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Personal profile

Academic Biography

Dr Seibu Mary Jacob is a Mathematics lecturer whose appetite for teaching has taken her on a journey of 10+ years of teaching Engineering Mathematics and Statistics. She took her bachelor degree in Mathematics (BSc) and Master degree in Mathematics (MSc), along with Post Graduate Diploma in Computer Applications (PGDCA). She was keen on research in Mathematics Education which started off with her Bachelor degree in Mathematics Education (BEd) and culminated in her doctoral degree. Her PhD research focussed on investigating Critical Thinking skills facilitated through online discussion forums in Engineering Mathematics.

She began her teaching career in Malaysia and has handled Engineering Mathematics for degree students and Statistics for post-graduate research students in the Swinburne University of Technology (Sarawak Campus), Malaysia. She is experienced in the use of SPSS for statistical data analysis and modelling and MATLAB for engineering problems. She moved into Teesside University in January 2014.

She has authored more than 20 research publications as book chapters, journal papers and conference papers. As a reviewer she has reviewed many conference papers. She is a member of IEEE, IET, IAENG and IACSIT for many years.

Summary of Research Interests

Her research interests lie in the statistical analysis and modelling of small and large data sets using SPSS.

She is equally interested in Mathematics education, Engineering education, Modelling Critical thinking or Problem solving skills, Creation of innovative assessments, Internalisation of Education and Curriculum etc.

Fingerprint Dive into the research topics where Seibu Mary Jacob is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Blood vessels Engineering & Materials Science
Learning systems Engineering & Materials Science
Support vector machines Engineering & Materials Science
Spam Mathematics
Semi-supervised Learning Mathematics
Supervised learning Engineering & Materials Science
Intrusion detection Engineering & Materials Science
Intrusion Detection Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2005 2019

A Semi-Supervised Learning Approach for Tackling Twitter Spam Drift

Imam, N., Issac, B. & Jacob, S. M., 30 Jun 2019, In : International Journal of Computational Intelligence and Applications. 18, 2, 18 p.

Research output: Contribution to journalArticleResearchpeer-review

Spam
Semi-supervised Learning
Supervised learning
Learning systems
Machine Learning
23 Downloads (Pure)

Intelligent Intrusion Detection System Through Combined and Optimized Machine Learning

Shah, S. A. R., Issac, B. & Jacob, S. M., 28 Jun 2018, In : International Journal of Computational Intelligence and Applications. 17, 2, 1850007.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Intrusion detection
Intrusion Detection
Support vector machines
Learning systems
Support Vector Machine
9 Downloads (Pure)

Multi-Population Differential Evolution for Retinal Blood Vessel Segmentation

Mistry, K., Issac, B., Jacob, S., Jasekar, J. & Zhang, L., 20 Dec 2018, Proceedings of 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) : ICARCV 2018. IEEE, p. 424-429 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearch

Open Access
File
Blood vessels
Support vector machines
Neural networks
Classifiers
Pixels

Multi-Population Differential Evolution for Retinal Blood Vessel Segmentation

Mistry, K., Issac, B., Jacob, S., Jasekar, J. & Zhang, L., 20 Dec 2018.

Research output: Contribution to conferencePaperResearchpeer-review

Open Access
File
Blood vessels
Support vector machines
Neural networks
Classifiers
Pixels