KAUST Ph.D. student Sabrina Vettori won the 2017 Student Paper Competition sponsored by the Section on Statistics and the Environment of the American Statistical Association. Her winning paper was titled "Bayesian clustering and dimension reduction in multivariate air pollution extremes", co-authored by Huser and Genton. The competition focused on environmental statistics, with winners presenting at the Joint Statistical Meetings. Why it matters: This award recognizes KAUST's contribution to environmental statistics and highlights the university's ability to attract and nurture talent in this critical area.
KAUST Ph.D. alumna Sabrina Vettori and Ph.D. student Yuxiao Li received a Distinguished Student Paper Award at the 2018 Eastern North American Region (ENAR) Spring Meeting of the International Biometric Society. Li's paper focused on efficient estimation for non-stationary spatial covariance functions, while Vettori's paper addressed Bayesian hierarchical modelling of air pollution extremes. Both students were recognized for their contributions to statistical environmental studies and air pollution modeling. Why it matters: This award highlights KAUST's commitment to fostering high-quality research and recognizes the achievements of its students in addressing critical environmental challenges.
Former Saudi Research Science Institute (SRSI) student Abdullatif, now a junior at Berkeley, published a paper in the Journal of the American Chemical Society (JACS). The paper, "Isomerically Pure Tetramethylrhodamine Voltage Reporters," details the design, synthesis, and application of Rhodamine Voltage Reporters (RhoVRs). Abdullatif, who worked at KAUST during her SRSI program on carbon dioxide capture, plans to return for advanced studies. Why it matters: This highlights KAUST's role in nurturing young Saudi talent in STEM and contributing to high-impact scientific research.
Dr. Roberto Arrigoni, a research scientist at KAUST's Red Sea Research Center, has been awarded the international "Benazzi Lentati" prize in zoology by L'Accademia Nazionale dei Lincei in Rome. The biennial prize is dedicated to young researchers under 35 in organismic evolutionary zoology. Arrigoni's research focuses on the systematics, phylogeny, and biogeography of scleractinian corals from the Indo-Pacific, particularly the Red Sea coral fauna. Why it matters: This award recognizes KAUST's contributions to marine biology and highlights the importance of Red Sea research on coral biodiversity.
KAUST alumna Bedour Al-Sabban, who received her master's ('12) and Ph.D. ('16) from KAUST, currently works as a senior researcher in the Chemical Catalysts Department at SABIC. She credits KAUST for preparing her for work in industry and providing access to diverse perspectives and international collaborations. In 2015, she won second place in the Leadership Excellence for Women Awards & Symposium during a conference in Bahrain. Why it matters: This highlights KAUST's role in developing Saudi talent for key industrial positions and fostering leadership in STEM fields.
Giulia De Masi, Principal Scientist at the Technology Innovation Institute (TII) in Abu Dhabi, specializes in Collective Intelligence and Swarm Robotics. Her work focuses on designing emergent behaviors in robot swarms through local interactions, drawing inspiration from social insects. De Masi's background includes positions at academic institutions in the UAE and a PhD from the University of Rome La Sapienza. Why it matters: This highlights the growing focus on swarm robotics and collective intelligence research within the UAE, with potential applications in various industries.
Giovanni Puccetti from ISTI-CNR presented research on linguistic probing of language models like BERT and RoBERTa. The research investigates the ability of these models to encode linguistic properties, linking this ability to outlier parameters. Preliminary work on fine-tuning LLMs in Italian and detecting synthetic news generation was also presented. Why it matters: Understanding the inner workings and linguistic capabilities of LLMs is crucial for improving their reliability and adapting them to diverse languages like Arabic.
MBZUAI graduate Svetlana Maslenkova worked with Assistant Professor Mohammad Yaqub on a project focused on the earlier detection of kidney failure using tabular data. Maslenkova's master's thesis involved predicting Acute Kidney Injury (AKI) using Electronic Health Records (EHR), specifically the MIMIC-IV v2.0 database. She found that patient weight distribution was a factor in the severity of kidney failure. Why it matters: This research highlights the potential of AI and machine learning to improve healthcare outcomes through the analysis of often-overlooked tabular data in electronic health records.