Experts::USM

CV Information
EXPERT IN FORMAL SCIENCES SCHOOL OF MATHEMATICAL SCIENCES Main Campus UNIVERSITI SAINS MALAYSIA (USM) Starting Date in USM: 01 August 2008 saratha@usm.mysaratha@usm.my +6(04) 653 (Ext) 2428 https://experts.usm.my/cvitae/sarathahttps://experts.usm.my/cvitae/saratha https://math.usm.my/index.php/academic-profile/179-saratha-sathasivamhttps://math.usm.my/index.php/academic-profile/179-saratha-sathasivam B Sc ED, MATEMATIK / FIZIK UNIVERSITI SAINS MALAYSIA (USM) (MALAYSIA) MSc, MATEMATIK UNIVERSITI SAINS MALAYSIA (USM) (MALAYSIA) PhD, FIZIK UNIVERSITI MALAYA (UM) (MALAYSIA) BIOGRAPHY I am an Associate Professor at the School of Mathematical Sciences, Universiti Sains Malaysia. I earned my Bachelor of Education (Science) and Master of Science (Mathematics) from Universiti Sains Malaysia in 2001 and 2003, followed by a PhD from Universiti Malaya in 2007. My research focuses on artificial intelligence, numerical analysis, and computational mathematics. I am particularly interested in developing innovative mathematical models. RESEARCH INTERESTS My research focuses on artificial intelligence, neural networks logic, and computational mathematics, particularly in logic programming using Hopfield and Boltzmann networks. I explore neuro-symbolic integration, satisfiability modeling (e.g., 2-SAT, 3-SAT), fuzzy systems, and optimization via evolutionary algorithms for applications in data mining, forecasting, and mathematical modeling. Scopus ID 2563469410025634694100 Researcher ID B-1777-2018B-1777-2018 ORCID 0000-0002-2843-70820000-0002-2843-7082 Google Scholar ID a4OCYD0AAAAJa4OCYD0AAAAJ EXPERTISE FORMAL SCIENCES >> Applied Mathematics > Numerical Analysis FORMAL SCIENCES >> Applied Mathematics > Ordinary Differential and Partial Differential Equations FORMAL SCIENCES >> Applied Mathematics > Mathematics in Image Processing and Pattern Recognition FORMAL SCIENCES >> Computation Theory and Mathematics > Computational Simulation and Modelling APPLIED SCIENCE AND TECHNOLOGY >> Artificial Intelligence and Machine Learning > Neural network for Machine Learning SDG (Research Grants)

CV Information

PROFESOR MADYA TS. DR. SARATHA A/P SATHASIVAM

EXPERT IN

FORMAL SCIENCES

SCHOOL OF MATHEMATICAL SCIENCES

Main Campus

UNIVERSITI SAINS MALAYSIA (USM)

Starting Date in USM: 01 August 2008

saratha@usm.my

+6(04) 653 (Ext) 2428

https://experts.usm.my/cvitae/saratha

https://math.usm.my/index.php/academic-profile/179-saratha-sathasivam

B Sc ED, MATEMATIK / FIZIK
UNIVERSITI SAINS MALAYSIA (USM) (MALAYSIA)
MSc, MATEMATIK
UNIVERSITI SAINS MALAYSIA (USM) (MALAYSIA)
PhD, FIZIK
UNIVERSITI MALAYA (UM) (MALAYSIA)

BIOGRAPHY

I am an Associate Professor at the School of Mathematical Sciences, Universiti Sains Malaysia. I earned my Bachelor of Education (Science) and Master of Science (Mathematics) from Universiti Sains Malaysia in 2001 and 2003, followed by a PhD from Universiti Malaya in 2007. My research focuses on artificial intelligence, numerical analysis, and computational mathematics. I am particularly interested in developing innovative mathematical models.

RESEARCH INTERESTS

My research focuses on artificial intelligence, neural networks logic, and computational mathematics, particularly in logic programming using Hopfield and Boltzmann networks. I explore neuro-symbolic integration, satisfiability modeling (e.g., 2-SAT, 3-SAT), fuzzy systems, and optimization via evolutionary algorithms for applications in data mining, forecasting, and mathematical modeling.

Scopus ID

25634694100

Researcher ID

B-1777-2018

ORCID

0000-0002-2843-7082

Google Scholar ID

a4OCYD0AAAAJ

EXPERTISE

FORMAL SCIENCES >> Applied Mathematics > Numerical Analysis
FORMAL SCIENCES >> Applied Mathematics > Ordinary Differential and Partial Differential Equations
FORMAL SCIENCES >> Applied Mathematics > Mathematics in Image Processing and Pattern Recognition
FORMAL SCIENCES >> Computation Theory and Mathematics > Computational Simulation and Modelling
APPLIED SCIENCE AND TECHNOLOGY >> Artificial Intelligence and Machine Learning > Neural network for Machine Learning

SDG (Research Grants)

Expertise Indicator:

Excellent
Good
Average

Full Expert CV - Profile