Pierre Baldi from UC Irvine presented applications of AI to biomedicine, covering molecular-level analysis of circadian rhythms, real-time polyp detection in colonoscopy videos, and prediction of post-operative adverse outcomes. He discussed integrating AI in future AI-driven hospitals. The presentation was likely part of a panel discussion hosted by MBZUAI in collaboration with the Manara Center for Coexistence and Dialogue. Why it matters: This highlights the growing interest in AI applications within the healthcare sector in the UAE, particularly through institutions like MBZUAI.
Fatima Ali AlNuaimi from the Autonomous Robotics Research Center (ARRC) had two research papers on brain-computer interface (BCI) technology published at the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2022. The papers are titled “Real-time Control of UGV Robot in Gazebo Simulator using P300-based Brain-Computer Interface” and “Secure Password Using EEG-based BrainPrint System: Unlock Smartphone Password Using Brain-Computer Interface Technology”. AlNuaimi is recognized as a young Emirati scientist advancing BCI knowledge in the UAE. Why it matters: This highlights growing BCI research capabilities in the UAE and the contributions of Emirati researchers to this emerging field.
This article discusses the use of artificial intelligence in precision oncology, particularly in understanding individual tumor mechanisms and aiding clinical decision-making. Dr. Xinghua Lu, with extensive experience in medicine and biomedical informatics, will present research on individualized Bayesian causal inference methods for investigating oncogenic mechanisms. These methods aim to provide clinical decision support at the cellular, tumor, and patient levels. Why it matters: AI-driven precision oncology can enable more personalized and effective cancer treatments, improving patient outcomes in the region and globally.
Daisuke Kihara from Purdue University presented a seminar at MBZUAI on using deep learning for biomolecular structure modeling. His lab is developing 3D structure modeling methods, especially for cryo-electron microscopy (cryo-EM) data. They are also working on RNA structure prediction and peptide docking using deep neural networks inspired by AlphaFold2. Why it matters: Applying advanced deep learning techniques to biomolecular structure prediction can accelerate drug discovery and our understanding of molecular functions.
MBZUAI Visiting Professor Haiyan Huang is working on bridging biology and AI by incorporating domain knowledge into modeling frameworks. She combines statistical principles, AI tools, and domain expertise to develop scientifically informed and statistically grounded methods. Her work addresses the challenge of extracting meaningful signals from complex biological data.
KAUST Ph.D. student Mohamed Bahloul received a best paper award at the IEEE Engineering in Medicine and Biology Society (EMBC ‘18) for the Africa and Middle East region. Bahloul's paper presented a three-element fractional-order viscoelastic Windkessel model developed in the EMAN group at KAUST. The model incorporates a fractional-order capacitor, potentially enabling earlier prediction of cardiovascular diseases. Why it matters: The award recognizes impactful research in biomedical engineering at KAUST and highlights the potential for advanced modeling techniques to improve healthcare in the region.
Michael Waterman, professor at USC, and Wei Wang, director at UCLA, gave keynote addresses at KAUST. Charlotte Hauser, KAUST professor of bioscience, also gave a keynote lecture. Peer Bork (EMBL) and Martin Noble spoke with Vladimir Bajic at the event. Why it matters: This indicates KAUST's ongoing engagement with international experts to advance research in computational biology.