"Generative AI focuses on creating new data—such as text, images, or audio—by learning
patterns and structures from existing datasets. By using models like GPT, diffusion models,
and variational autoencoders, Generative AI can design realistic content, simulate scenarios,
and automate complex creative tasks. This technology enables advanced applications such as
automated content generation, synthetic data creation for training, and intelligent decision support.
As these models become more capable, understanding their reliability, ethics, and potential risks is
essential for building safe and trustworthy AI systems."
Witty Quote
“By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it." – Eliezer Yudkowsky
Publications at a glance
| # | Paper Title | Link | Publisher |
|---|---|---|---|
| C | Investigating the Efficacy of Machine Learning-Enhanced Mindfulness-Based Interventions for Individuals with Emotional and Intellectual Disabilities | Link | ResearchGate |
| C | FedRobo: Federated Learning Driven Autonomous Inter Robots Communication For Optimal Chemical Sprays | Link | Arxiv |
| C | Generative AI like ChatGPT in Blockchain Federated Learning: use cases, opportunities and future | Link | Arxiv |
Research Domain Interests
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Generative AI
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Security Enhancements
"AI uses machine learning and deep learning to recognize patterns on the network and cluster them, it will then detect deviations or security incidents from the norm before responding to them. These patterns can help to improve security in the future. Similar potential threats can be detected and blocked early enough."