Abdul Rahman
Abdul Rahman is an AI-driven materials engineer, remote consultant to companies in the United States, and entrepreneur. He combines physical metallurgy with machine learning and CALPHAD modeling, works as a research engineer and senior instructor at the Pakistan Council of Scientific and Industrial Research (PCSIR), and founded Connected 2 Future (C2F), EduCon and Jobs4DAE.
Materials engineering consulting for US companies
Abdul Rahman works remotely with engineering, manufacturing and R&D teams in the United States and worldwide.
Metallurgical failure analysis consulting
Root-cause analysis of cracked, corroded or worn metal parts: fractography, metallography and chemistry, with a clear report on what failed, why, and what to change.
SEM/EDS and XRD data interpretation
Send your SEM images, EDS spectra or XRD patterns and get phase identification, Rietveld refinement and a written interpretation your team can act on.
Materials informatics and machine learning for R&D
Machine learning models, Bayesian optimization and CALPHAD modeling that predict properties from composition and processing, so you run fewer experiments.
Battery recycling and critical minerals
Direct recycling and relithiation of NMC lithium-ion cathodes, and characterization-led beneficiation of low-grade ores.
Corrosion and protective coatings
Corrosion kinetics, electrochemical testing data and machine learning-guided design of self-healing protective coatings.
Research in metallurgy and materials informatics
- Physical and extractive metallurgy: phase transformations, microstructural evolution and sustainable mineral processing.
- Computational materials science: materials informatics, machine learning and CALPHAD-based modeling for accelerated discovery.
- Surfaces, interfaces and degradation: nanotribology, multifunctional coatings, corrosion, wear and oxidation.
- Sustainable materials: direct recycling and regeneration of NMC lithium-ion battery cathodes.
Toolkit: SEM/EDS, XRD, Python and CALPHAD
Python (scikit-learn, pandas), PyTorch, PyCalphad, Pymatgen, MatGL, Bayesian optimization, agentic AI workflows; SEM/EDX, XRD with Rietveld refinement, XRF, optical metallography, hardness and tensile testing, CSWIP 3.1; MATLAB, OriginPro, ImageJ, Thermo-Calc, COMSOL Multiphysics, LAMMPS and Quantum ESPRESSO.
Experience and education
- Research Engineer & Senior Instructor, Pakistan Council of Scientific and Industrial Research (PCSIR). Upgraded low-grade iron ore from 36% to 65% Fe, ran SEM/EDS, XRD and XRF on 50+ projects, managed ISO 17025 quality systems and built CBT&A curricula with GIZ.
- Project Engineer, Machine Zone Ltd. Process planning and sintering optimization for a powder metallurgy facility.
- MSc Metallurgical and Materials Engineering, UET Lahore. Thesis on direct recycling of nickel-rich NMC cathodes.
- BSc Metallurgical and Materials Engineering, UET Lahore. Thesis on 316L stainless steel weld cladding.
Publications and conference work
- Machine learning-driven design of self-healing epoxy coatings using MgO-loaded ZIF-8 nanocontainers for corrosion protection. Submitted to a Springer Nature journal (2026).
- Hybrid Generative and Multimodal Machine Learning for Quantum-Enhanced Design of Metal-Organic Frameworks. Accepted abstract, AIMS-2025.
- Agentic AI-Driven Digital Twin Framework for Accelerated Discovery of Rare-Earth Materials. Poster, MSE, Deutsche Gesellschaft für Materialkunde.
Ventures founded by Abdul Rahman
- Connected 2 Future (C2F): AI automation, web development and digital marketing. Founder and CEO since 2020.
- EduCon: education and career guidance for students.
- Jobs4DAE: jobs, higher-education guides and AI tools for DAE students in Pakistan.
Questions people ask
Who is Abdul Rahman?
Abdul Rahman is an AI-driven materials engineer and entrepreneur. He is a research engineer and senior instructor at the Pakistan Council of Scientific and Industrial Research (PCSIR), holds BSc and MSc degrees in metallurgical and materials engineering from UET Lahore, and founded Connected 2 Future (C2F), EduCon and Jobs4DAE.
What does Abdul Rahman specialize in?
He specializes in physical and extractive metallurgy, materials informatics (machine learning and CALPHAD modeling), materials characterization with SEM/EDS, XRD and XRF, corrosion and protective coatings, and direct recycling of lithium-ion battery cathodes.
Which companies has Abdul Rahman founded?
Abdul Rahman founded Connected 2 Future (C2F), a digital agency for AI automation, web development and digital marketing, which he has led as CEO since 2020. He also founded EduCon, an education venture, and Jobs4DAE, a career portal for DAE students in Pakistan.
Does Abdul Rahman work with companies in the United States?
Yes. He consults remotely for companies in the United States and worldwide. Engagements start with a 30-minute video call booked online, followed by a written proposal; data such as SEM images, EDS spectra and XRD patterns are shared securely online.
What is materials informatics?
Materials informatics applies data science and machine learning to materials science. It uses data from experiments, simulations and databases to predict how a material's composition and processing affect its properties, which reduces the number of experiments needed to develop new alloys, coatings and battery materials.
What does a metallurgical failure analysis include?
A metallurgical failure analysis typically includes visual and fractographic examination, SEM/EDS analysis of fracture surfaces and deposits, metallography, hardness or mechanical testing and chemical analysis, ending in a root-cause finding and recommendations to prevent recurrence.
Can I hire Abdul Rahman as a consultant?
Yes. He advises on metallurgical failure analysis, SEM/EDS and XRD characterization, materials informatics workflows and mineral processing. You can book a 30-minute discovery call on the contact page.
What has Abdul Rahman published?
His work includes machine learning-driven design of self-healing epoxy coatings with MgO-loaded ZIF-8 nanocontainers (submitted to a Springer Nature journal), hybrid generative machine learning for metal-organic frameworks (AIMS-2025), and an agentic AI digital twin for rare-earth materials discovery (MSE, DGM).
Contact: [email protected] | LinkedIn | GitHub