Muhammed Dawood | Pharmacogenomics and Personalized Medicine | Best Researcher Award

Mr. Muhammed Dawood | Pharmacogenomics and personalized medicine | Best Researcher Award

Computer Science Department | United Kingdom

Author Profile

Google Scholar

EARLY ACADEMIC PURSUITS

Muhammad Dawood's academic journey began with a Bachelor's in Computer Software Engineering from the University of Engineering and Technology (UET) Peshawar, Pakistan, where his thesis explored a novel approach for Quran learning using Neuro-Linguistic Programming (NLP) and Total Physical Interaction (TPI) in handheld devices. He continued his studies with a Master's in Computer Science from the Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, focusing on the analysis of hurricane satellite imagery.

PROFESSIONAL ENDEAVORS

Following his master's, Dawood gained teaching and industrial experience. As a Lecturer at the Department of Software Engineering, University of Science & Technology Bannu, Pakistan, he taught various courses, supervised undergraduate final year projects, and served as a coordinator. Additionally, he worked as a Machine Learning Engineer at INTAQSOL Islamabad, Pakistan, before embarking on his Ph.D. journey at the TIA Research Centre, Computer Science Department, University of Warwick.

CONTRIBUTIONS AND RESEARCH FOCUS ON PHARMACOGENOMICS AND PERSONALIZED MEDICINE

Dawood's contributions span a diverse range of projects, reflecting his expertise in computational pathology, genomic data science, machine learning, and software engineering. Notable projects include gene expression prediction, cellular composition prediction, and drug sensitivity prediction from histology images. His research also delves into hurricane intensity prediction, personalized aesthetic-based apparel recommendation, and sentiment analysis of Twitter tweets.

IMPACT AND INFLUENCE

Muhammad Dawood's impactful work is underscored by numerous achievements. He secured a fully funded studentship for his Ph.D. studies from GlaxoSmithKline and received the Best Paper Award at ICCV CDpath 2021. His teaching contributions as a Graduate Teaching Assistant at the University of Warwick further showcase his commitment to academic excellence.

ACADEMIC CITES

Dawood's research, particularly in the field of computational pathology and genomics, has likely garnered attention within the academic community. While specific citation metrics are not provided, his Best Paper Award at ICCV CDpath 2021 suggests recognition and appreciation for the quality of his work.

LEGACY AND FUTURE CONTRIBUTIONS

As a fourth-year Ph.D. student, Dawood's legacy includes a diverse portfolio of projects that contribute to the understanding of cellular processes, cancer therapy personalization, and drug design. His future contributions are anticipated to further advance the fields of machine learning, computational pathology, and genomic data science, leaving a lasting impact on personalized medicine and beyond.

Notable Publications

SlideGraph+: Whole slide image level graphs to predict HER2 status in breast cancer 2022(47)

Deep-PHURIE: deep learning based hurricane intensity estimation from infrared satellite imager  2020(37)

CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting 2023(5)