A
PROFILE
Laman Web Staf UPM
DR. MUHAMMAD ADIB BIN MOHD NASIR
PENSYARAH KANAN
FAKULTI KEJURUTERAAN
muhammadadib@upm.edu.my
Laman Web UPM
PROFILE
muhammadadib
BM
EN

PROFESIONAL

NAMA :
(Dr.) MUHAMMAD ADIB BIN MOHD NASIR
JAWATAN :
PENSYARAH KANAN
PTJ :
FAKULTI KEJURUTERAAN

BIDANG PENYELIAAN
AGRICULTURAL MECHANISATION AND AUTOMATION / ENVIRONMENTAL ENGINEERING / SAFETY, HEALTH AND EMERGENCY MANAGEMENT / SOIL AND WATER ENGINEERING / WATER RESOURCES ENGINEERING
PENDIDIKAN
DOKTOR FALSAFAH DALAM KEJURUTERAAN AWAM
UNIVERSITI TEKNOLOGI MALAYSIA, SKUDAI, JOHOR
Graduated : 2023
MASTER SAINS
UNIVERSITI PUTRA MALAYSIA, SERDANG, SELANGOR
Graduated : 2019
BACELOR KEJURUTERAAN (PERTANIAN DAN BIOSISTEM)
UNIVERSITI PUTRA MALAYSIA, SERDANG, SELANGOR
Graduated : 2015
KEJURUTERAAN MEKANIKAL (PERTANIAN)
POLITEKNIK KOTA BHARU, KELANTAN
Graduated : 2010
PENERBITAN JOURNAL
1. Long-term rainfall projection based on CMIP6 scenarios for Kurau River Basin of rice-growing irrigation scheme, Malaysia
    Journal type: Citation-Indexed Journal - ESCI
2. Metalearning Approach Coupled with CMIP6 Multi-GCM for Future Monthly Streamflow Forecasting
    Journal type: Citation-Indexed Journal - Science Citation Index (JCR)
3. Projected irrigation demand for large-scale rice granary under future climate scenarios based on CMIP6 multi-GCM ensemble: a case study of Kerian Irrigation Scheme, Malaysia
    Journal type: Citation-Indexed Journal - Science Citation Index (JCR)
4. Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
    Journal type: Citation-Indexed Journal - Science Citation Index (JCR)
5. Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia
    Journal type: Citation-Indexed Journal - Science Citation Index (JCR)
6. Assessing Machine-Learning Performances in Predicting Future Irrigation Demand for Large-Scale Rice Granaries Based on Global Climate Models
    Journal type: Citation-Indexed Journal - Science Citation Index (JCR)
PENERBITAN
2025
Assessing Machine-Learning Performances in Predicting Future Irrigation Demand for Large-Scale Rice Granaries Based on Global Climate Models
2025
Assessing Machine-Learning Performances in Predicting Future Irrigation Demand for Large-Scale Rice Granaries Based on Global Climate Models
2025
Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia
2024
Projected irrigation demand for large-scale rice granary under future climate scenarios based on CMIP6 multi-GCM ensemble: a case study of Kerian Irrigation Scheme, Malaysia
2024
Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
2022
Metalearning Approach Coupled with CMIP6 Multi-GCM for Future Monthly Streamflow Forecasting