KAUST computer scientist Mohamed Elhoseiny and his VISION CAIR team developed Creative Walk Adversarial Networks (CWAN) for novel art generation. CWAN learns from existing art styles and deviates using 'random walk deviation' methods. Human evaluators preferred CWAN-generated art compared to other methods like StyleGAN2. Why it matters: The research demonstrates AI's potential as a valuable tool for artists, enabling the creation of unique and meaningful art, and explores more effective emotional language in image captioning.
KAUST will host a Modern Saudi Art Exhibit from Arabian Wings (Jan 11-15), an Al-Balad 24 Photography Exhibition featuring work by Marina Kochetyga and Andrea Bachofen (Jan 11-16), and an East African Tingatinga art exhibition (Jan 18-24). The Al-Balad exhibit includes a video by Dr. Lorenzo Pareschi documenting a fire in the historic district. Why it matters: These art exhibits expose the KAUST community to diverse artistic styles and cultural perspectives, fostering cross-cultural understanding.
Margaret Livingstone, a neurobiology professor at Harvard Medical School, lectured at KAUST's Winter Enrichment Program 2018 on how art can reveal insights into the human brain. She discussed how artists have long understood the independent roles of color and luminance in visual perception. Livingstone highlighted examples from Picasso, Monet, and Warhol to illustrate how artists manipulate visual cues. Why it matters: This interdisciplinary approach can potentially lead to new understandings of how the brain processes visual information and inform advances in both neuroscience and art.
Ivan Gromicho, a scientific illustrator at KAUST, creates visual representations of complex research findings for journals like Cell, Nature, and Science. He collaborates with KAUST faculty to transform data into comprehensible illustrations. Outside of work, Gromicho pursues rock climbing, exploring natural rock formations across Saudi Arabia. Why it matters: This highlights KAUST's support for interdisciplinary pursuits and employee well-being, fostering innovation at the intersection of science and art.
American artist Rachel Sussman spoke at KAUST's 2019 Winter Enrichment Program about her project documenting the world's oldest living organisms. Sussman photographed 30 species alive for over 2,000 years, including trees, coral, and bacteria. She collaborated with 30 scientists to identify and document these organisms. Why it matters: The lecture highlights KAUST's interdisciplinary approach to knowledge, connecting art, science, and philosophy to explore concepts of time and longevity.
KAUST Ph.D. student Amal Mohammed Alamri was a finalist in the July 2018 IEEE nanoArt Competition, part of the 18th IEEE International Conference on Nanotechnology in Cork, Ireland. Her work, displayed at University College Cork and Crawford/CIT Gallery, involved stacking n-type MoS2 single crystal with p-type perovskite CH3NH3PbBr3 single crystal. Alamri's IEEE Nano paper entitled "Photonic Single Crystal Heterostructures based on Perovskites/Molybdenum disulfide" was also presented at the conference. Why it matters: This highlights KAUST's contribution to nanotechnology research and its students' participation in international scientific events.
Artists from Switzerland collaborated with researchers at KAUST's Red Sea Research Center to photograph autonomous reef monitoring structures (ARMS). ARMS are artificial towers that capture small critters colonizing coral reefs, developed to measure marine biodiversity. KAUST has deployed and retrieved over 180 ARMS units since 2013 to study cryptobenthic biodiversity, which represents up to 70% of a reef's biodiversity. Why it matters: This collaboration highlights the innovative approaches being used to study marine ecosystems in the Red Sea and underscores the importance of interdisciplinary collaborations in advancing scientific understanding.
Researchers from Carnegie Mellon University and MBZUAI have developed a new method called ConceptAligner for precise image editing using AI. The system decomposes text embeddings into independent building blocks called atomic concepts, allowing users to make targeted tweaks without generating entirely new images. Their approach ensures that each latent factor maps to a specific user-controllable dial, enabling accurate concept-level modifications. Why it matters: This research addresses a major limitation in AI image generation, enhancing its usefulness in industries where precise control is crucial, such as advertising and medicine, and improving the reliability of AI-driven creative tools.