Emad Al Ibrahim

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5 Article

Augmentations for selective multi-species quantification from infrared spectroscopic data
Al Ibrahim, E. & Farooq, A., Jul 19 2023, In: Chemometrics and Intelligent Laboratory Systems. 240, p. 104913
Research output: Contribution to journal › Article › peer-review
4 Scopus citations
Characterization of non-ideal blending in infrared spectra of gasoline surrogates
Al Ibrahim, E., Rekik, H. E. & Farooq, A., Jul 15 2023, In: Fuel. 344, 128134.
Research output: Contribution to journal › Article › peer-review
3 Scopus citations
Transfer Learning Approach to Multitarget Temperature-Dependent Reaction Rate Prediction
Al Ibrahim, E. & Farooq, A., Jul 6 2022, In: The journal of physical chemistry. A. 126, 28, p. 4617-4629 13 p.
Research output: Contribution to journal › Article › peer-review
7 Scopus citations
Prediction of the Derived Cetane Number and Carbon/Hydrogen Ratio from Infrared Spectroscopic Data
Al Ibrahim, E. & Farooq, A., Apr 23 2021, In: Energy & Fuels.
Research output: Contribution to journal › Article › peer-review
25 Scopus citations
Octane prediction from infrared spectroscopic data
Al Ibrahim, E. & Farooq, A., Jan 1 2019, In: Energy and Fuels. 34, 1, p. 817-826 10 p.
Research output: Contribution to journal › Article › peer-review
26 Scopus citations

New Findings from King Abdullah University of Science and Technology (KAUST) in the Area of Machine Learning Described (Voc-certifire: Certifiably Robust One-shot Spectroscopic Classification Via Randomized Smoothing)
Farooq, A., Al Ibrahim, E. & Sy, M.
10/1/24
1 item of Media coverage
Press/Media: Press / Media
Reports from King Abdullah University of Science and Technology (KAUST) Describe Recent Advances in Fuel Research (Characterization of Non-ideal Blending In Infrared Spectra of Gasoline Surrogates)
Farooq, A. & Al Ibrahim, E.
07/14/23
1 item of Media coverage
Press/Media: Press / Media
Fueling a cleaner future for transport
Farooq, A. & Al Ibrahim, E.
03/10/20
1 item of Media coverage
Press/Media: Press / Media
New Model can Pave Way for Cleaner, More Efficient Transport Fuels
Farooq, A. & Al Ibrahim, E.
03/10/20
1 item of Media coverage
Press/Media: Press / Media

Emad Al Ibrahim

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

Augmentations for selective multi-species quantification from infrared spectroscopic data

Characterization of non-ideal blending in infrared spectra of gasoline surrogates

Transfer Learning Approach to Multitarget Temperature-Dependent Reaction Rate Prediction

Prediction of the Derived Cetane Number and Carbon/Hydrogen Ratio from Infrared Spectroscopic Data

Octane prediction from infrared spectroscopic data

New Findings from King Abdullah University of Science and Technology (KAUST) in the Area of Machine Learning Described (Voc-certifire: Certifiably Robust One-shot Spectroscopic Classification Via Randomized Smoothing)

Reports from King Abdullah University of Science and Technology (KAUST) Describe Recent Advances in Fuel Research (Characterization of Non-ideal Blending In Infrared Spectra of Gasoline Surrogates)

Fueling a cleaner future for transport

New Model can Pave Way for Cleaner, More Efficient Transport Fuels

Emad Al Ibrahim

Fingerprint

Collaborations and top research areas from the last five years

Research output

Press/Media