Ali Othman Albaji Updated 【iOS HOT】

Arabic-optimized language processing and local AI system deployment. Pioneering the Libyan AI Ecosystem

: Operates alongside Alexis , a complementary proprietary deep learning system built by Dr. Albaji. 🏛️ Event Leadership and Institutional Influence

Albaji engineered , an advanced deep learning framework engineered for highly complex data pattern recognition. This proprietary architecture acts as the bedrock for his automated environmental and urban monitoring configurations. 3. Environmental Smart City Applications

Operating as the CEO of NOVACORTIX , Albaji steers an emergent global enterprise focusing on deep-tech consulting, enterprise AI integration, and cross-border innovation strategy. ali othman albaji updated

Directs a dedicated technical firm focused on custom AI consulting, strategic development, and edge processing deployment. General Chairperson

: Graduated with a Bachelor’s degree in Electrical Engineering, specializing in General Communications.

Albaji's specific code methodologies for smart cities, or would you prefer a deeper look into the ? Share public link Environmental Smart City Applications Operating as the CEO

: Engineered via advanced deep learning mechanisms to process high-scale datasets.

As the creator and executive supervisor of , Dr. Albaji built Libya's very first localized large language model. Trained on highly specialized datasets, LibiGPT emphasizes multi-language performance, enterprise-grade secure data handling, and cultural contextualization. The initiative represents a critical step toward national data sovereignty, reducing reliance on external, non-localized generalized models. Alexis Deep Learning Model

The study processed extensive acoustic datasets using algorithms such as Decision Trees, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Random Forest. The research proved that Random Forest architectures yield the highest accuracy for mapping multi-source urban sounds (e.g., trains, traffic, birds, and airports), giving urban planners concrete data analytics tools to implement effective noise-mitigation strategies. 2. Published Literature and wildlife. for Libya

: Evaluated 873 distinct audio samples capturing 16 different environmental noise categories, including railways, highways, airports, and wildlife.

for Libya, promoting cloud literacy and AI capacity building.

Ali Othman Albaji | Computer Science and Artificial Intelligence