Ts. Dr. Tan Min Keng
Fakulti Kejuruteraan, UMS
Dr. Tan Min Keng is a Senior Lecturer at the Faculty of Engineering, Universiti Malaysia Sabah (UMS), where he obtained his Bachelor’s, Master’s, and PhD in Electrical and Electronic Engineering. His research interests include adaptive intelligence, multi-agent systems, and AI-driven analytics, with a focus on advancing intelligent engineering solutions.
Tan is a registered Professional Technologist with the Malaysia Board of Technologists (MBOT) and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). He holds leadership roles as Vice Chair of the IEEE Sabah Subsection and Counsellor of the IEEE Student Branch at UMS.
Beyond academia, Dr. Tan actively contributes to the international research community through conference leadership and remains committed to professional mentorship, volunteerism, and broader engagement within the engineering community.
Contact Information
Academic Department
Fakulti Kejuruteraan, UMS
Appointed Department
Fakulti Kejuruteraan, UMS
Education
Ijazah Doktor Falsafah (phd)
Universiti Malaysia Sabah
2019
Ijazah Sarjana Kejuruteraan (meng)
Universiti Malaysia Sabah
2013
Ijazah Sarjana Muda Kejuruteraan Dengan Kepujian (beng (hons))
Universiti Malaysia Sabah
2010
Research Collaborators
Research
Projects
14
Active
5
Grants
RM 771,800.00
Research Interests & Expertise
Electrical And Electronic Engineering - Control Optimization Algorithm
Electrical And Electronic Engineering - Multi-Agent Control System
Statistical Studies - Computational Artificial Neural Networks
Statistical Studies - Markov Chain Monte Carlo Methods
Publications
Total Publications by Year
Scopus Metrics
Scopus ProfileDocuments
100
H-Index
14
Citations
671
Affiliation
Universiti Malaysia Sabah
Research listing
Current Research Projects
Temporal difference learning based automatic generation control for multi-area power system
Leader
2025 - 2027
Decentralized proximal policy optimization algorithm with alternate clipping function for traffic signal control optimization
Leader
2025 - 2027
An extended temporal difference learning algorithm with adaptive meta-model for optimising automatic generation control in multi-area power system
Leader
2023 - 2026
Dynamic modelling and optimisation of multi-objective molarity-based fitness mechanism for industrial exothermic process using hybridised dyna-q-pso algorithm
Member
2022 - 2025
Classification of juvenile hybrid grouper (epinephelus fuscoguttatus × e. lanceolatus) behaviour under the culture environment: application of machine learning in fish condition monitoring
Member
2021 - 2026
Publications listing
NOTE: PUBLICATION DATA FOR THE LAST 3 YEARS WILL BE DISPLAYED
Showing 1 to 8 of 8 entries
Tan Min Keng , Lim Kit Guan , Kenneth Teo Tze Kin (2025), Adaptive Disturbance Stability Control For Uncrewed Aerial Vehicles Based On Radial Basis Function Neural Networks And Backstepping Sliding-mode Control
Yang Soo Siang , Tan Min Keng (2025), Rolling Bearing Fault Diagnosis Method Based On Gjo–vmd, Multiscale Fuzzy Entropy, And Gsabo–bp Neural Network
Tan Min Keng , Yang Soo Siang (2025), Factory Simulation Construction Method And Implementation Of Intelligent Manufacturing
Kenneth Teo Tze Kin , Lim Kit Guan , Tan Min Keng (2025), Adaptive Disturbance Stability Control For Uncrewed Aerial Vehicles Based On Radial Basis Function Neural Networks And Backstepping Sliding-mode Control
Tan Min Keng , Tham Heng Jin , Kenneth Teo Tze Kin (2024), Optimization Of Fed-batch Baker’s Yeast Fermentation Using Deep Reinforcement Learning
Lim Kit Guan , Rayner Alfred , Lim Leong Seng , Rossita Shapawi , Tan Min Keng , Kenneth Teo Tze Kin (2023), A Technical Overview Of Feeding Management In Epinephelinae Groupers Grow-out Farming
Tan Min Keng , Chua Bih Lii , Kenneth Teo Tze Kin , Renee Chin Ka Yin , Lim Kit Guan (2023), Engine Misfire Fault Diagnosis Based On Sc-anfis
Ali Farzamnia , Lim Kit Guan , Tan Min Keng , Kenneth Teo Tze Kin , Helen Chuo Sin Ee (2023), Research On Risk Detection Of Autonomous Vehicle Based On Rapidly-exploring Random Tree