Prince Hamandawana

Assistant Professor

Ajou University

South Korea

Research Interests

Explore related searches

Professors in South Korea Professors in Cybersecurity Cybersecurity professors in South Korea

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Prince Hamandawana is an Assistant Professor at Ajou University in South Korea. His research focuses on advanced topics in machine learning and data integrity, as evident from his recent publications on brain tumor detection, voice phishing detection, and frameworks for enhanced performance in storage systems. Additionally, he explores innovative solutions for fault tolerance and resource orchestration in scalable storage environments.

Articles (11)

Year:

2025

Year:

2025

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Year:

2020

Collaborators (3)

Tae‐Sun Chung

SOUTH KOREA

View details

Sungyong Park

Sogang University

SOUTH KOREA

View details

Ronnie Mativenga

Ajou University

SOUTH KOREA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Prince Hamandawana

Research Interests

Explore related searches

Contact this professor

About

Articles (11)

Improved EfficientNet Architecture for Multi-Grade Brain Tumor Detection

Enhancing Voice Phishing Detection Using Multilingual Back-Translation and SMOTE: An Empirical Study

Speed-Dedup: A New Deduplication Framework for Enhanced Performance and Reduced Overhead in Scale-Out Storage

CRBF: Cross-Referencing Bloom-Filter-Based Data Integrity Verification Framework for Object-Based Big Data Transfer Systems

ParSCL: A Parallel and Distributed Framework to Process All Nearest Neighbor Queries on a Road Network

TPBF: Two-Phase Bloom-Filter-Based End-to-End Data Integrity Verification Framework for Object-Based Big Data Transfer Systems

Accelerating ML/DL Applications with Hierarchical Caching on Deduplication Storage Clusters

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

FTRM: A Cache-Based Fault Tolerant Recovery Mechanism for Multi-Channel Flash Devices

Crocus: Enabling Computing Resource Orchestration for Inline Cluster-Wide Deduplication on Scalable Storage Systems

A Content Fingerprint-Based Cluster-Wide Inline Deduplication for Shared-Nothing Storage Systems

Collaborators (3)

Tae‐Sun Chung

Sungyong Park

Ronnie Mativenga

Make your next move.