Background

Background and Professional Journey

My background is not a sequence of disconnected degrees and job titles. It is a progression—from modelling physical systems, to understanding markets and organizations, to using data and digital technologies, and now to studying how AI should be governed.

A Connected Story

Different Fields, One Continuing Question

My path has never followed a single disciplinary lane. Engineering taught me to model systems and respect constraints. Finance and business shifted my attention toward uncertainty, incentives, and decision-making. Professional roles exposed me to how organizations actually use evidence under commercial, operational, and institutional pressures. Data science and Information Systems then gave me a language for connecting these experiences.

Across these stages, the question has become more precise: how can organizations design, adopt, and govern technologies in ways that are technically sound, managerially useful, and socially responsible?

What connects my work is not one industry or method, but an interest in how complex systems move from analysis to decision, from design to use, and from formal responsibility to practical control.

Academic and Professional Journey

How Each Stage Shaped the Next

The timeline brings education and professional practice together, showing how technical, managerial, and computational experiences gradually converged in my current research.

2010–2017

Foundation I

Systems, Modelling, and the Discipline of Engineering

Mechanical engineering introduced me to systems thinking: understanding components, interactions, constraints, and failure points. As a Computational Fluid Dynamics Engineer, I learned to move between mathematical models and real technical problems, while recognizing that every model is a selective representation of reality.

Academic BSc in Mechanical Engineering

Qom University of Technology · 2010–2014

Thesis: computational modelling and simulation of a shell-and-tube heat exchanger.
Professional Computational Fluid Dynamics Engineer

Iran Polymer and Petrochemical Institute · 2014–2017

Applied simulation and quantitative reasoning to engineering and research-oriented work.
Systems ThinkingSimulationMATLABQuantitative Analysis
2015–2019

Foundation II

From Technical Models to Markets and Managerial Decisions

An MBA in Finance shifted my attention from physical systems to organizational decisions under uncertainty. Work in consulting and digital commerce made this transition practical: analysis had to support strategy, market understanding, forecasting, supplier choices, and commercial action.

Academic MBA in Finance

Kharazmi University · 2015–2017

Thesis on hybrid models for assessing default risk among companies listed on the Tehran Stock Exchange.
Professional Business Analyst

The European House – Ambrosetti · 2017–2018

Category Sales Developer

Snapp Group / Bamilo · 2018–2019

Business AnalysisMarket ResearchForecastingCommercial Strategy
2021–2025

Convergence

Data at Scale, Digital Platforms, and Distributed Systems

Working with large-scale retail data showed me how analytics becomes meaningful only when it fits operational routines and managerial decisions. My MSc in Data Science and Management expanded this practical experience into machine learning, statistics, data visualization, cybersecurity, and responsible AI. Later work in blockchain development strengthened my interest in distributed architectures, traceability, and digital trust.

Professional Sales Data Analyst

Golrang Industrial Group / Ofogh Koorosh Chain · 2021–2022

Blockchain Developer

LaborX · 2024–2025

Academic MSc in Data Science and Management

Luiss Guido Carli University · 2022–2024

Thesis on privacy-preserving collaborative AI in healthcare using federated learning and blockchain.
Machine LearningData VisualizationPythonBlockchainTrustworthy AI
2025–Present

Current Direction

Information Systems, AI Governance, and Organizational Capability

My current research brings the earlier stages together. I study how AI and digital systems are governed inside organizations, how formal responsibilities become operational controls, and how technical architecture interacts with organizational capability, risk, and accountability.

Academic PhD in Management

Luiss Guido Carli University · 2025–Ongoing

Research in Information Systems under the supervision of Professor Paolo Spagnoletti.
Research Focus Governance of Emerging Technologies

AI governance, governance by design, cybersecurity management, organizational AI adoption, and digital transformation.

Broader interests include cognitive science and computational social science.
Information SystemsAI GovernanceDesign Science ResearchCybersecurity GovernanceCausal Methods

What This Background Enables

Four Complementary Ways of Seeing a Problem

The value of an interdisciplinary background lies in combining perspectives without confusing them. Each lens contributes something different to the way I frame and investigate a question.

01

Systems and Computational Reasoning

Modelling complex relationships, recognizing dependencies and constraints, and testing how changes in one component affect the wider system.

02

Business and Organizational Understanding

Connecting analysis with incentives, decision rights, strategy, implementation realities, and the practical conditions under which organizations act.

03

Data and AI Methods

Using quantitative analysis, machine learning, natural language processing, network analysis, causal reasoning, and visualization to investigate complex questions.

04

Governance and Interdisciplinary Research

Studying how technical design, organizational arrangements, human judgment, regulation, and accountability shape one another.

Methods and Skills

A Research and Analytical Toolkit

Methods are selected according to the research problem rather than treated as an identity of their own.

Research Design

Design Science Research · Quantitative Research · Causal Inference · Econometrics · Computational Modelling · Scientific Writing

Data and AI

Machine Learning · Natural Language Processing · Network Analysis · Simulation · Statistical Analysis · Data Visualization

Programming and Tools

Python · R · STATA · SQL · Solidity · MATLAB · Power BI · Tableau · Excel

Complete Record

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