoc Summer School on Autonomous Systems and completed courses on web development and artificial intelligence from prestigious institutions like the University of Michigan and Accenture.

MEMBERSHIPS

Ali is an active member of several esteemed organizations, including the Harvard Business School Club of Pakistan, the Institute of Electrical and Electronics Engineers (IEEE), and the Society for Peace and Harmony. These memberships reflect his commitment to professional development and community engagement.

PUBLICATIONS

Ali has contributed significantly to the field of biomedical engineering and computer science through his publications. His work on the recognition and classification of the Urdu sign language dataset was published in PeerJ Computer Science. He also co-authored papers on deep learning approaches to Pakistani Sign Language recognition and the simulation of transvascular transport of nanoparticles in tumor microenvironments, published in top journals like Scientific Reports and Engineering Applications of Artificial Intelligence.

FUTURE DIRECTIONS

Looking ahead, Ali aims to further his research in biomedical engineering, focusing on innovative solutions that bridge technology and healthcare. His future projects will continue to explore advanced applications of artificial intelligence and computational methods to improve patient care and medical outcomes.

NOTABLE PUBLICATION

Simulation of Transvascular Transport of Nanoparticles in Tumor Microenvironments for Drug Delivery Applications

Authors: Shabbir, F., Mujeeb, A.A., Jawed, S.F., Khan, A.H., Shakeel, C.S.
Year: 2024
Journal: Scientific Reports
Volume: 14

A Neural-Network Based Web Application on Real-Time Recognition of Pakistani Sign Language

Authors: Mujeeb, A.A., Khan, A.H., Khalid, S., Mirza, M.S., Khan, S.J.
Year: 2024
Journal: Engineering Applications of Artificial Intelligence

A Computer Vision-Based System for Recognition and Classification of Urdu Sign Language Dataset

Authors: Zahid, H., Rashid, M., Syed, S.A., Mujeeb, A.A., Khan, A.H.
Year: 2022
Journal: PeerJ Computer Science

ACADEMIC AND PROFESSIONAL BACKGROUND

Fangyu Wu is a distinguished researcher and academic in the field of computer science, specializing in deep learning, multi-modal learning, and intelligent data analysis. He is currently an Associate Professor at Xi’an Jiaotong-Liverpool University (XJTLU) in China, where he supervises PhD and Master's students focusing on innovative research topics such as multi-modal learning and deep learning for computer vision. His previous role included co-supervising PhD students at Zhejiang University, contributing to advancements in facial recognition and image-text retrieval.

HONORS AND AWARDS

Dr. Wu's achievements have been recognized through several prestigious awards. He was named a Suzhou Youth Innovation Leading Talent in 2023 and won first prize at the 7th China Innovation Challenge for his project on intelligent tracking systems using infrared thermal imaging. Additionally, he received the Lotfi Zadeh Best Paper Award at ICMLC&ICWAPR 2017 and has been honored with the Outstanding Graduates award from Xi’an Jiaotong-Liverpool University and National Encouragement Scholarships from China.

RESEARCH PROJECTS

Fangyu Wu leads several high-impact research projects. These include “Intelligent Multimodal Data Analysis for Digital Twin Cities” under the Gusu Innovation and Entrepreneurship Leading Talents Programme, and “Relational Modeling and Reasoning for Reliable Cross-Modal Retrieval” funded by the Zhejiang Natural Science Foundation. His projects also cover advanced topics such as distributed AI platforms for Metaverse scenarios and optimization software for injection molding processes.

PUBLICATIONS

Dr. Wu has an extensive list of publications in top-tier conferences and journals. Notable works include papers on fine-grained image-text matching, relation-aware prototype networks, and pose-robust face recognition. His research has been featured at prestigious conferences such as CVPR, ECCV, and ICPR, showcasing his contributions to advancements in deep learning and computer vision.

CONFERENCE ORGANIZATION

In addition to his research, Fangyu Wu plays a vital role in organizing academic conferences. He served as the Publication Chair for the IEEE 17th International Conference on Computer Science & Education (ICCSE 2022) and as General Co-Chair for the 5th International Symposium on Emerging Technologies for Education (SETE 2020). His involvement ensures the smooth execution of these events and contributes to the dissemination of cutting-edge research.

STUDENT SUPERVISION

Fangyu Wu is actively engaged in supervising students at both the PhD and Master’s levels. He currently supervises a PhD student at XJTLU focusing on multi-modal learning and has previously co-supervised a PhD student at Zhejiang University on deep learning for computer vision. His mentorship extends to six Master’s students at XJTLU and three at Zhejiang University, covering areas such as facial recognition and image-text retrieval.

COMPETITIONS AND RECOGNITION

Dr. Wu has achieved notable success in various competitions. His project on human motion recognition based on deep neural networks won third prize at the China First Smart Manufacturing and Big Data Innovation Competition. Additionally, his participation in competitions has been marked by significant awards, including the first prize in the China Innovation Challenge for his intelligent tracking system.

NOTABLE PUBLICATION

Fine-grained Image-text Matching by Cross-modal Hard Aligning Network

Authors: Pan, Z., Wu, F., Zhang, B.
Year: 2023
Conference: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
Pages: 19275–19284

Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification

Authors: Li, J., Chen, Q., Wang, W., Wu, F.
Year: 2023
Conference: IEEE International Conference on Smart Computing (SMARTCOMP)
Pages: 222–224

Kernel Triplet Loss for Image-Text Retrieval

Authors: Pan, Z., Wu, F., Zhang, B.
Year: 2022
Conference: Computer Animation and Virtual Worlds
Article: e2093

FaceCaps for Facial Expression Recognition

Authors: Wu, F., Pang, C., Zhang, B.
Year: 2021
Conference: Computer Animation and Virtual Worlds
Article: e2021