About & Research

My Journey

My professional and academic journey has evolved across several interconnected disciplines.

I began with qualifications in Discrete associate degree in Technical Drawing (2003–2005) and a Bachelor of Science (BSc) in Industrial Design & Technical Drawing (2007-2009) at Vali-e-Asr college of Tehran in Iran, building a strong foundation in design and manufacturing. My academic path subsequently led me towards Master of Science (MSc) in Manufacturing Systems Engineering at Universiti Putra Malaysia (UPM, 2013-2015), where I developed a particular interest in the relationship between material behavior, properties and structural Integrity using acoustic emission (AE), sparking my interest in none-destructive testing (NDT) and failure analysis. As engineering research became increasingly data-intensive, I earned a Postgraduate Diploma in Artificial Intelligence (AI) and Machine Learning (ML) from National Institute of Technology (NIT) Warangal (2021-2022) and began exploring how data-driven approaches can support materials characterisation, damage detection and predictive engineering. I recently completed my Doctor of Philosophy (PhD) in Mechanical Engineering at University of Cape Town (UCT), focusing on advanced materials characterisation of steel alloys under blast loadings.

Today, my research increasingly connects these areas with Biomedical Engineering, exploring how advanced materials, additive manufacturing and artificial intelligence can contribute to the development of future medical devices.

Manufacturing Engineering ➡️Mechanical & Materials Engineering ➡️AI & ML ➡️Structural Integrity ➡️Biomedical Engineering

This interdisciplinary journey continues to shape the way I approach research.

Explore My Educational backgorund →

Research Focus

Advanced Materials & Smart BioMaterials

I investigate the relationship between material processing, microstructure, mechanical properties and performance.

Understanding these relationships is essential for designing advanced materials that can meet demanding engineering and biomedical requirements.

Areas of Interest

Materials characterisation
Microstructural evolution
Mechanical behaviour
Structural performance
Damage and failure mechanisms
Advanced engineering materials
Smart biomaterials
Steel Alloys

Additive Manufacturing

Advanced manufacturing technologies provide new opportunities to design materials and structures with tailored properties.

My research explores how manufacturing parameters influence the relationship between:

Processing → Microstructure → Properties → Performance

I am particularly interested in metal additive manufacturing, and its potential to produce complex structures and advanced materials.

A key area of interest is NiTi (Nitinol) shape-memory alloys and their potential applications in biomedical engineering and medical devices.

Areas of Interest

Metal additive manufacturing
Laser Powder Bed Fusion
NiTi shape-memory alloys
Process optimisation
Microstructural control
Mechanical and functional properties
Porous and complex structures

Artificial Intelligence & Machine Learning

Modern engineering research generates large and complex datasets that often require advanced analytical approaches.

I apply and explore machine learning, deep learning, and AI techniques to extract meaningful information from experimental data and support predictive engineering.

My interests include the use of AI for:

Materials characterisation
Signal analysis
Damage detection
Structural monitoring
Predictive modelling
Engineering optimisation

My goal is to create stronger connections between physical understanding and data-driven intelligence.

Biomedical Engineering & Intelligent Healthcare

My current research direction increasingly focuses on the application of advanced materials and intelligent technologies in biomedical engineering and healthcare. I am interested in smart biomaterials and advanced manufacturing approaches that can contribute to future biomedical engineering and personalised medical devices.

Alongside materials research, I am also exploring questions surrounding trustworthy artificial intelligence in healthcare.

In high-stakes applications, predictive performance alone is not enough. AI systems must also be reliable, interpretable and subject to meaningful evaluation.

My emerging interests include:

Personalised medical devices
AI-enabled healthcare
Explainable AI
Digital Twins
Hybrid AI

How I Approach Research

Experimental Research

I investigate materials and engineering systems through experimental approaches that examine their mechanical behaviour, structural performance and response to damage.

Cyclic loading
Tensile tesing and Micro tensile testing
Blast loading and Impact Engineering
Additive Manufacturing

Advanced Characterisations

I use state-of-the-art characterisation techniques to gain insights into material structure, composition and behaviour.

Scanning Electron Microscopy (SEM)
Electron Backscatter Diffraction (EBSD)
Energy-Dispersive X-ray Spectroscopy (EDS)
X-ray Diffraction (XRD)
Acoustic Emission (AE)
Hardness

Data-Driven Methods

I integrate computational approaches to analyse complex experimental data and develop predictive models, including:

Python-based data analysis
Machine learning
Deep learning
Statistical analysis
Signal processing
Predictive modelling

Research Vision

My long-term research vision is to develop stronger connections between:

Advanced Materials

Understanding and designing materials with tailored properties.

Advanced Manufacturing

Creating new possibilities for material and structural design.

Artificial Intelligence

Transforming complex data into scientific insight and predictive capability.

Biomedical Engineering

Translating engineering innovation towards technologies that can support future healthcare.

I am particularly interested in research that follows the complete pathway from:

Material Design → Advanced Manufacturing → Characterisation → Digital Twins & Aritificial Intelligence → Engineering & Healthcare Applications

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