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USD 50 /hr
Hire Dr. Zahid U.
South Korea
USD 50 /hr
AI Modeling & Process Simulation Expert | Chemical & Process Systems Engineer | Advanced Solutions for Industry & Resear
Profile Summary
Subject Matter Expertise
Services
Writing
Technical Writing,
Business & Legal Writing
Research
Market Research,
Feasibility Study,
Fact Checking,
Gap Analysis,
Gray Literature Search,
Scientific and Technical Research,
Systematic Literature Review
Consulting
Digital Strategy Consulting,
Scientific and Technical Consulting
Data & AI
Predictive Modeling,
Statistical Analysis,
Image Processing,
Image Analysis,
Algorithm Design-ML,
Data Visualization,
Big Data Analytics,
Text Mining & Analytics,
Data Mining
Product Development
Product Evaluation,
Manufacturing,
Quality Assurance & Control (QA/QC)
Work Experience
PhD
Korea Institute of Science and Technology
- Present ![]()
Education
PhD in Energy and Environment Technology
Korea Institute of Science and Technology (KIST), Seoul, South Korea
September 2022 - December 2025
Master in Process System Engineering
National University of Sciences and Technology (NUST), Pakistan
October 2019 - December 2021
Bachelor in Chemical Engineering
University of Engineering and Technology, Pakistan
September 2015 - August 2019
Certifications
- Certification details not provided.
Publications
JOURNAL ARTICLE
Ullah, Zahid, Yun, Nakyeong, Rossi, Ruggero, Son, Moon(2025). Autonomous water quality management in an electrochemical desalination process. Water Research. 280. p. 123521. Elsevier
Ullah, Zahid, Ahmad, Iftikhar, Samad, Abdul, Saghir, Husnain, Ahmad, Farooq, Kano, Manabu, Caliskan, Hakan, Caliskan, Nesrin, Hong, Hiki(2025). Artificial intelligence assisted prediction of optimum operating conditions of shell and tube heat exchangers: A grey-box approach. CAAI Transactions on Intelligence Technology. 10. (2). p. 349--358. Wiley Online Library
Ullah, Zahid, Liao, Ziqiao, Choi, KungWon, Son, Moon, Ahn, Yongtae, Khan, Moonis Ali, Prabhu, Subbaiah Muthu, Jeon, Byong-Hun(2024). Artificial neural network modeling for the oxidation kinetics of divalent manganese ions during chlorination and the role of arsenite ions in the binary/ternary systems. Water Research. 259. p. 121876. Elsevier
Ullah, Zahid, Kim, Hoo Hugo, Choi, Byeongwook, Jeong, Nahyeon, Cho, Kyung Hwa, Park, Sanghun, Baek, Sang-Soo, Son, Moon(2024). Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model. Water Research. 262. p. 122092. Elsevier
Ullah, Zahid, Tarus, Bethwel Kipchirchir, Jande, Yusufu AC, Njau, Karoli N, Byun, Jeehye, Son, Moon(2024). Desalination performance in versatile capacitive/battery deionization configurations using a cation intercalating electrode. Desalination. 586. p. 117857. Elsevier
Zahid Ullah, Muzammil Khan, Imran Khan, Asif Jamil, Umair Sikandar, Muhammad Taqi Mehran, Muhammad Mubashir, Pei En Tham, Kuan Shiong Khoo, Pau Loke Show(2024). Recent Progress in Oxidative Dehydrogenation of Alkane (C2--C4) to Alkenes in a Fluidized Bed Reactor Under Mixed Metallic Oxide Catalyst. Journal of Inorganic and Organometallic Polymers and Materials. 34. (1). p. 1--13. Springer US
Ullah, Zahid, Yun, Nakyeong, Rossi, Ruggero, Son, Moon(2024). Reinforcement learning and machine learning controllers for enhancing water quality and process efficiency in electrochemical desalination. ACS ES&T Water. 4. (12). p. 5482--5491. ACS Publications
Ullah, Zahid, Naqvi, Salman Raza, Taqvi, Syed Ali Ammar, Khan, Muhammad Nouman Aslam, Farooq, Wasif, Mehran, Muhammad Taqi, Juchelková, Dagmar, Štěpanec, Libor, others(2023). Applications of machine learning in thermochemical conversion of biomass-A review. Fuel. 332. p. 126055. Elsevier
Ullah, Zahid, Yoon, Nakyung, Tarus, Bethwel Kipchirchir, Park, Sanghun, Son, Moon(2023). Comparison of tree-based model with deep learning model in predicting effluent pH and concentration by capacitive deionization. Desalination. 558. p. 116614. Elsevier
Ullah, Zahid, Park, Sanghun, Yoon, Nakyung, Tarus, Bethwel Kipchirchir, Choi, Byeongwook, Kim, Hoo Hugo, Son, Moon(2023). Energy storage capability of seawater batteries for intermittent power generation systems: Conceptualization and modeling. Journal of Power Sources. 580. p. 233322. Elsevier
Ullah, Zahid, Khan, Muzammil, Mašek, Ondřej, Naqvi, Salman Raza, Khan, Muhammad Nouman Aslam(2022). Artificial neural networks for the prediction of biochar yield: a comparative study of metaheuristic algorithms. Bioresource technology. 355. p. 127215. Elsevier
Ullah, Zahid, Khan, Muzammil, Naqvi, Salman Raza, Khan, Muhammad Nouman Aslam, Farooq, Wasif, Anjum, Muhammad Waqas, Yaqub, Muhammad Waqas, AlMohamadi, Hamad, Almomani, Fares(2022). An integrated framework of data-driven, metaheuristic, and mechanistic modeling approach for biomass pyrolysis. Process Safety and Environmental Protection. 162. p. 337--345. Elsevier
Muzammil Khan, Zahid Ullah, Ondřej Mašek, Salman Raza Naqvi, Muhammad Nouman Aslam Khan(2022). Artificial neural networks for the prediction of biochar yield: a comparative study of metaheuristic algorithms. Bioresource technology. 355. p. 127215. Elsevier
Ullah, Zahid, Naqvi, Salman Raza, Farooq, Wasif, Yang, Haiping, Wang, Shurong, Vo, Dai-Viet N, others(2021). A comparative study of machine learning methods for bio-oil yield prediction--A genetic algorithm-based features selection. Bioresource Technology. 335. p. 125292. Elsevier
Ullah, Zahid, Khan, Muzammil, Mehran, Muhammad Taqi, Haq, Zeeshan Ul, Naqvi, Salman Raza, Ihsan, Mehreen, Abbass, Haider(2021). Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review. Expert systems with applications. 185. p. 115695. Elsevier
Ullah, Zahid, Ahmad, Iftikhar, Sana, Adil, Kano, Manabu, Cheema, Izzat Iqbal, Menezes, Brenno C, Shahzad, Junaid, Khan, Muzammil, Habib, Asad(2021). Machine learning applications in biofuels’ life cycle: Soil, feedstock, production, consumption, and emissions. Energies. 14. (16). p. 5072. MDPI