Professor Madya Dr.
 Goh Say Leng

Professor Madya Dr. Goh Say Leng

Fakulti Komputeran Dan Informatik, UMS

Professor Madya Dr. Goh Say Leng is a distinguished researcher at Fakulti Komputeran Dan Informatik, University Malaysia Sabah. Their research focuses on Operations Research, Discrete Optimization, Machine Learning, Combinatorial Optimization, Timetabling, Scheduling .

As a member of Fakulti Komputeran Dan Informatik, they contribute significantly to the academic and research community at UMS through their expertise and dedication to advancing knowledge in their field.

Professor Madya Dr. Goh Say Leng holds Doktor Falsafah from Nottingham University, Nottingham, UK , among other qualifications, and has established themselves as a respected expert in their field.

Contact Information

Academic Department

Fakulti Komputeran Dan Informatik, UMS

Appointed Department

Fakulti Komputeran Dan Informatik, UMS

Education

Doktor Falsafah

Nottingham University, Nottingham, UK

2017

Msc Computing Science

Imperial College Technology, Science And Medical

2006

Bachelor Of Information Technology

Universiti Malaysia Sabah

2004

Research Collaborators

Research

Projects

13

Active

1

Grants

RM 439,100.00


Research Interests & Expertise

Specialist Topics In Mathematics - Operations Research in Optimization

Publications

Total Publications by Year

NOTE: N/A = Data not available, 0 = Data not completed


Scopus Metrics

Scopus Profile

Documents

37

H-Index

14

Citations

702

Affiliation

Universiti Malaysia Sabah

Research listing

Current Research Projects

Hybrid mixed integer linear programming and simulated annealing optimization algorithm for nurse rostering problems

Leader

2025 - 2028

Publications listing

NOTE: PUBLICATION DATA FOR THE LAST 3 YEARS WILL BE DISPLAYED

Showing 1 to 10 of 26 entries

1.

Goh Say Leng , Goh Say Leng (2025) , Multi-population Kidney-inspired Algorithm With Migration Policy Selections For Feature Selection Problems

2.

Goh Say Leng , Goh Say Leng (2025) , Digital Drone Education In Sarawak: Enhancing Stem Learning Through Hands-on Training For School Students

3.

Goh Say Leng , Goh Say Leng (2025) , Optimizing Decentralized Exam Timetabling With A Discrete Whale Optimization Algorithm

4.

Goh Say Leng , Goh Say Leng (2025) , Optimizing Heart-kidney Interaction For Cancer Detection Through Physiological Process Simulation As A Decision Support System

5.

Goh Say Leng , Goh Say Leng (2025) , Multi-neighborhood Local Search With Room Split Balancer For Exam Timetabling: A Case Study

6.

Goh Say Leng , Goh Say Leng (2025) , Optimizing Heart-kidney Interaction For Cancer Detection Through Physiological Process Simulation As A Decision Support System

7.

Goh Say Leng , Goh Say Leng (2025) , Multi-neighborhood Local Search With Room Split Balancer For Exam Timetabling: A Case Study

8.

Goh Say Leng , Goh Say Leng (2025) , Multi-population Kidney-inspired Algorithm With Migration Policy Selections For Feature Selection Problems

9.

Goh Say Leng , Goh Say Leng (2025) , Optimizing Decentralized Exam Timetabling With A Discrete Whale Optimization Algorithm

10.

Goh Say Leng , Goh Say Leng (2025) , Digital Drone Education In Sarawak: Enhancing Stem Learning Through Hands-on Training For School Students


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