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Alumnus innovator builds AI venture

MBZUAI ·

MBZUAI alumnus Abdulwahab Sahyoun launched SnowHeap LLC, an AI-powered data analytics company. Sahyoun, a machine learning engineer with roots in Lebanon, aims to provide strategic tech consulting and develop in-house AI products. He was inspired by MBZUAI and the UAE's startup ecosystem to pursue his entrepreneurial ambitions. Why it matters: The story highlights MBZUAI's role in fostering AI entrepreneurship and the UAE's attractiveness for AI ventures.

Visualizing and experiencing science at WEP 2016

KAUST ·

KAUST's Winter Enrichment Program (WEP) 2016 featured a poster competition highlighting research by graduate students, postdocs, and international undergraduates. A science fair included shows by science podcast host Dr. Chris Smith, art exhibits, and a visualization lab. Exhibits included "On the Trail of the Glaciers: An Interactive Experience" and short films produced by KAUST students. Why it matters: Such programs foster scientific engagement and communication within the KAUST community and beyond.

A platform for material scientists

KAUST ·

Scimagine is a KAUST-based startup that provides a cloud-based platform for managing and storing experimental data for material scientists. The platform allows researchers to store, manage, and share their data, as well as create scientific visuals. It addresses the problem of experimental data being hidden in PDF files and not easily searchable. Why it matters: This platform improves data accessibility and collaboration in materials science research, potentially accelerating discovery and innovation in the field.

Smart Waste Management System for Makkah City using Artificial Intelligence and Internet of Things

arXiv ·

A research paper proposes a smart waste management system called TUHR for Makkah, Saudi Arabia, leveraging IoT and AI to handle waste accumulation during the annual pilgrimage. The system uses ultrasonic sensors to monitor waste levels and gas detectors to identify harmful substances, alerting authorities when containers are full or hazards are detected. The proposed system aligns with Saudi Vision 2030 by promoting sustainability and improving public health through optimized waste management.

On Optimizing Mobile Memory, Storage, and Beyond

MBZUAI ·

Prof. Chun Jason Xue from the City University of Hong Kong presented research on optimizing mobile memory and storage by analyzing mobile application characteristics, noting their differences from server applications. The research explores system software designs inherited from the Linux kernel and identifies optimization opportunities in mobile memory and storage management. Xue's work aims to enhance user experience on mobile devices through mobile application characterization, focusing on non-volatile and flash memories. Why it matters: Optimizing mobile systems based on the unique characteristics of mobile applications can significantly improve device performance and user experience in the region.

WEP 2024 showcases the digital future coming

KAUST ·

KAUST's Winter Enrichment Program (WEP) 2024 focused on the theme "Digital Adventure – ride to the future," featuring lectures and activities related to machine learning, AI, and the future of technology. Speakers covered topics from quantum computing and robotics to smart cities and sustainable economies. Rick Fox discussed his company Partanna's work on revolutionizing concrete production with KAUST's Carlos Duarte as an advisor. Why it matters: The event highlights KAUST's role in fostering discussions around cutting-edge technologies and their impact on various sectors within the Kingdom and globally.

BRIQA: Balanced Reweighting in Image Quality Assessment of Pediatric Brain MRI

arXiv ·

This paper introduces BRIQA, a new method for automated assessment of artifact severity in pediatric brain MRI, which is important for diagnostic accuracy. BRIQA uses gradient-based loss reweighting and a rotating batching scheme to handle class imbalance in artifact severity levels. Experiments show BRIQA improves average macro F1 score from 0.659 to 0.706, especially for Noise, Zipper, Positioning and Contrast artifacts.