Overview

I am an academic researcher with a multidisciplinary background in Industrial Engineering and Computer Science, specialising in data-driven optimisation, machine learning, deep learning, and decision support systems. My research is strongly application-driven, focusing on developing advanced analytical and optimisation methods that can be deployed in large-scale, real-world decision environments.

My work lies at the intersection of machine learning, deep learning, optimisation, and decision science, with a particular emphasis on problems characterised by uncertainty, complex constraints, and high computational scale. I aim to bridge rigorous methodological development with practical decision impact—ensuring that research outputs are both theoretically sound and operationally relevant.

Table of Contents

Research Focus: Machine Learning & Deep Learning

A central component of my research is the integration of machine learning and deep learning models with optimisation and decision frameworks. Rather than treating ML models as standalone predictors, my work focuses on embedding learning models within decision-making pipelines, enabling adaptive, data-informed decisions.

Key directions include:

  • Hybrid learning–optimisation systems where predictive models are coupled with constrained optimisation for planning, scheduling, and resource allocation.
  • Deep learning for complex decision environments, including representation learning, surrogate modelling, and learning-based decision policies.
  • Scalable, high-performance decision support, leveraging GPU/HPC acceleration for computationally intensive optimisation and real-time decision workflows.

Research Themes

My academic work spans several interlinked themes:

1) Data-driven Optimisation & Multi-objective Decision-making

  • Multi-objective optimisation for large-scale, real-world systems
  • Decision modelling under competing objectives (cost, risk, feasibility, performance)
  • Constraint-aware optimisation and feasibility-first strategies

2) Decision Support Systems (DSS) under Uncertainty

  • Decision support for complex environments with operational constraints
  • Scenario-based analysis and uncertainty-aware planning
  • Deployable decision pipelines: data → model → decision recommendation

3) High-Performance Computing (HPC) for ML + Optimisation

  • GPU acceleration and parallel computing to scale decision pipelines
  • Algorithm engineering for large data + optimisation workloads
  • Performance benchmarking and reproducible computational workflows

4) AI for Energy, Mining, and Industrial Systems

  • Applied AI and optimisation in energy systems and industrial operations
  • Forecasting, efficiency optimisation, and decision analytics
  • Industry-relevant, decision-centric modelling AI-Driven Energy Demand Forecasting and Load Optimisation in Healthcare Systems

Teaching Experience

I have substantial university teaching experience across Australia and internationally, covering data science, machine learning, programming, analytics, and enterprise systems.

University of Technology Sydney (UTS), Australia

  • Fundamentals of Software Programming (2026)
  • Enabling Enterprise Information Systems (2025)
  • Collaborative Business Processes (2025)
  • Innovations for Global Relationship Management (2024–2025)
  • Fundamentals of C Programming (2024–2025)
  • Capstone Project (2022–2025)
  • Computing Science Studio (2022)
  • Fundamentals of Information Systems (2024)

The University of Sydney, Australia

  • Professional Practice in IT (2026)
  • Project Management in IT (2026)
  • Data Privacy: Theory and Practice (2025)
  • Professional Practice in IT (2025)
  • Project Management in IT (2025)
  • Agile Software Development Practices (2025)

Australian Catholic University (ACU), Australia

  • Essentials of Artificial Intelligence and Machine Learning (2025)
  • Information Technology Essentials (2025)
  • Modern Database Management (2025)
  • Information Technology in Action (2025)
  • Advanced Programming Concepts (2025)

University of Tasmania, Australia

  • Programming (2026)
  • Programming Fundamentals (2026)
  • Professional Practice in IT (2026)

    Khazar University, Azerbaijan Republic

  • Machine Learning (2025)
  • Advanced Data Structure (2024)
  • Parallel Programming (2024)
  • Image Processing (2024)

Supervision & Mentoring

  • Supervised / co-supervised 100+ master’s and bachelor’s capstone projects (UTS, 2022–2024), supporting topic definition, methodology, implementation, and academic writing.
  • Example project supervision areas:
    • Context-aware lemmatisation for Azerbaijani using BiLSTM and BERT
    • Unsupervised clustering-based short-term solar forecasting
    • AI-based demand forecasting and load balancing for energy optimisation in healthcare

Publications

My publication record spans machine learning, optimisation, decision support systems, and applied analytics, with an emphasis on real-world impact.

Selected research directions reflected in my publications include:

  • AI-driven DSS integrating optimisation, learning, and uncertainty modelling for operational decision-making
  • ML + optimisation for industrial efficiency (including mining and energy systems)
  • Large-scale text mining / bibliometric intelligence for mapping research trends and collaboration networks
    My full publications are avaiable at: Google Scholar —

Books & Edited Volumes

Below is a selection of books and edited volumes that reflect my work in AI, optimisation, evolutionary computation, scheduling, and data-driven supply chain analytics.

Multi-Objective Combinatorial Optimization Problems and Solution Methods
Academic Press

Evolutionary Computation in Scheduling
Wiley

Big Data Analytics in Supply Chain Management
CRC Press

Sustainable Supply Chain of Renewable Energy Networks
Springer

Smart Cities: A System of Systems Perspective – Engineering, Analytics, and Innovations for Sustainable Urban Development
Elsevier

Grants & Awards

  • Travel Grant, Australian-French Entrepreneurship Challenge — Embassy of France (2024)
  • Travel Grant, OPTIMA-CON 24 — Optima Conference (2024)
  • Visiting Researcher Grant — Helmholtz Association, Germany (2023)
  • Australia Global Talent Visa — Department of Home Affairs (2022)
  • NAWA Scholarship — Polish National Agency (2022)
  • Nicolas Baudin Scholarship — Embassy of France (2021)
  • UTS Full PhD Scholarship (2021)
  • Research Grants — Iran National Science Foundation (2021), University of Tabriz (2020)

Invited Talks & Academic Service

Invited Talks (Selected)

  • AI-Based Optimization, Optima, Melbourne (Aug 2025)
  • Second Workshop on Genetic Programming, UTS (Mar 2025)
  • Data Science Institute Symposium, UTS (Jun 2024)
  • International Conference on Computational Methods in Science & Technology, India (Sep 2020)

Reviewing & Service

  • Reviewer for 50+ journal articles across venues including Nature, IEEE Transactions on Evolutionary Computation, Omega, Expert Systems with Applications, IEEE Transactions on Cybernetics, and others.
  • Conference reviewing and committees, including ECIS, ACIS, and multiple AI/IS conferences.