activity
20232026
most citedAdaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments

5 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.GT2026

A Collaborative Artificial Intelligence as a Service Composition Dataset

Deepak Kanneganti, Sajib Mistry, Sheik Fattah +1

Artificial Intelligence as a Service (AIaaS) composition is an emerging research area that enables clients to combine multiple AI services to meet complex requirements. A recent ex…

cs.LG2026

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +3

Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environments, widely adopted across hea…

cs.AI2026

Designing Sustainable Federated Learning as a Service using Neural Architecture Search

Keya Patel, Sajib Mistry, Sheik Fattah +4

The sustainability constraints of FLaaS consumers pose significant challenges to maintaining carbon-feasible federated training in FLaaS environments. These constraints often lead…

cs.LG2026

Test-Time Adaptive Composition for Machine Learning as a Service (MLaaS) in IoT Environments

Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +1

The dynamic nature of Internet of Things (IoT) environments affects the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions. Existing adaptive composition…

cs.LG2026

Machine Learning as a Service (MLaaS) Dataset Generator Framework for IoT Environments

Deepak Kanneganti, Sajib Mistry, Sheik Fattah +2

We propose a novel MLaaS Dataset Generator (MDG) framework that creates configurable and reproducible datasets for evaluating Machine Learning as a Service (MLaaS) selection and co…

cs.LG2025★ 5 cited

Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments

Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +2

The dynamic nature of Internet of Things (IoT) environments challenges the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions. The uncertainty and variab…

cs.CL2023

A New cross-domain strategy based XAI models for fake news detection

Deepak Kanneganti

In this study, we presented a four-level cross-domain strategy for fake news detection on pre-trained models. Cross-domain text classification is a task of a model adopting a targe…