Hesham A. Al-Mansouri

Research Associate at Kuwait Institute for Scientific Research

Me@Hesham.Tech

General

Kuwait University
M.Sc. Computer Science (2019)
Gulf University for Science & Technology
B.Sc. Computer Science (2014)

Kuwait Institute for Scientific Research
Research Associate

Systems and Software Development Department

2021 – Present

Conduct applied research to address and solve local problems in Kuwait, contributing to the advancement of scientific and technological solutions.

Gulf University for Science and Technology
Coordinator

Gulf Financial Center

2019 – 2021

Facilitated the use of advanced financial software and tools for students and academics, providing instruction and support to enhance applied finance education and research. Extended GFC services to corporate clients.


Teaching Assistant

Math Foundation Unit

2015 – 2019

Implemented innovative teaching models, promoted technology-driven learning, automated exam scheduling, and contributed to achieving NADE accreditation.

Azure Technologies
Managing Partner

2018

Founded and managed an IT and graphic design company with a focus on innovative software solutions, blending IT development with investment in creative ideas.

Global Investment House (Kamco Invest)
Analyst Programmer

IT Department, Development Unit

2014 – 2015

Led a programming team to efficiently develop multiple systems within tight deadlines while identifying and mitigating security vulnerabilities to safeguard company systems against potential threats.


Research

Unfunded Research Reward - Kuwait University

2024

For our paper Shortest Node-to-Node Disjoint Paths Algorithm for Symmetric Networks

Shortest Node-to-Node Disjoint Paths Algorithm for Symmetric Networks

Hesham Almansouri, Zaid Hussain

2024

Cluster Computing (Q1)

Disjoint paths are defined as paths between the source and destination nodes where the intermediate nodes in any two paths are disjoint. They are helpful in fault-tolerance routing and securing message distribution in the network. Several research papers were proposed to solve the problem of finding disjoint paths for a variety of interconnection networks such as Hypercube, Generalized Hypercube, Mesh, Torus, Gaussian, Eisenstein-Jacobi, and many other topologies. In this research, we have developed a general algorithm that constructs maximal node-to-node disjoint paths for symmetric networks where all paths are shortest. The algorithm presented in this paper outperforms other algorithms in finding not only the disjoint paths but shortest and maximal disjoint paths with a complexity of O(n2). In addition, we have simulated the proposed algorithm on different networks. The solution of unsolved problem in Cube-Connected-Cycles is given in the simulation results.

Interconnection network; Symmetric network; Edge disjoint; Disjoint paths; Fault-tolerant; Routing; Node-to-node

Panconnectivity algorithm for Eisenstein-Jacobi networks

Mohammad Awadh, Zaid Hussain, Hesham Almansouri

2023

Kuwait Journal of Science (Q2)

The cycles in an interconnection network are one of the communication types that are considered as a factor to measure the efficiency and reliability of the networks’ topology. The network is said to be panconnected if there are cycles of length l between two nodes u and v, for all l ​= ​d(u, v), d(u, v) ​+ ​1, d(u, v) ​+ ​2, , n ​− ​1 where d(u, v) is the shortest distance between u and v in a given network, and n is the total number of nodes in the network. In this paper, we propose an algorithm that proves the existence of panconnectivity of Eisenstein-Jacobi networks by constructing all cycles between any two nodes in the network of length l such that 3 ≤ l ​< ​n. The correctness of the proposed algorithm is given with the time complexity O(n4). The proposed algorithm adopts and modifies the idea of Dynamic Source Routing (DSR) to find all possible shortest paths. The results of some test cases using the proposed algorithm are provided.

Eisenstein-Jacobi networks; Fault-tolerant; Interconnection network; Panconnectivity; Pancyclic

The COVID-19 Pandemic and Instability of Stock Markets: An Empirical Analysis Using Panel Vector Error Correction Model

Yousef Abdulrazzaq, Mohammad Ali, Hesham Almansouri

2022

The Journal of Asian Finance, Economics and Business (Q2)

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

COVID-19; Stock Returns; Pedroni; VECM; Panel Data

AI-Driven Decision Support Systems for Enhancing Cybercrime Investigations
Project Leader
2024-2025

Developed machine learning models to predict case resolution times, assign the best officer for each case, and provide decision support for optimal investigation procedures.

Technologies
  • JavaScript
  • HTML/CSS
  • Python
  • Python ML Libraries
  • SQL (MSSQL)
Developing a Web-based Application to Assist Decision Makers of Charitable Organizations in Kuwait
Task Leader
2024-2025

Developed a machine learning model to predict high-impact philanthropic projects, supporting decision-making in charitable organizations.

Technologies
  • Python
  • Python ML Libraries
Generation of an Electronic Big Data Genome Wide Association Selection (GWAS) Atlas for Domestic Chicken Breeds
Task Leader
2022-2024

Led the collection of genomic data for chicken breeds and developed an online database with advanced search capabilities to support researchers.

Technologies
  • JavaScript
  • HTML/CSS
  • PHP
  • Python
  • SQL (MySQL)
Development of an Online Questioning System
Task Leader
2023

Created an online system to record and analyze interrogation results, enhancing investigative efficiency.

Technologies
  • JavaScript
  • HTML/CSS
  • Python
  • PHP
  • SQL (MySQL)
Development of a Machine Learning Model to Predict Criminal Characteristics
Project Leader
2022-2023

Built an ensemble machine learning model to predict criminal characteristics based on victim and crime information.

Technologies
  • Python
  • Python ML Libraries

Business

Real Estate Management System
Project Leader
2021-2022

Created a web application for managing real estate portfolios, including properties, units, contracts, maintenance, invoices, legal cases, and reporting.

Technologies
  • JavaScript
  • HTML/CSS
  • PHP
  • SQL (MySQL)
Automated Exam Time-slot Distribution Application
Project Leader
2016

Developed a program to schedule exam sessions for approximately 800 students, ensuring no time conflicts with their class schedules and minimizing the time students spend at the university.

Technologies
  • Python
  • SQL (MySQL)
Wealth Management System
Task Leader
2014-2015

Successfully developed a CRM web application for the wealth management department at Global Investment House.

Technologies
  • JavaScript
  • HTML/CSS
  • C#
  • SQL (Oracle)
Web Development
Project Leader
2014-Present

Developed multiple e-commerce and informational websites for various clients.

Technologies
  • JavaScript
  • HTML/CSS
  • Python
  • PHP
  • SQL (MySQL)

Training

Web Development Course
Duration: 5 Weeks

Year: 2023

Venue: KISR

Delivered a comprehensive Full-Stack Web Development course, encompassing HTML, CSS, JavaScript, PHP, MySQL, and fundamental concepts of web servers and programming.

Systems Penetration Testing - Level 1 Course
Duration: 1 Week

Year: 2024

Venue: Crime Investigation Department

Conducted an introductory course on penetration testing, covering command line interface basics, port scanning, directory enumeration, SQL injection, and password brute forcing, alongside essential concepts of networks and protocols.

Systems Penetration Testing - Level 2 Course
Duration: 1 Week

Year: 2024

Venue: Crime Investigation Department

Conducted an advanced penetration testing course focused on web application vulnerabilities, covering HTTP request modification, cookie and session manipulation, and exploiting Cross-Site Scripting (XSS) vulnerabilities. Participants learned techniques to prevent XSS and detect access control flaws, enhancing their ability to test and secure web applications.