.NET Foundation member and Software Egineer with over ten years of professional experience in software design and development,
specializing in building scalable, maintainable, and high-quality systems. My work is grounded in clean architecture principles and
disciplined engineering practices, with expertise spanning mathematical optimization, system architecture, algorithmic problem solving,
and AI/ML-driven solutions.
I bring strong analytical thinking, clear communication, and effective interpersonal skills, enabling me to collaborate across teams and
translate complex requirements into practical solutions. A fast learner who performs well under pressure and consistently meets tight deadlines,
I am adaptable to emerging technologies and committed to continuous improvement. Equally effective working independently or within cross-functional
teams, I maintain a strong focus on precision, quality, and delivering measurable impact.
- Design and implement software for cardiology and ultrasound devices, as well as associated digital healthcare platforms. This includes developing reliable, high-performance applications that support medical imaging workflows and device integration. The work involves close collaboration with domain experts to ensure clinical accuracy, regulatory compliance, and usability in healthcare environments. Additionally, it covers the development of backend services and APIs that enable secure data exchange, interoperability between systems, and integration with imaging standards such as DICOM.
- Research Assistant at the Arctic Green Computing Group at the Arctic University of Norway, conducting research on techno-economic modeling approaches to evaluate the value of data center flexibility within sustainable electrical energy systems. The work focuses on optimizing energy consumption and task scheduling across data centers distributed in different time zones and interconnected at both national and international levels. The project aims to support grid balancing and enhance the integration of intermittent renewable energy sources, while also providing more cost-effective strategies for managing peak demand by reducing or deferring the need for expensive investments in power grid expansion.
- Software Development Engineer in the Information Technology Department at Khuzestan Steel Company (KSC). Responsible for designing and developing new software systems using Microsoft technologies, including Microsoft TFS, .NET Core/Framework, ASP.NET MVC, Web API, SignalR, and SQL Server. Involved in requirements analysis and end-to-end management of the software development lifecycle (SDLC), as well as training and supporting other developers.
M.Sc. Computer Science
The Arctic University of Norway
2020 – 2022
Focus areas:
Algorithms, System design, Software architecture fundamentals, Distributed Systems, Green computing, and Mathematical optimization.
This paper aims at discussing visions and research directions to investigate the value of data centers flexibility within sustainable electrical energy systems. While optimizing the energy consumption and task scheduling within data centers located in different time zones and connected at national and international level, it is possible to balance the local power grids, to allow a better penetration of intermittent renewable energy sources, and a more economical way to address peak demand by avoiding or postponing costly investments in network expansion. Challenges and opportunities that lie behind the exploitation of data centers flexibility within sustainable electrical energy systems will be discussed. An interdisciplinary approach to tackle these kind of problems will be proposed, and visions for a novel framework called VEDA (moVE DAta to balance the grid) will be outlined.
Data centers are considered the information backbone of the modern digital society. Everyday life is now intertwined with digital tools and platforms such as mobile (smart) phones, high-powered personal computers, cyber-physical gadgets, etc. These tools rely on data centers. In the modern digital society, the concept of sustainable development includes energy-efficient, energy waste recovery, and climate aware process of digitization. Modern and digital power system operations would rely more on the data centers. This is a conceptual paper that discusses socio-techno-economic aspects to better utilize the data centers in a sustainable way. Broad guidelines are provided on the key features to be considered to build novel decision-support system tools for the optimal integration of data centers within power systems.
As a new branch of Mobile ad hoc networks, Vehicular ad hoc networks (VANETs) have significant attention in academic and industry researches. Because of high dynamic nature of VANET, the topology will be changed frequently and quickly, and this condition is causing some difficulties in maintaining topology of these kinds of networks. Clustering is one of the controlling mechanism that able to grouping vehicles in same categories based upon some predefined metrics such as density, geographical locations, direction and velocity of vehicles. Using of clustering can make network’s global topology less dynamic and improve the scalability of it. Many of the VANET clustering algorithms are taken from MANET that has been shown that these algorithms are not suitable for VANET. Hence, in this paper we proposed a new clustering scheme that use Gauss Markov mobility (GMM) model for mobility predication that make vehicle able to prognosticate its mobility relative to its neighbors. The proposed clustering scheme’s goal is forming stable clusters by increasing the cluster head lifetime and less cluster head changes number. Simulation results show that the proposed scheme has better performance than existing clustering approach, in terms of cluster head duration, cluster member duration, cluster head changes rate and control overhead.
Azure Fundamentals
Administrator
Developer