My Projects
A collection of my work, from academic research to personal coding endeavors.
Enhancing Adaptive Learning, Communication, and Therapeutic Accessibility through the Integration of Artificial Intelligence and Data-Driven Personalization in Digital Health Platforms for Students with Autism Spectrum Disorder
Autism Spectrum Disorder (ASD) impacts millions worldwide, posing distinct obstacles in schooling, communication, and access to therapy. Conventional educational and therapeutic approaches, while sometimes helpful, frequently lack the adaptability and customization necessary to meet the varied needs of kids with ASD. This research tackles existing gaps by integrating advanced Artificial Intelligence (AI) techniques and data-driven personalization in digital health systems. This study presents a novel, AIdriven adaptive learning and treatment system specifically developed for kids with autism spectrum disorder (ASD). This research assesses the efficacy of AI-driven personalization in improving learning outcomes, communication skills, and therapeutic accessibility through the utilization of simulated experimental data. Adaptive machine learning algorithms, natural language processing, and reinforcement learning techniques were incorporated into digital platforms, resulting in tailored intervention models that dynamically adjust to the cognitive and communicative profiles of each learner. Results from the simulated experiments demonstrate substantial enhancements in tailored adaptive learning pathways, quantifiable progress in communication skills, and heightened therapeutic accessibility and engagement compared to conventional methods. The performance assessment of AI models reveals strong accuracy, responsiveness, and efficiency in customizing instructional and therapeutic content to meet individual learner requirements. This research enhances previous work by providing empirical insights and practical consequences, demonstrating how AI-driven devices can substantially improve educational experiences and treatment outcomes for kids with ASD. Future directions encompass empirical testing, ongoing enhancement of AI models, and additional investigation into scalable application options within educational and healthcare contexts.
Artificial Intelligence-Driven Business Analytics for IT Strategy: Advancing Decision-Making, Real-Time Insights, and Organizational Agility Through Intelligent Automation and Data Integration
In the current digital era, companies depend on business analytics powered by AI to modify their IT strategies and improve their ability to decide. AI with business intelligence, organizations process huge amounts of data quickly to get useful information that supports efficient work and gives them an edge over their competitors. The focus is on how using smart automation and integrated data allows IT governance to become proactive and enterprise planning to adapt. A combination of qualitative and quantitative methods is used in this study. Through surveys given to 300 IT experts and leaders from many industries. The experience with AI-driven analytics tools and how they see AI helping with strategic planning was recorded. Deep insight into these factors was gathered through interviews with 20 IT executives. The author used SPSS software for statistics on numbers and thematic coding on words to look for similar themes and links between AI adoption and IT plan results. AI technology in business analytics is shown to help companies react more quickly, support data-driven choices and ensure alignment between the business and IT. With intelligent automation, there is less complexity in operating the business and to real-time analytics, reactions to market changes are faster. Some integration obstacles and data quality issues did not stop organizations from achieving better innovation and standing out in the market. The research makes clear that AI is key to having successful data-based and flexible IT systems in the future.
Re-imagining Digital Transformation in the United States: Harnessing Artificial Intelligence and Business Analytics to Drive IT Project Excellence in the Digital Innovation
Digital transformation has become a defining megatrend of the 21st century, significantly changing the operations of governments, corporations, and communities. The amalgamation of artificial intelligence (AI), business analytics, and digital innovation in the United States has expedited technological transformation, presenting new opportunities and challenges for firms aiming to sustain global competitiveness. Digital transformation encompasses not just the integration of digital tools but also a profound organizational and social change in the utilization of data, technology, and human resources to generate value, enhance efficiency, and develop creative business models. This transformation centers on the quest for IT project excellence—executing technology-driven projects punctually, within financial constraints, and in accordance with strategic objectives while managing complications such as cybersecurity threats, stakeholder expectations, and swiftly changing innovation environments. The digital landscape of the United States is distinctive in its magnitude and intricacy, characterized by a combination of federal initiatives, private sector dominance, and worldwide impact on technological advancement. This creates an optimal environment for exploring how AI and business analytics may be utilized to redefine digital transformation and attain excellence in IT projects.