We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

Security researchers uncovered a range of cyber issues targeting AI systems that users and developers should be aware of — ...

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

A research team has developed a new model, PlantIF, that addresses one of the most pressing challenges in agriculture: the ...

Saurabh Misra work spans machine learning, large-scale systems, and software performance, with a consistent focus on building faster, more efficient, and more sustainable technology.

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

But an internal research project is looking at ways to automate the translation of millions of lines of code per month into ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Abstract: The proliferation of Internet of Things (IoT) devices has increased susceptibility to Distributed Denial of Service (DDoS) attacks, exposing the limitations of traditional security ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...