Dr Amr Rashad Ahmed Abdullatif
Assistant Professor
| Faculty/Dept/School |
Department of Computer Science (Faculty of Engineering and Informatics) |
|---|---|
| a.r.a.abdullatif@bradford.ac.uk |
Biography
Dr Amr Abdullatif is a renowned expert in the field of Computing and Artificial Intelligence. He is known for his work in the safety and reliability of ML and deep learning methods when coupled with safety-critical systems. He currently serves as an Assistant Professor of Computer Science at the University of Bradford, where he conducts research on systems for automated driving, healthcare, and supply chain management.
Dr Abdullatif has a wealth of experience in applying his research to real-world scenarios, having worked with industrial partners such as GE Oil & Gas, Ansaldo, Valeo, and Renault. Prior to joining the University of Bradford, he was a research fellow at Scuola Superiore Sant'Anna and General Electric, where he focused on applying ML algorithms for predictive maintenance and supply chain management.
In addition to his research, Dr Abdullatif has also contributed to writing research grants for UKRI-funded projects and has been a co-investigator on many successful UKRI and industrial-funded projects at the University of Bradford. He is also a core team member of the University of Bradford's AI and automotive research centre and Co-leader of SAFI (https://www.bradford.ac.uk/automotive-research-centre/safi/).
Dr Abdullatif received his PhD in computer science and system engineering from the University of Genoa, Italy, in 2018, where he conducted research on Unsupervised tracking of time-evolving data streams and an application to short-term urban traffic flow forecasting. His dedication to the field and contributions to the research community have established him as a respected leader in the field of Computing and Artificial Intelligence.
Research
Dr. Amr Abdullatif is a Lecturer in Computer Science. He has extensive industry experience (e.g. General Electric, Bombardier and Ansaldo Energy). His research interests focus on machine learning, predictive diagnostics and online learning from data streams.Publications
| Peer Reviewed Journal | |
|---|---|
| Title | Clustering of nonstationary data streams: A survey of fuzzy partitional methods (2018) |
| Authors | Abdullatif A.;Masulli F.;Rovetta S. |
| Journal | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery |
| DOI | 10.1002/widm.1258 |
| Title | Tracking Time Evolving Data Streams for Short-Term Traffic Forecasting (2017) |
| Authors | Abdullatif A.;Masulli F.;Rovetta S. |
| Journal | Data Science And Engineering |
| DOI | 10.1007/s41019-017-0048-y |
| Book Chapters | |
|---|---|
| Title | Graded possibilistic clustering of non-stationary data streams (2017) |
| Authors | Abdullatif A.;Masulli F.;Rovetta S.;Cabri A. |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Publisher | Springer, Cham |
| DOI | 10.1007/978-3-319-52962-2_12 |
| Other Publications | |
|---|---|
| Other type | Article |
| Title | Hubs and communities identification in dynamical financial networks (2015) |
| Authors | Mahmoud H.;Masulli F.;Resta Marina M.;Rovetta S.;Abdulatif A. |
| Journal | Smart Innovation, Systems and Technologies |
| DOI | 10.1007/978-3-319-18164-6_10 |
| Title | Author(s) |
|---|---|
| Comparison of methods for community detection in networks (2016) | Mahmoud H.;Masulli F.;Rovetta S.;Abdullatif A. |
| Layered ensemble model for short-term traffic flow forecasting with outlier detection (2016) | Abdullatif A.;Rovetta S.;Masulli F. |