Dr. Asadi Srinivasulu

Visiting Professor

University of Newcastle Australia

Australia

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About

Dr. Asadi Srinivasulu is a Visiting Professor at the University of Newcastle in Australia. His research areas encompass climate-smart agriculture, machine learning applications in predictive modeling, cybersecurity enhancements, and health data analysis. Recent articles authored by Dr. Srinivasulu explore the adoption of agricultural interventions, arsenic and cadmium modeling in rice, and advanced threat mitigation techniques utilizing deep learning. He is also engaged in innovative approaches to disease detection and academic support for mathematics education.

Articles (19)

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2025

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2023

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2023

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2023

Collaborators (1)

Mohammad Mahmudur Rahman

Associate Professor

Newcastle University

AUSTRALIA

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Dr. Asadi Srinivasulu

Research Interests

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Articles (19)

Multivariate and predictive modelling of arsenic and cadmium in rice: Influence of origin, grain type, and processing

Constraints and prospects of adoption of climate smart agriculture interventions: Implication for farm sustainability

Predictive Modeling of Mean Residence Time in Bubble Column Reactors: A Machine Learning Approach Using Linear Regression, Random Forest, and Neural Networks

COVID-19 health data prediction: a critical evaluation of CNN-based approaches

Enhancing cybersecurity through script development using machine and deep learning for advanced threat mitigation

Hybrid AI and semiconductor approaches for power quality improvement

Embedding and Siamese deep neural network-based malware detection in Internet of Things

Automatic Detection and Classification of Eye Diseases from Retinal Images Using Deep Learning: A Comprehensive Research on the ODIR Dataset

A Critical Review of Climate Change Impacts on Groundwater Resources: A Focus on the Current Status, Future Possibilities, and Role of Simulation Models

Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model

Myocarditis detection using proximal policy optimization and mutual learning

Enhancing Education through AI: Tailored Learning for Future Generations

Automatic Speech Recognition through Artificial Intelligence

Enhancing Monkeypox Detection through Data Analytics: A Comparative Study of Machine and Deep Learning Techniques

Performance and Improvement of Linguistic Data Analysis on Different Languages Using Deep Learnedness Techniques

Optimizing Nonlinear Distortion and Interference in MC-CDMA Receivers Employing Deep Neural Networks

Intelligent Energy Management for Distributed Power Plants and Battery Storage

Dynamic Behavior and Stability Analysis of Automatic Voltage Regulator with Parameter Uncertainty

Advances in Nanoscience and Nanotechnology

Collaborators (1)

Mohammad Mahmudur Rahman

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