Education
Dr. Syed Aziz Shah completed his PhD in Electrical and Electronics Engineering at Xidian University, China, from 2015 to 2018. His doctoral research focused on advanced RF sensing technologies, and he gained recognition for his significant contributions to the field. Dr. Shah’s academic journey also includes extensive research and publications in esteemed journals such as IEEE, IET, and MDPI, which earned him several awards, including the Research Excellence Award from Xidian University for achieving the highest number of publications during his PhD studies. His strong educational foundation has been instrumental in his current work at the Research Centre for Intelligent Healthcare at Coventry University, UK, where he leads cutting-edge research in AI-based RF sensing technologies.
Experience
Dr. Syed Aziz Shah currently holds the position of Reader (Associate Professor) in AI-based RF Sensing Technologies at the Research Centre for Intelligent Healthcare, Coventry University, UK, where he has been serving since 2020. In addition, he is the Post Graduate Research Lead at the same institution, overseeing research initiatives and guiding postgraduate research projects. Dr. Shah leads the Healthcare Sensing Technology Group, managing a team of researchers including one Assistant Professor, two Research Fellows, and eight PhD students. He has made significant contributions to the field of intelligent healthcare through his research on AI-based RF sensing technologies, particularly in applications such as remote patient monitoring and fall detection. His leadership extends beyond research, as he also serves as the Outreach Programme Manager at the Institute of Health and Wellbeing at Coventry University, where he works to enhance the institute’s visibility through strategic initiatives. Throughout his career, Dr. Shah has been invited to deliver keynote talks and courses at prestigious institutions such as Imperial College London, University of Bristol, University of Manchester, and University of Leeds, further cementing his position as an expert in the field. He has also supervised several PhD students and served as an external examiner for doctoral theses at various international institutions.
Research Interests
Dr. Syed Aziz Shah’s research interests lie at the intersection of AI-based technologies and RF (Radio Frequency) sensing, with a particular focus on their applications in healthcare. His work explores innovative solutions for remote patient monitoring, human activity recognition, and disease detection through advanced RF sensing techniques. Dr. Shah has contributed extensively to the development of intelligent healthcare systems, using machine learning algorithms to enhance the accuracy and efficiency of RF sensing technologies. His research also delves into the use of intelligent reflecting surfaces in communication systems, aiming to improve the quality and reliability of wireless communications for healthcare applications. Additionally, he is involved in developing AI-driven methodologies to support medical diagnostics, such as contactless respiratory waveform extraction for COVID-19 patients. Dr. Shah is particularly interested in the integration of RF sensing and AI to create cutting-edge solutions for healthcare monitoring and intervention, advancing the field of intelligent healthcare technology.
Skills
Dr. Syed Aziz Shah possesses a robust set of skills in advanced technologies, particularly in the realms of AI-based RF Sensing, Machine Learning, and Signal Processing. His expertise spans RF System Design and the application of Artificial Intelligence in healthcare sensing technologies. He is adept at developing and managing RF sensing solutions for real-time healthcare monitoring, including fall detection and respiratory waveform extraction for remote patient care. Dr. Shah has substantial skills in project management, exemplified through leading large research projects and managing research teams at Coventry University’s Research Centre for Intelligent Healthcare, where he oversees a team comprising Assistant Professors, Research Fellows, and Ph.D. students. Additionally, Dr. Shah is experienced in outreach and pastoral care, having managed outreach initiatives and welfare programs to enhance institutional visibility and student support. His skills in supervision and mentorship are demonstrated by his involvement in Ph.D. supervision and training programs, alongside his role as an external examiner for doctoral research. His technical and leadership skills are further underscored by his active participation as a keynote speaker, course leader, and organizer of academic conferences and workshops, establishing him as a leader in the field of intelligent healthcare and RF sensing technology.
Dr. Syed Aziz Shah has received several prestigious awards and honors throughout his academic and research career. Notably, he was honored with the UK’s Most Prestigious ESPRC New Investigator Award, a recognition granted to individuals holding academic lectureship positions, which includes a substantial grant of GBP 410,000. This award highlights his pioneering work in RF sensing for remote patient monitoring. Additionally, Dr. Shah was endorsed as an Exceptional Talent: ‘Emerging Leader’ by the Royal Academy of Engineering, UK, in acknowledgment of his groundbreaking contributions to the field of RF sensing technology. This prestigious recognition is given to early-career innovators and scientists who demonstrate exceptional potential and leadership in their field. Furthermore, he received the Research Excellence Award from Xidian University, China, for achieving the highest number of publications in esteemed journals such as IEEE, IET, and MDPI during his Ph.D. studies. As part of this honor, he was also awarded a USD 5,000 reward for his academic achievements. These awards reflect Dr. Shah’s significant impact on the research community, particularly in the area of intelligent healthcare technology and RF sensing.
Title: RF sensing technologies for assisted daily living in healthcare: A comprehensive review
- Authors: SA Shah, F Fioranelli
- Journal: IEEE Aerospace and Electronic Systems Magazine
- Volume: 34
- Issue: 11
- Pages: 26-44
- Cited by: 170
- Year: 2019
Title: An intelligent non-invasive real-time human activity recognition system for next-generation healthcare
- Authors: W Taylor, SA Shah, K Dashtipour, A Zahid, QH Abbasi, MA Imran
- Journal: Sensors
- Volume: 20
- Issue: 9
- Article Number: 2653
- Cited by: 162
- Year: 2020
Title: A novel hybrid secure image encryption based on julia set of fractals and 3D Lorenz chaotic map
- Authors: F Masood, J Ahmad, SA Shah, SS Jamal, I Hussain
- Journal: Entropy
- Volume: 22
- Issue: 3
- Article Number: 274
- Cited by: 130
- Year: 2020
Title: A Review of the State of the Art in Non-Contact Sensing for COVID-19
- Authors: W Taylor, QH Abbasi, K Dashtipour, S Ansari, SA Shah, A Khalid, et al.
- Journal: Sensors
- Volume: 20
- Issue: 19
- Article Number: 5665
- Cited by: 108
- Year: 2020
Title: Radar sensing for healthcare: The applications of radar in monitoring vital signs and recognizing human activity patterns
- Authors: DF Fioranelli, DSA Shah, H Li, A Shrestha, DS Yang, DJL Kernec
- Journal: Electronics Letters
- Volume: 55
- Issue: 19
- Pages: 1022-1024
- Cited by: 108*
- Year: 2019
Title: Radar for health care: Recognizing human activities and monitoring vital signs
- Authors: F Fioranelli, J Le Kernec, SA Shah
- Journal: IEEE Potentials
- Volume: 38
- Issue: 4
- Pages: 16-23
- Cited by: 94
- Year: 2019
Title: Machine learning driven approach towards the quality assessment of fresh fruits using non-invasive sensing
- Authors: A Ren, A Zahid, A Zoha, SA Shah, MA Imran, A Alomainy, QH Abbasi
- Journal: IEEE Sensors Journal
- Volume: 20
- Issue: 4
- Pages: 2075-2083
- Cited by: 89
- Year: 2019
Title: Human activity recognition: Preliminary results for dataset portability using FMCW radar
- Authors: SA Shah, F Fioranelli
- Conference: 2019 International Radar Conference (RADAR)
- Pages: 1-4
- Cited by: 73
- Year: 2019
Title: Freezing of gait detection considering leaky wave cable
- Authors: X Yang, SA Shah, A Ren, N Zhao, Z Zhang, D Fan, J Zhao, W Wang, et al.
- Journal: IEEE Transactions on Antennas and Propagation
- Volume: 67
- Issue: 1
- Pages: 554-561
- Cited by: 64
- Year: 2018
Conclusion
Dr. Syed Aziz Shah’s exceptional contributions to AI, RF sensing, and intelligent healthcare systems make him a fitting nominee for the Top Researcher Award. His leadership in research, innovative projects, and outstanding academic achievements reflect his dedication to advancing technology for the betterment of society. His accolades, teaching roles, and continued research excellence position him as a trailblazer in his field, deserving of this prestigious recognition.