Profesor Madya Ir. Ts. Dr. Yeo Wan Sieng

Profesor Madya Ir. Ts. Dr. Yeo Wan Sieng

Fakulti Kejuruteraan, UMS

As an Associate Professor at Universiti Malaysia Sabah, I bring a wealth of experience and a deep passion for advancing engineering education and research. My academic journey, marked by a commitment to excellence, includes a Doctorate and MPhil in Chemical Engineering from Curtin University and a Bachelor's degree in Bioprocess-Chemical Engineering from Universiti Teknologi Malaysia.

Before transitioning to academia, I gained valuable industry experience in the environmental and oil & gas sectors, serving as a Technical Support Engineer, Environmental Engineer, and Trainee Chemical Engineer. These roles provided me with a strong foundation in practical engineering applications, which I integrate into my teaching and research.

My professional journey reflects dedication to upholding the highest standards of engineering practice. As a Professional Engineer and an Engineering Accreditation Panel Member, I actively contribute to the engineering community. I hold more than 10 professional memberships and have received over 10 prestigious awards, underscoring my commitment to lifelong learning and professional development.

In addition to teaching and research, I am dedicated to bridging the gap between academia and industry. Through fostering collaboration and innovation, I aim to inspire future engineers to excel in their fields while contributing to sustainable and impactful solutions for global challenges.

Contact Information

Academic Department

Fakulti Kejuruteraan, UMS

Appointed Department

Fakulti Kejuruteraan, UMS

Education

Doktor Falsafah (ph.d)

Curtin University Of Technology, Australia

2019

Sarjana Falsafah Dalam Kejuruteraan Kimia

Curtin University Of Technology, Australia

2014

Ijazah Sarjana Muda Kejuruteraan Kimia Bioproses

Universiti Teknologi Malaysia, Skudai

2007

Research Collaborators

No collaboration data available

Research

Projects

3

Active

1

Grants

RM 15,000.00


Research Interests & Expertise

Chemical Engineering - Other Chemical Plant Design, Modelling, Construction and Operation N.E.C

Publications

Total Publications by Year

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


Scopus Metrics

Scopus Profile

Documents

42

H-Index

14

Citations

571

Affiliation

Universiti Malaysia Sabah

Research listing

Current Research Projects

Predictive modelling of chromium removal and mechanical properties of membranes for wastewater treatment

Leader

2025 - 2027

Publications listing

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

Showing 11 to 20 of 25 entries

11.

Yeo Wan Sieng (2024) , A Comprehensive Overview Of The Applications Of Kernel Functions And Data-driven Models In Regression And Classification Tasks In The Context Of Software Sensors

12.

Yeo Wan Sieng (2024) , Reviewing The Dynamic Modelling Aspects Of Chemical Looping Hydrogen Production

13.

Yeo Wan Sieng (2024) , Simulation Of Multi-loop Pi Control Strategies For Optimizing Microalgae Cultivation And Co2 Capture In 3-stage Bubble Column Photobioreactors

14.

Yeo Wan Sieng (2024) , Enhancing Sustainability In Sewage Treatment: A Least Square Support Vector Regression-based Modeling Approach For Optimizing Regeneration Conditions Of Ifecu

15.

Yeo Wan Sieng (2024) , Least Square Support Vector Regression-based Modelling For The Ammonia Removal Process Using Immobilised Nanoparticle Fecu

16.

Yeo Wan Sieng (2024) , A Comprehensive Review And Recent Advances Of Vitamin C: Overview, Functions, Sources, Applications, Market Survey And Processes

17.

Yeo Wan Sieng (2023) , An Overview On Just-in-time Based Soft Sensors For Processes Industry

18.

Yeo Wan Sieng (2023) , Optimization And Prediction Of The Cotton Fabric Dyeing Process Using Taguchi Design-integrated Machine Learning Approach

19.

Yeo Wan Sieng (2023) , Effect Of Ethrel As A Flower Induction Agent On The Growth And Quality Of Fresh Golden Pineapple (md2) In Malaysia

20.

Yeo Wan Sieng (2023) , Sustainable Fashion: Design Of The Experiment Assisted Machine Learning For The Environmental-friendly Resin Finishing Of Cotton Fabric


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