Dr Kamran Pedram

Dr Kamran Pedram BSc, MSc, PhD, CEng, MWeldI, PGCert, FHEA

Senior Lecturer in Electrical and Electronic Engineering (Physical Layer and Telecommunications Security)

Key details

Dr Kamran Pedram

Senior Lecturer in Electrical and Electronic Engineering (Physical Layer and Telecommunications Security)

Dr Pedram joined the University of Greenwich in January 2019 as a Lecturer in Electrical Engineering. Prior to joining the University of Greenwich, Dr Pedram was a project leader at TWI Ltd for two years and collaborate through a number of successful Innovate UK and European research projects. His area of expertise includes signal processing, programming, data analysis, software development, long-range ultrasonic testing, and guided waves testing.

Dr Kamran Pedram was awarded his doctoral degree from the Brunel University with a thesis on " Time-Frequency Analysis based on Split Spectrum Applied to Audio and Ultrasonic Signals;". This PhD studentship was sponsored by Brunel University London and TWI Ltd to enable development of novel Advanced Signal Processing techniques for enhancing the quality of Audio and Ultrasonic Applications.

Holder of a BSc in Electrical Engineering and Electronics, MSc degree in Data Communication Systems from Brunel University.

Dr Pedram has contributed to over 50 publications and industrial reports, he is a reviewer for several transactions. Dr Pedram is a Chartered Engineer (CEng - MWeldI), a Member of the IEEE (MIEEE) and a Member of the IET (MIET). He has obtained the PGCert awards and become a Fellow of the Higher Education Academy.

Responsibilities within the university

Module leader:

ELEC1035 Materials for Electical and Electronic Engineering

ELEE1150 Advanced Analogue and HF Electronics

ELEE1161 Machine Sensing


Runner-up winner of case study for NDT section at TWI Ltd 2018

Vice-Chancellor's Travel Prize, Brunel University London, 2014 & 2015


  • Chartered Engineer (CEng)
  • PG Cert in Higher Education Academy – PGCERT HEA
  • Fellow of Higher Education Academy - FHEA
  • Member of the IEEE
  • Member of The Welding Institute (TWI) - MWeldI

Research / Scholarly interests

  • Signal Processing Applications particularly in audio and Ultrasonic
  • Non-Destructive testing techniques particularly in Guided wave testing and Long-Range Ultrasonic Testing
  • Wearable Sensors
  • RF and Microwave system design and field trials
  • Advanced analogue circuit design and theory
  • Data Communication Systems
  • Machine Sensing
  • Ground Penetration Radar

Key funded projects

  1. Ref fund Awards £8000 at Greenwich University 2019
  2. Seeding fund £5000 at Greenwich University 2019
  3. Inspection of reinforced concrete structures by autonomous umbilical free Robot (SIRCAUR) which was partly funded by Innovate UK (funded value £394,744).
  4. UNION Project within the "Developing the Civil Nuclear Supply Chain" initiative which was partly funded by Innovate UK and TWI Ltd.

Guided wave testing has great potential for examination of hard-to-access pipes and pipelines from adjacent accessible locations, e.g. below ground sections from the part above ground. Buried lines invariably have protective coatings; these attenuate the ultrasound severely. The backfill around buried sections causes further attenuation effects. The importance of inspection and maintaining the integrity of buried in-plant piping has been widely recognised in the power industry.

The 'UNION' (Ultrasonic Nuclear Inspection) project sought to:

Improve the length of buried pipe which can be examined from each test location, Increase the sensitivity to defects attainable in such highly attenuating pipes, Demonstrate the practical implementation of such enhancements. This was achieved through a combination of theory/modelling, procedure enhancements and signal post-processing.

Recent publications


Hassanein, Ahmed , Mohamed, Sarah, Pedram, Kamran (2023), Glove-based classification of hand gestures for Arabic sign language using faster-CNN. European Open Science (EJ-ENG). In: , , , . European Open Science (EJ-ENG), European Journal of Engineering and Technology Research (EJ-ENG), 8 (5) . pp. 31-35 ISSN: 2736-576X (Print), (doi: https://doi.org/10.24018/ejeng.2023.8.5.3092).

Pedram, Kamran , Gan, Tat-Hean, Ghafourian, Mahdieh (2020), Improved defect detection of guided wave testing using split-spectrum processing. MDPI. In: , , , . MDPI, Sensors, 20: 4759 (17) . ISBN: 14248220 1424-8220 (Online) (doi: https://doi.org/10.3390/s20174759).

Pedram, Seyed Kamran , Mudge, Peter, Gan, Tat-Hean (2018), Enhancement of ultrasonic guided wave signals using a split-spectrum processing method. MDPI. In: , , , . MDPI, Applied sciences, 8: 1815 (10) ISSN: 2076-3417 (Print), (doi: https://doi.org/10.3390/app8101815).

Pedram, Seyed Kamran , Fateri, Sina, Gan, Lu, Haig, Alex , Thornicroft, Keith (2017), Split-spectrum processing technique for SNR enhancement of ultrasonic guided wave. Elsevier. In: , , , . Elsevier, Ultrasonics, 83 . pp. 48-59 ISSN: 0041-624X (Print), (doi: https://doi.org/10.1016/j.ultras.2017.08.002).