Recent Research Interest

Dr. Hamdy S. Soliman’s research is centered on machine learning and neural network modeling, with emphasis on classification, association, and generalization in complex systems. His work includes a wide range of ANN models, such as LVQ, BP, BAM, Hopfield AM, ART, and KSOFM, applied to big data analytics, cloud computing management, intelligent sensor networks, and image processing.

His research further focuses on the development of smart and secure wireless sensor networks (SS-WSNs) for early detection of critical asynchronous events, including forest fires, border intrusion, environmental hazards, and disease progression, enabling real-time prediction and intelligent decision-making.

Dr. Soliman has also contributed to network security, developing novel encryption mechanisms and secure communication protocols, resulting in five U.S. patents. His recent work extends to machine learning applications in healthcare, particularly early cancer detection and subtype identification using high-dimensional data.

Currently, his research group includes two Ph.D. students and multiple undergraduate and graduate researchers, working on interdisciplinary problems spanning machine learning, sensor networks, and security, with outcomes reflected in peer-reviewed publications and patented technologies.

Research Labs

Smart & Secure Sensor Lab
This research lab is used to develop "smart" and "secure" wireless sensor network to detect asynchronous events such as forest- fire, volcanic eruption, border intrusion, seismic activity, etc., with the help of the neural networks security sibling labs.
Security Lab
The major task of this lab is to secure cyber and cellphone communication. Our novel encryption algorithm and security protocol(to be compared to the known CCMP)which is more advance than even existing government standard e.g. AES, CCMP. Most recent activity is the development of cross Atlantic security communication tested successfully, with our protocol; and the development of secure cellphone Apps and progressing API and plugin. The work is managed and supported by NMT Research Foundation.
Neural Networks (NNs) Lab
The Neural networks lab is used to model diffrent NNs intelligent algorithms (training and operating)to add intelligence (smartness) which is much needed in many vital scientific application such cloud computing management, big data mining, sensor networks applications and any scientific application that requires intelligence. Hence, the lab can be easly used as interdisciplinary reseach for other departments to carry in softcomuting applications. In addition,in this lab he is implementating his image compression patent.

Research Grants and Contracts

Advances in Machine Learning Methods: Methodologies for a Data Science Approach to Applications of Genetics

2021

$76,944

by LANL
PI: Dr. Subhasish Mazumdar | My Role: Co-PI

An Intelligent Management System for Large Scale Cloud Data Centers

2016

$25,000

by NASA & NMSGC

On-Demand, Distributed, In-Memory Computing for Big Data Processing

2015

$25,000

by NASA & NMSGC

Volunteer Cloud Federation to Enable Data- and Compute-Intensive Scientific Applications

2012-2013

$25,000

by NASA & NMSGC

Equipment for a Computer Networks Laboratory

1992-1995

$48,674

by National Science Foundation, Instrumentation and Laboratory Improvement Program
with Dr. George A. Cunningham, III

A Task-Grain Very High Level Language for Data-Driven Multiprocessing system

1991-1993

$60,000

by Sandia National Laboratories