ย Professor at University of Tehran, Iran
Prof. Dr. Faramarz Doulati Ardejani ๐ฎ๐ท is a renowned expert in hydrogeology and environmental mining engineering. Currently a Full Professor at the University of Tehran ๐ซ, he has contributed to academia and industry for over three decades. With a Ph.D. from the University of Wollongong ๐ฆ๐บ, he has authored 205 journal papers ๐ and led 30+ national and international industrial projects ๐๏ธ. As head of the MEHR Laboratory and multiple departments, heโs a mentor to over 130 postgrad students ๐จโ๐ซ. A DAAD awardee and Erasmus+ scholar ๐, he advocates for sustainable mining ๐ฑ and hydro-environmental innovation ๐ง.
Profile
Scopus
scholar
๐ Educationย
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๐ Ph.D. in Mining Engineering (Environmental Hydrogeology), University of Wollongong, Australia ๐ฆ๐บ (2000โ2003)
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๐ M.Sc. in Mining Engineering, Amir Kabir University, Tehran ๐ฎ๐ท (1990โ1993)
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๐ B.Sc. in Mining Engineering, Isfahan University of Technology ๐ฎ๐ท (1986โ1990)
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๐งฎ High School Diploma, Math-Physics, Rezvanshahr ๐ฎ๐ท (1986)
๐ผ Experienceย
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๐จโ๐ซ Full Professor, University of Tehran (2011โPresent)
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๐จโ๐ซ Professor, Shahrood University of Technology (2011)
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๐จโ๐ซ Associate Professor (2007โ2011), Assistant Professor (2003โ2007), Shahrood
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๐ข๏ธ Consultant, National Iranian Oil Company (1992โ1999)
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โป๏ธ Environmental Consultant, Iran Colour Research Centre (2004โ2006)
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๐งช Over 30 industrial projects involving hydrogeology & environmental studies
๐น Professional Developmentย
ย Prof. Doulati Ardejani has held numerous leadership roles including Deputy of Graduate Studies and Head of the MEHR Laboratory at the University of Tehran ๐งโ๐ฌ. He was previously Dean of Mining at Shahrood University ๐จโ๐ซ. He launched the ICWR Conference ๐ and has served as Editor-in-Chief for two Scopus-indexed journals ๐. A committed educator, he has advised over 130 graduate students ๐จโ๐. His international exposure includes the Erasmus+ Program with TU Freiberg ๐ฉ๐ช and collaborative research with UNESCO and IMWA ๐. He regularly delivers workshops, webinars, and keynotes on mining and hydro-environmental sustainability ๐ค.
๐ Research Focus
Prof. Doulati Ardejaniโs research focuses on hydrogeology, mine water management ๐ง, environmental impact assessment โป๏ธ, and green mining strategies ๐ฑ. His work bridges academia and real-world challenges in surface and underground mining ๐๏ธ. With expertise in finite element and volume modeling ๐, he designs dewatering systems, studies climate impact on mining ๐, and proposes sustainable water collection in mining zones ๐ฐ. He has also explored pollutant removal using eco-materials ๐งช. His international collaborations emphasize eco-safe mining practices, resource optimization, and climate resilience across diverse geological environments ๐.
๐น Awards & Honorsย
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Awards & Honors
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๐ฉ๐ช 2024 DAAD Award, German Academic Exchange Service
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๐งช 2006 Scientific Commendation, for research on dye removal using almond shells
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๐ฑ 2002 Excellence in Environmental Research, numerical modeling of open-cut mine pollution
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๐ Editor of major international journals (2010โ2018)
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๐ Erasmus+ Scholarship at TU Freiberg (2023โ2024)
๐ Publication
1. Adsorption of Direct Red 80 dye from aqueous solution onto almond shells: Effect of pH, initial concentration and shell type
Citation:
F. Doulati Ardejani, K. Badii, N. Yousefi Limaee, S.Z. Shafaei, A.R. Mirhabibi. Journal of Hazardous Materials, 151(2), 730โ737 (2008).
Cited by: 342
DOI: 10.1016/j.jhazmat.2007.06.039
Summary:
This study explores the effectiveness of raw and treated almond shells as low-cost adsorbents for removing Direct Red 80 dye from water. The authors investigate the effects of pH, initial dye concentration, and adsorbent type. The results demonstrate that dye removal is highly pH-dependent, with maximum adsorption occurring under acidic conditions. The isotherm and kinetic modeling indicate that the adsorption process follows the Langmuir model and pseudo-second-order kinetics.
2. Numerical modelling and laboratory studies on the removal of Direct Red 23 and Direct Red 80 dyes from textile effluents using orange peel, a low-cost adsorbent
Citation:
F. Doulati Ardejani, K. Badii, N. Yousefi Limaee, N.M. Mahmoodi, M. Arami, et al. Dyes and Pigments, 73(2), 178โ185 (2007).
Cited by: 206
DOI: 10.1016/j.dyepig.2006.01.005
Summary:
This paper presents both experimental and numerical modeling of the adsorption of Direct Red 23 and Direct Red 80 dyes onto orange peel. Key operational parameters such as dye concentration, contact time, and temperature are analyzed. The study demonstrates orange peelโs promising capacity for dye removal, offering an environmentally friendly solution to textile wastewater pollution. The adsorption follows Langmuir isotherms and second-order kinetics.
3. Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks
Citation:
M. Raeesi, A. Moradzadeh, F. Doulati Ardejani, M. Rahimi. Journal of Petroleum Science and Engineering, 82, 151โ165 (2012).
Cited by: 166
DOI: 10.1016/j.petrol.2012.01.008
Summary:
This work utilizes artificial neural networks (ANNs) integrated with seismic and well-log data to classify and characterize lithofacies in a hydrocarbon reservoir. The ANN approach outperforms traditional statistical methods, providing more accurate predictions of lithological and petrophysical variations, which are critical for optimizing oil and gas recovery strategies.
4. Monitoring soil lead and zinc contents via combination of spectroscopy with extreme learning machine and other data mining methods
Citation:
V. Khosravi, F. Doulati Ardejani, S. Yousefi, A. Aryafar. Geoderma, 318, 29โ41 (2018).
Cited by: 147
DOI: 10.1016/j.geoderma.2017.11.032
Summary:
The study integrates visible-near infrared spectroscopy with machine learning techniquesโspecifically Extreme Learning Machine (ELM), Support Vector Machine (SVM), and Random Forest (RF)โto estimate soil contamination by lead and zinc. The ELM model provides high accuracy, showing the potential of rapid and cost-effective soil monitoring for environmental and agricultural applications.
5. Decolorization and mineralization of textile dyes at solution bulk by heterogeneous nanophotocatalysis using immobilized nanoparticles of titanium dioxide
Citation:
N.M. Mahmoodi, M. Arami, N. Yousefi Limaee, K. Gharanjig, et al. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 290(1โ3), 125โ131 (2006).
Cited by: 133
DOI: 10.1016/j.colsurfa.2006.05.047
Summary:
This paper evaluates the photocatalytic degradation of various textile dyes using titanium dioxide (TiOโ) nanoparticles immobilized on glass beads. The study reveals efficient dye decolorization and mineralization under UV light, emphasizing the reusability and stability of the immobilized catalyst. It presents a sustainable method for wastewater treatment in textile industries.
Conclusion:
Prof. Faramarz Doulati Ardejaniโs blend of academic excellence, real-world application, and global collaboration makes him exceptionally suited for the Best Researcher Award. His work not only pushes scientific boundaries but also addresses urgent environmental challenges through sustainable and scalable innovations.
๐ท โA true leader in hydro-environmental research whose legacy is marked by innovation, impact, and mentorship.โ