MBZUAI presents research at GSRC Dubai

Nine MBZUAI students and researchers presented their latest findings at the Graduate Student Research Conference (GSRC) held in Dubai in March 2022. The group, led by MBZUAI Assistant Professor of Computer Vision, Mohammad Yaqub, presented on a range of topics including deep learning, computer learning, disease prediction, and other topics related generally to AI in healthcare.

The students are part of the BioMedIA (BioMedical Image Analysis) lab, headed up by Yaqub, which aims to investigate real-world healthcare problems using Artificial Intelligence. Yaqub founded the lab to be a “world leading research center focused on solving real-world, health-related problems using AI.”

Healthcare research in focus

Sevim Cengiz

Doctoral candidate Sevim Cengiz gave a poster presentation on her paper entitled: “Deep Learning-based Quality Assessment of Clinical Protocol Adherence in Fetal Ultrasound Dating Scans”. Cengiz is a Ph.D. candidate in the Computational Imaging Lab (CIL) at Boğaziçi University in Istanbul, Turkey, and a part-time research assistant in the BioMedical Image Analysis (BioMedIA) lab at MBZUAI. Learn more: A researcher’s life: Cengiz shares her story>

Ikboljon Sobirov

Computer vision master’s student Ikboljon Sobirov is currently working on automating head and neck cancer diagnosis and prognosis using deep learning. He and his colleagues were able to publish two papers on that topic and have won challenges at previous international conferences including MICCAI, which is one of the biggest in the medical field. Sobirov gave a poster presentation entitled: “An ensemble approach for patient prognosis of head and neck tumor using multimodal data”.

Sayed Hashim

Sayed Hashim is studying a master’s in machine learning. Hashim gave an oral presentation entitled: “SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification”. Learn more: Dedicated to AI cancer solutions>

Diego Oswaldo Sáenz Penafiel

MBZUAI graduate student Diego Oswaldo Sáenz Penafiel gave an oral presentation entitled: “Disease risk prediction using generative pre-trained transformers with EHR.” Sáenz graduated with a bachelor’s in physics from the University of Melbourne before attending MBZUAI and working as a research intern at Oxford Immune Algorithmics Ltd.

Rand Emad Saleh Muhtaseb and Mohamed Saeed

Segmentation of the heart’s left ventricle is an important step in assessing cardiac function and diagnosis of disease. Two MBZUAI students, Rand Emad Saleh Muhtaseb and Mohamed Saeed, collaborated on published research that focuses on the use of self-supervised learning to improve automated segmentation of the left ventricle in ultrasound images of the heart. The pair delivered an oral presentation based on their paper at GSRC entitled: “Is Contrastive Learning Suitable for Left Ventricular Segmentation in Echocardiographic Images?”

Hussain Ali Jaffar Hassan Alasmawi

Master’s student in machine learning Hussain Alasmawi delivered an oral presentation entitled: “Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?” Alasmawi is a graduate of the United Arab Emirates University where he earned a bachelor’s degree in mathematics before attending MBZUAI.

Muhammad Ridzuan

Muhammad Ridzuan is a graduate research assistant at MBZUAI. He gave an oral presentation at UAE GSRC entitled: “Computer Assisted Diagnosis of Tuberculosis: A Case Study in the Detection and Localization of TB from Chest X-rays”. Ridzuan has had a highly successful path through Iowa State University, Saudi Aramco, and most recently as an AI consultant before coming to MBZUAI.

Ameera Bawazir

Ameera Bawazir is undertaking a master’s in machine learning at MBZUAI. She gave an oral presentation at UAE GSRC entitled: “AI Driven segmentation of infection in COVID-19 lung CT scans”. Bawazir is a graduate of Khalifa University where she earned a bachelor’s degree in applied mathematics and statistics (with a concentration in biology) before attending MBZUAI. Learn more: A conversation with Women in AI founders>