About

Dr. Sagheer Khan is working as Assistant Professor in the College of Electrical & Mechanical Engineering . Dr. Sagheer Khan has a PhD in AI signal processing Digital Twin . Dr. Sagheer Khan has published 6 research articles & conference papers having a citation count of 146 , carried out 0 projects and filed 0 intellectual property.

Research Tags

Research Projects

0

Industry Projects

0

Amount Granted

0.0 M

Publications

6

Citations

146

Intellectual Property

0
Publication Types
Project Types
Publications by Year
Projects by Year

Education

PhD AI signal processing Digital Twin 2021- 2024
University of Edinburgh , United Kingdom
Master Electrical Communication and Signal Processing 2016- 2019
NUST, Islamabad , Pakistan
BSc Electrical Electronics 2012- 2016
UET Taxila , Pakistan
F.Sc Preengineering 2010- 2012
FBISE, Islamabad , Pakistan
Matric (SSC) Preengineering 2008- 2010
FBISE, Islamabad , Pakistan

Experience

Assistant Professor 2025- Present
College of Electrical & Mechanical Engineering , NUST
Assistant Professor 2024- 2024
College of Electrical & Mechanical Engineering , NUST
Graduate Teaching Assistant 2021- 2024
University of Edinburgh , Grant Institute Kings Buildings, W Mains Rd, Edinburgh EH9 3JW, UK ,

Awards

Memberships

No project records found for this faculty member
6
Research Articles
0
Conference Proceedings
0
Books
0
Book Chapters
0
Editorial Activities
Evaluation of Unobtrusive Microwave Sensors in Healthcare 4.0—Toward the Creation of Digital-Twin Model 2022
IM
Imran M. Saied (University of Edinburgh)
TH
Tharmalingam Ratnarajah (University of Edinburgh)
TU
Tughrul Arslan (University of Edinburgh)
Journal: MDPI Sensors, Volume 22, Issue 21, Article Number 8519
Impact Factor: 3.900 Citations: 11 Quartile: 2
SDG 9
Digital Twin Perspective of Fourth Industrial and Healthcare Revolution 2022
TU
Tughrul Arslan (University of Edinburgh)
TH
Tharmalingam Ratnarajah (University of Edinburgh)
Journal: IEEE Access, Volume 10, Pages 25732-25754
Impact Factor: 3.900 Citations: 84 Quartile: 2
SDG 9
Novel statistical time series data augmentation and machine learning based classification of unobtrusive respiration data for respiration Digital Twin model 2024
AA
Aaesha Alzaabi (University of Edinburgh)
TH
Tharmalingam Ratnarajah (University of Edinburgh)
Tughrul Arslan (University of Edinburgh)
Journal: Computers in Biology and Medicine, Volume 168, Article Number 107825
Impact Factor: 7.000 Citations: 21 Quartile: 1
SDG 9
Radio Frequency-Enabled Cerebral Blood Flow Monitoring and Classification Using Data Augmentation and Machine Learning Techniques 2024
US
Usman Anwar (University of Edinburgh)
TU
Tughrul Arslan (University of Edinburgh)
TO
Tom C. Russ (University of Edinburgh)
PE
Peter Lomax (University of Edinburgh)
Journal: IEEE Sensors Journal, Volume 24, Issue 19, Pages 31040-31053
Impact Factor: 4.300 Citations: 5 Quartile: 1
SDG 9
A Novel Digital Twin (DT) Model Based on WiFi CSI, Signal Processing and Machine Learning for Patient Respiration Monitoring and Decision-Support 2023
AA
Aaesha Alzaabi (University of Edinburgh)
ZA
Zafar Iqbal (University of Edinburgh)
TH
Tharmalingam Ratnarajah (University of Edinburgh)
TU
Tughrul Arslan (University of Edinburgh)
Journal: IEEE Access, Volume 11, Pages 103554-103568
Impact Factor: 3.400 Citations: 25 Quartile: 2
SDG 3 SDG 9
RF-Based Sensing and AI Decision Support for Stroke Patient Monitoring: A Digital Twin Approach 2025
US
Usman Anwar (University of Edinburgh)
AF
Aftab Khan (Allama Iqbal Open University)
TU
Tughrul Arslan (University of Edinburgh)
Journal: IEEE Access, Volume:13, Page(s):74047-74061
Impact Factor: 3.4 Citations: 0 Quartile: 2
SDG 3
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0
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