Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award
Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.
Publication ProfilesΒ
Googlescholar
Education and Experience
- Visiting Research FellowΒ – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present)Β
- Senior LecturerΒ (Computer Science) – South Eastern University of Sri Lanka (2020 – Present)Β
- Sessional AcademicΒ – School of Electrical Engineering & Computer Science, QUT (2016 – 2019)Β
- LecturerΒ (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015)Β
- Assistant LecturerΒ – South Eastern University of Sri Lanka (2010 – 2012)Β
- DemonstratorΒ in Computer Science – South Eastern University of Sri Lanka (2009 – 2010)Β
Suitability For The Award
Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.
Professional Development
Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement.Β
Research Focus
Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research.Β
Awards and Honors
- Senate Honours Award for High Impact PublicationsΒ – SEUSL (2022 & 2023)Β
- Queensland University of Technology Postgraduate Award (QUTPRA)Β (2015)Β
- Faculty Write Up (FWU) ScholarshipΒ – QUT, Australia (2019)Β
- Effective Communication in Teaching and LearningΒ – QUT, Australia (2019)Β
- Foundation of Teaching and LearningΒ – QUT (2018)Β
Publication Top NotesΒ
-
Locating tables in scanned documents for reconstructing and republishingΒ | Cited by: 46 | Year: 2014Β
-
Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14)Β | Cited by: 37 | Year: 2014Β
-
AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based AssignmentsΒ | Cited by: 34 | Year: 2014Β
-
Plagiarism detection tools and techniques: A comprehensive surveyΒ | Cited by: 23 | Year: 2021Β
-
Fingerprint Systems: Sensors, Image Acquisition, Interoperability and ChallengesΒ | Cited by: 11 | Year: 2023Β
-
Contactless finger recognition using invariants from higher order spectra of ridge orientation profilesΒ | Cited by: 10 | Year: 2018Β
-
Accelerating text-based plagiarism detection using GPUsΒ | Cited by: 10 | Year: 2015Β
-
Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariantsΒ | Cited by: 9 | Year: 2018Β