Muhammed Mohaimin Sadiq

This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.

Ph.D Candidate

UA Little Rock

Also affiliated: The University of Texas at Austin (2020)

Graduate Student Researcher

2 h-index 5 pubs 38 cited

Research Areas

Links

ORCID

OverviewAI-generated summary

Muhammed Mohaimin Sadiq's research focuses on the application of machine learning techniques for the detection of epileptic seizures using electroencephalogram (EEG) data. His work involves developing novel feature selection methods, specifically utilizing Hellinger distance, to improve classification accuracy. Sadiq has published research in this area, including work on novel EEG classification based on Hellinger distance for seizure epilepsy detection and novel EEG feature selection based on Hellinger distance for epileptic seizure detection.

He has a developing publication record with 5 total publications and 37 citations, achieving an h-index of 2. Sadiq collaborates with other researchers at the University of Arkansas at Little Rock, including Mariofanna Milanova, with whom he shares 2 publications. His most recent publication was in 2025, indicating his recent activity in the field.

Metrics

h-index: 2
Publications: 5
Citations: 38

Selected Publications

Novel EEG feature selection based on hellinger distance for epileptic seizure detection (2025)

Smart Health 14 citations DOI OpenAlex
Novel EEG Classification Based on Hellinger Distance for Seizure Epilepsy Detection (2024)

IEEE Access 24 citations DOI OpenAlex