KAUST Ph.D. student Matthias Müller won the Best Paper/Presentation Award at the 2nd International Workshop on Computer Vision for Unmanned Aerial Vehicles for his paper on teaching UAVs to navigate a racecourse autonomously. The paper, "Teaching UAVs to Race: End to End Regression of Agile Controls in Simulation," details research on training a deep neural network to predict UAV controls from raw image data. The research uses imitation learning with data augmentation to allow for correction of navigation mistakes, outperforming state-of-the-art methods. Why it matters: This award recognizes KAUST's contributions to computer vision and autonomous drone navigation, important areas for future applications in logistics, surveillance, and environmental monitoring in the region.
A robotics team from KAUST's Robotics, Intelligent Systems, and Control (RISC) lab won the "Best Air Team" special award and the European Global Navigation Satellite Systems Agency special prize at the European Robotics League Emergency Robots Challenge in Sevilla, Spain. The KAUST team, led by Kuat Telegenov and advised by Professor Jeff Shamma, competed against international teams in aerial robotic challenges. The competition aimed to encourage advancements in autonomous capabilities and seamless outdoor/indoor navigation for robots. Why it matters: The awards recognize KAUST's contributions to robotics research and highlight the importance of developing autonomous systems for emergency response and complex environments.
KAUST Ph.D. student Mohammad Shaqura was a finalist for the Best Student Paper Award at the IEEE International Conference. The award is from the Institute of Electrical and Electronics Engineers. The conference and award recognize outstanding contributions from student researchers in electrical and electronics engineering. Why it matters: This recognition highlights the growing talent pool and research capabilities in engineering fields at KAUST.
KAUST Ph.D. student Jinhui Xiong won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization in Germany for his paper "Stochastic Convolutional Sparse Coding". The paper, co-authored with KAUST Professors Peter Richtárik and Wolfgang Heidrich, introduces a novel stochastic spatial-domain solver for Convolutional Sparse Coding (CSC). The proposed algorithm outperforms state-of-the-art solutions in terms of execution time and offers an improved representation for learning dictionaries from sample images. Why it matters: This award recognizes significant research in efficient image representation and dictionary learning, contributing to advancements in visual computing and AI at KAUST.
KAUST master’s degree student Samuel Horváth won a best poster award at the Data Science Summer School (DS3) in Paris for his poster entitled "Nonconvex Variance Reduced Optimization with Arbitrary Sampling". The poster is based on a paper of the same name currently under review and is joint work between Horváth and his supervisor Professor Peter Richtárik from the KAUST Visual Computing Center. Horváth's research interests are at the interface of statistical learning and big data optimization, with a focus on randomized methods for non-convex problems. Why it matters: This award recognizes the quality of KAUST's research and its students' contributions to the field of data science and optimization.