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Faizal Immaddudin Wira Rohmat, S.T., M.T., Ph.D
Research Interests

Machine learning, artificial intelligence, and high-performance computing for water resources systems

Keywords

Machine learning

Email : faizalrohmat@itb.ac.id

1. Ph.D. Water Resources Planning and Management, Colorado State University (2014 – 2019) Dissertation: Machine Learning Methods to Facilitate Optimal Water Allocation and Management in Irrigated River Basins to Comply with Water Law, using MODSIM Surface Water Model in Conjunction with MODFLOW Groundwater Model
2. Master’s degree in Civil Engineering (Water resources focus), Institut Teknologi Bandung (2011-2012) Thesis: Irrigation O&M Fair Budgeting Strategy using Multi-Criteria Decision Analysis (MCDA)
3. Bachelor’s degree in Civil Engineering (Water resources focus), Institut Teknologi Bandung (2007-2011) Thesis: GIS-based Analysis of Erosion, Sedimentation, and Service Life of Jatigede Dam

Achievement/Award
  • Sumono Prize,
  • Bintang Jasa Utama,
  • Penghargaan Berprestasi Tinggi dalam Kursus Lemhannas Angkatan ke VII,
  • The World Bank Award for Excellence,
  • Satya Lencana Karya Satya, 40 Tahun ITB
Experience

Direktur Jenderal Pendidikan Dasar dan Menengah (Dikdasmen) Departemen Pendidikan Nasional (Depdiknas) (1998-2005)

Paten
Organization

Himpunan Ahli Konstruksi Indonesia

· Rohmat, F.I.W., Stamataki, I., Sa’adi, Z. and Fitriani, D., 2022. Flood analysis using HEC-RAS: The case study of Majalaya, Indonesia under the CMIP6 projection (No. EGU22-3090). Copernicus Meetings.
· Sa’adi, Z., Rohmat, F.I., Stamataki, I., Shahid, S., Iqbal, Z., Yaseen, Z.M., Yusop, Z. and Alias, N.E., 2022. Spatiotemporal Rainfall Projection in Majalaya basin, West Java, Indonesia under CMIP6 Scenarios. Preprints.
· Kardhana, H., Valerian, J.R., Rohmat, F.I.W. and Kusuma, M.S.B., 2022. Improving Jakarta’s Katulampa Barrage Extreme Water Level Prediction Using Satellite-Based Long Short-Term Memory (LSTM) Neural Networks. Water, 14(9), p.1469.
· Valerian, J.R., Rohmat, F., Kardhana, H., Kusuma, M.S.B. and Yatsrib, M., 2021, September. Sadewa satellite remote sensing data to Manggarai 1-hour water level machine learning model. In 2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) (pp. 1-6). IEEE.
· Fields, C.M., Labadie, J.W., Rohmat, F.I. and Johnson, L.E., 2021. Geospatial decision support system for ameliorating adverse impacts of irrigated agriculture on aquatic ecosystems. Agricultural Water Management, 252, p.106877.
· Pratama, M.I., Rohmat, F.I.W., Farid, M., Adityawan, M.B., Kuntoro, A.A. and Moe, I.R., 2021, April. Flood hydrograph simulation to estimate peak discharge in Ciliwung river basin. In IOP Conference Series: Earth and Environmental Science (Vol. 708, No. 1, p. 012028). IOP Publishing.
· Farid, M., Pratama, M.I., Kuntoro, A.A., Adityawan, M.B., Rohmat, F.I.W. and Moe, I.R., 2021. Pengaruh Perubahan Tutupan Lahan terhadap Debit Banjir di Daerah Aliran Sungai Ciliwung Hulu.
· Rohmat, F.I.W., Labadie, J.W., and Gates, T.K. 2021. Enabling improved water and environmental management in an irrigated river basin using multi-agent optimization of reservoir operations.
· A Sidik, HC Maddi, D Rohmat, S Solehudin, K Sarewo, FIW Rohmat. 2020. Regional Distribution of Relative Drought Using Standardized Precipitation Index (SPI) Calculation in The Lasolo-Konaweha Watershed System, HATHI 6th International Seminar on Advancement of Water Resources Management.
· Rohmat, F.I.W., Labadie, J.W., and Gates, T.K. 2019. Deep learning for compute-efficient modeling of BMP impacts on stream-aquifer exchange and water law compliance in an irrigated river basin.
· Rohmat, F., Labadie, J.W., Gates, T.K. 2019. Application of High-dimensional Epsilon Mutation Linear Particle Swarm Optimization in Mitigating the Effects of Best Management Practices Application in the Lower Arkansas River Basin. 39th Annual American Geophysical Union’s Hydrology Days. 27 – 29 Maret, 2019, Fort Collins, USA.
· Rohmat, Faizal, John W. Labadie, and Timothy K. Gates. 2018. “Computationally Efficient ANN as a Realistic Surrogate of MODFLOW-UZF for Integration with the GeoMODSIM River Basin Management Model.”
· Rohmat, F., Labadie, J.W. 2018. Integrated Water System Planning, Design, and Operation using MODSIM-DSS and Particle Swarm Optimization: Application to Tripa River Basin, Indonesia. 38th Annual American Geophysical Union’s Hydrology Days. 19 – 21 Maret 2018, Fort Collins, USA.
· Rohmat, D., Kendra, H. Natasaputra, S., and Rohmat, F. Delineation of Recharge and Catchment Areas in the Upstream Watersheds to Ensure Sustainability of Water and Energy Supply for Irrigation Areas: Case Study on Tamiang-Langsa River Basin System in Aceh Province, Indonesia. 23rd International Congress on Irrigation and Drainage. 8‐14 Oktober 2017, Mexico City, Mexico.
· Rohmat, F., Labadie, J.W., Gates, T.K. 2017. Application of Neural Networks to Development of a Computationally Efficient Surrogate to the MODFLOW Model: Application to the Stream-aquifer System of the Lower Arkansas River Basin in Colorado. 2017 UCOWR/NIWR Annual Conference. 13- 15 Juni 2017, Fort Collins, USA.
· Soentoro, E. A., Rohmat, F., and Vurnamawati, V. 2014. Fair Budgeting Formulation for O&M of Irrigation Using Multi-Criteria Decision Analysis: WA and AHP Methods. Journal of Civil Engineering, Institut Teknologi Bandung.