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Results for "Robert Dibble"

KAUST professors named Fellows of The Combustion Institute

KAUST ·

KAUST Professors William Roberts and Robert Dibble were inducted as Fellows of The Combustion Institute (CI) in February. Roberts was recognized for his work on laminar flames, turbulent combustion, and soot formation at elevated pressures. Dibble was inducted for exceptional contributions to developing and using laser diagnostics for combustion research. Why it matters: This recognition highlights KAUST's contributions to combustion research and strengthens its position as a leading institution in the field, attracting top students and researchers.

Tackling food security through genetic technology

KAUST ·

Dr. John Bedbrook of DiCE Molecules LLC spoke at KAUST about the challenges of feeding a growing population with increasingly stressed arable land. He noted the increasing demand for meat in emerging economies exacerbates the problem. Bedbrook emphasized the role of genetics and hybridization in improving crop yields and quality to address food security. Why it matters: Investments in agricultural biotechnology are crucial for the GCC region to enhance food security and reduce reliance on imports amid changing climate conditions.

Diffusion-BBO: Diffusion-Based Inverse Modeling for Online Black-Box Optimization

arXiv ·

This paper introduces Diffusion-BBO, a new online black-box optimization (BBO) framework that uses a conditional diffusion model as an inverse surrogate model. The framework employs an Uncertainty-aware Exploration (UaE) acquisition function to propose scores in the objective space for conditional sampling. The approach is shown theoretically to achieve a near-optimal solution and empirically outperforms existing online BBO baselines across 6 scientific discovery tasks.

Five-week writing experience leads to KAUST enrollment

KAUST ·

James Scott Berdahl, originally a science writer, first came to KAUST for a five-week writing program covering the 2014 Winter Enrichment Program. Impressed by the opportunities, he applied and was accepted as a Ph.D. student in Earth Science and Engineering under Professor Matthew McCabe. He appreciates the resources at KAUST that enable ambitious research. Why it matters: This highlights KAUST's ability to attract international talent and convert short-term engagements into long-term academic pursuits, strengthening its research community.

Bredas honored at 251st American Chemical Society National Meeting

KAUST ·

This article mentions KAUST in the context of the 251st American Chemical Society National Meeting. However, it contains no specific details about AI or related research activities. The content is primarily a copyright notice for King Abdullah University of Science and Technology. Why it matters: This mention provides minimal information about KAUST's involvement in the event and lacks substantial AI-related content.

Making the invisible, visible

KAUST ·

This is an advertisement for KAUST Discovery Associate Professor of Computer Science Ivan Viola. The ad promotes KAUST as a university. Why it matters: This reflects KAUST's ongoing efforts to attract international faculty and promote its research programs.

Prof. Mérouane Debbah Receives Double Accolade: Ranks No.1 in France, and 180th globally among Top 1,000 Scientists, and among the 2,000 most influential scholars for Internet of Things for 2022.

TII ·

Prof. Mérouane Debbah, Chief Researcher at the AI Cross-Center Unit and DSRC, has been ranked No. 1 in France and 180th globally in Electronics and Electrical Engineering by Research.com. He has an H-index of 98 and over 47000 citations. Debbah was also recognized as a 2022 AI 2000 Most Influential Scholar in Internet of Things for contributions between 2012 and 2021. Why it matters: This recognition highlights the growing AI research talent within the GCC region, particularly in areas related to communication technologies and IoT.

Student Focus: Adel Bibi

KAUST ·

KAUST Ph.D. student Adel Bibi is researching how to bridge the gap between theory and practice in deep learning, focusing on the mathematical understanding of deep learning models. Bibi is currently interning at Intel in Munich and previously worked on various computer vision problems. He aims to use optimization and mathematics to better understand deep learning models and build better models systematically from theory. Why it matters: This research contributes to the fundamental understanding of deep learning, potentially leading to more efficient and reliable AI systems developed in the region.