Skip to content
GCC AI Research

Search

Results for "Purdue University"

SSRC Partners with Purdue University on Game-Changing UAV Security Project

TII ·

TII's Secure Systems Research Center (SSRC) has partnered with Purdue University on a three-year cybersecurity project focused on ensuring the safe and efficient use of Unmanned Aerial Vehicles (UAVs) in urban environments. The collaboration will study security and resilience in cyber-physical and autonomous systems, addressing vulnerabilities in communication, navigation, and command and control. The project includes four phases: modeling and analysis of UAS security, developing algorithms for high-assurance autonomy, constructing an experimental environment, and testing mitigation strategies. Why it matters: The partnership enhances the UAE's capabilities in securing critical digital systems and fosters the growth of commercial autonomous drones and robots, opening new opportunities for enterprises.

International Experts to Board of Advisors at SSRC

TII ·

TII's Secure Systems Research Center (SSRC) in Abu Dhabi has appointed international experts to its Board of Advisors. The advisors have expertise in areas like autonomous computing, cyber-physical systems, and cryptology. The board includes experts from Khalifa University, NYU Abu Dhabi, Dubai Electronic Security Center, and Purdue University. Why it matters: The move strengthens the UAE's cybersecurity research capabilities and aligns with its focus on developing secure autonomous systems.

Discrete and Continuous Submodular Bandits with Full Bandit Feedback

MBZUAI ·

Vaneet Aggarwal from Purdue University presented new research on discrete and continuous submodular bandits with full bandit feedback. The research introduces a framework transforming discrete offline approximation algorithms into sublinear α-regret methods using bandit feedback. Additionally, it introduces a unified approach for maximizing continuous DR-submodular functions, accommodating various settings and oracle access types. Why it matters: This research provides new methods for optimization under uncertainty, which is crucial for real-world AI applications in the region, such as resource allocation and automated decision-making.

Self-Supervised Learning AI and AI for Molecular Biology

MBZUAI ·

Xiao Wang from Purdue University presented research on Adversarial Contrastive Learning (AdCo) and Cooperative-adversarial Contrastive Learning (CaCo) for improved self-supervised learning. He also discussed CryoREAD, a framework for building DNA/RNA structures from cryo-EM maps, and future work in deep learning for drug discovery. Wang's algorithms have impacted molecular biology, leading to new structure discoveries published in journals like Cell and Nature Microbiology. Why it matters: The research advances AI techniques for crucial tasks in molecular biology and drug discovery, with potential applications for institutions in the GCC region focused on healthcare and biotechnology.

Building and Validating Biomolecular Structure Models Using Deep Learning

MBZUAI ·

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.

Asymmetry Learning and OOD Robustness

MBZUAI ·

Bruno Ribeiro from Purdue University presented a talk on Asymmetry Learning and Out-of-Distribution (OOD) Robustness. The talk introduced Asymmetry Learning, a new paradigm that focuses on finding evidence of asymmetries in data to improve classifier performance in both in-distribution and out-of-distribution scenarios. Asymmetry Learning performs a causal structure search to find classifiers that perform well across different environments. Why it matters: This research addresses a key challenge in AI by proposing a novel approach to improve the reliability and generalization of classifiers in unseen environments, potentially leading to more robust AI systems.

The best and the brightest

KAUST ·

KAUST hosted the KAUST-NSF Research Conference on Interactive Electronics from January 30 to February 1. The conference featured speakers from Purdue University, Cornell University, and Saudi Aramco's EXPEC Advanced Research Center. Attendees from around the world gathered at KAUST for the event. Why it matters: The conference highlights KAUST's role as a hub for international collaboration and knowledge sharing in advanced electronics research within Saudi Arabia.