Abeer Fiaz Hussain

Academic

Career

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Abeer Fiaz Hussain
Cell: 923323434106 |  Email: abeerfiaz.03@gmail.com
LinkedIn: https://www.linkedin.com/in/abeer-fiaz-hussain-b5aa43297/
Address: HOUSE#7 STREET#29, BLOCK-L, NAVAL ANCHORAGE ISLAMABAD , Islamabad , Pakistan
PROFESSIONAL PROFILE
Electrical Engineering Graduate | Biomedical Modeling, Machine Learning & Embedded Systems
Passionate about transforming research insights into innovative, real-world solutions.
With a strong foundation in biomedical modeling, machine learning, and embedded systems, I am a motivated and versatile
engineering graduate passionate about transforming research insights into practical, cutting-edge solutions. I thrive on developing
innovative projects that deliver tangible results and am eager to contribute technical expertise, drive meaningful impact, and grow
professionally in dynamic, multidisciplinary environments.
EDUCATION
Bachelors of Electrical Engineering
National University of Science and Technology , Islamabad , 3.2 (2026)
INTERNSHIP EXPERIENCE
MiNE Lab
15-Jun-2025 - 15-Aug-2025
During my research-based internship, I worked on a non-invasive melanoma detection project using bioelectrical impedance analysis.
The work involved developing a multilayer electrical model of human skin (stratum corneum, viable skin, and subcutaneous adipose
tissue) using parameters extracted from peer-reviewed biomedical literature. COMSOL Multiphysics was used to simulate impedance
responses of healthy and melanoma-affected tissue under surface electrode excitation. This experience developed my skills in
biomedical modeling, impedance-based tissue analysis, simulation-driven research, and scientific documentation. I gained practical
exposure to literature-based parameterization, result interpretation, and technical reporting within a research environment.
FINAL YEAR PROJECT
Skin Impedance Based Melanoma Detection
This project investigates a non-invasive method for melanoma detection using the electrical impedance properties of human skin.
Melanoma causes changes in the structural and electrical characteristics of skin tissue, which can be reflected in measurable
impedance variations. The skin is modeled as a multilayer structure consisting of the stratum corneum, viable skin (epidermis and
dermis), adipose tissue and then muscle, with layer properties taken from published literature. Simulation-based analysis is used to
compare impedance responses of healthy and melanoma-affected skin under surface electrode excitation. The study aims to
evaluate the feasibility of skin impedance measurements as a low-cost screening approach for early melanoma detection.
TECHNICAL EXPERTISE
Research Intern – Skin-Impedance Melanoma Detection
Developed a multilayer human skin model and performed simulations in COMSOL Multiphysics to analyze impedance differences
between healthy and melanoma-affected tissue. Applied bioelectrical impedance analysis, electrode-based measurements, data
interpretation, and technical reporting.
Face-Detection Attendance System (Machine Learning)
Implemented an automated attendance system using face detection, including masked faces. Applied machine learning algorithms, data preprocessing, model training, and real-time application integration.

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