Farshad Sadeghpour | Data prediction | Best Researcher Award

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Dr. Farshad Sadeghpour | Data prediction | Best Researcher Award

Farshad Sadeghpour (b. 1996) šŸ‡®šŸ‡· is a Petroleum Engineer and Data Scientist šŸ’»šŸ›¢ļø with expertise in reservoir engineering, petrophysics, and AI applications in the energy sector. Based in Tehran, Iran šŸ“, he holds a Masterā€™s and Bachelorā€™s in Petroleum Exploration. With extensive experience in EOR, SCAL/RCAL analysis, and machine learning, Farshad has contributed to both academic and industrial R&D at RIPI, NISOC, and PVP. He has published multiple research articles šŸ“š, won international awards šŸ†, and participated in key petroleum projects. He served in the military šŸŖ– and actively collaborates with academia and industry on AI-driven energy solutions.

Profile

Education šŸŽ“

šŸ§‘ā€šŸŽ“ Master’s in Petroleum Engineering (Petroleum Exploration), Petroleum University of Technology, Abadan šŸ‡®šŸ‡· (2019ā€“2022) | GPA: 18.82/20
šŸŽ“ Bachelorā€™s in Petroleum Engineering, Islamic Azad University (Science & Research Branch), Tehran šŸ‡®šŸ‡· (2015ā€“2019) | GPA: 19.14/20
šŸ“š Courses covered include reservoir engineering, geomechanics, well-logging, and advanced data analytics.
šŸ› ļø Projects include COā‚‚ storage modeling, permeability prediction via AI, and LWD-based mud loss forecasting.
šŸ“Š Developed key industry collaborations with NISOC, RIPI, and OEID through thesis, internships, and military service projects.
šŸ’” Honed computational and simulation skills using MATLAB, Python, COMSOL, Petrel, and ECLIPSE.
šŸ›ļø Academic mentors: Dr. Seyed Reza Shadizadeh, Dr. Bijan Biranvand, Dr. Majid Akbari.

Experience šŸ‘Øā€šŸ«


šŸ”¬ Computer Aided Process Engineering (CAPE) ā€“ Petroleum Reservoir Engineer (Nov 2024ā€“Present)
šŸ›¢ļø Petro Vision Pasargad ā€“ Reservoir Engineer & Lab Operator (Sep 2023ā€“May 2024)
šŸ§  Research Institute of Petroleum Industry (RIPI) ā€“ Petroleum Engineer, Data Scientist (Mar 2023ā€“Apr 2024)
šŸ­ National Iranian South Oil Company (NISOC) ā€“ Petroleum Engineer, Petrophysicist (Mar 2021ā€“Nov 2024)
šŸ§Ŗ Internships: NIOC – Exploration Management, Oil & Energy Industries Development (OEID)
šŸ“Š Key contributions include EOR analysis, SCAL/RCAL lab testing, permeability modeling, machine learning pipelines, and field data analysis.
šŸ§¾ Delivered reports, simulations, and AI models supporting production optimization and reservoir characterization.

Awards & Recognitions šŸ…

šŸ„‰ 3rd Prize Winner ā€“ EAGE Laurie Dake Challenge 2022 (Madrid, Spain) šŸŒ
šŸŽ–ļø Recognized for thesis excellence in AI-driven mud loss prediction with NISOC collaboration
šŸ“Œ Acknowledged during military service project with RIPI for developing ANN-based well log models
šŸ… Published in high-impact journals such as Energy, Geoenergy Science and Engineering, and JRMGE
āœļø Co-author of multiple peer-reviewed papers and under-review articles across petroleum engineering disciplines
šŸ”¬ Worked alongside top researchers including Dr. Ostadhassan, Dr. Gao, and Dr. Hemmati-Sarapardeh
šŸ› ļø Actively participated in multidisciplinary teams combining AI, geomechanics, and petrophysics
šŸ“¢ Regular presenter and contributor at petroleum conferences and AI-in-energy seminars.

Research Interests šŸ”¬

šŸ“Œ AI & ML applications in petroleum engineering šŸ§ šŸ›¢ļø ā€“ including ANN, genetic algorithms, and deep learning
šŸ“Š Mud loss zone prediction, formation permeability modeling, COā‚‚ storage feasibility using ML
šŸ§Ŗ Experimental rock mechanics: nanoindentation, geomechanical upscaling, SCAL/RCAL testing
šŸ“ˆ Petrophysical property estimation in carbonate and unconventional reservoirs
šŸŒ Reservoir simulation, LWD analysis, and smart data integration using Python, Petrel, COMSOL
šŸ“– Notable studies include: elastic modulus upscaling, kerogen behavior under pyrolysis, RQI/FZI modeling
šŸ”¬ Interdisciplinary projects bridging data science with geoscience and reservoir engineering
šŸ¤ Collaboration with academic and industry leaders to develop practical, AI-driven solutions for energy challenges.

PublicationsĀ 

  • Elastic Properties of Anisotropic Rocks Using an Stepwise Loading Framework in a True Triaxial Testing Apparatus

    Geoenergy Science and Engineering
    2025-04 |Ā Journal article
    DOI:Ā 10.1016/j.geoen.2025.213883
    CONTRIBUTORS:Ā Farshad Sadeghpour;Ā Hem Bahadur Motra;Ā Chinmay Sethi;Ā Sandra Wind;Ā Bodhisatwa Hazra;Ā Ghasem Aghli;Ā Mehdi Ostadhassan

  • Storage Efficiency Prediction for Feasibility Assessment of Underground CO2 Storage: Novel Machine Learning Approaches

    Energy
    2025-04 |Ā Journal article
    DOI:Ā 10.1016/j.energy.2025.136040
    CONTRIBUTORS:Ā Farshad Sadeghpour

  • A new petrophysical-mathematical approach to estimate RQI and FZI parameters in carbonate reservoirs

    Journal of Petroleum Exploration and Production Technology
    2025-03 |Ā Journal article
    DOI:Ā 10.1007/s13202-025-01952-6
    CONTRIBUTORS:Ā Farshad Sadeghpour;Ā Kamran Jahangiri;Ā Javad Honarmand

  • Effect of stress on fracture development in the Asmari reservoir in the Zagros Thrust Belt

    Journal of Rock Mechanics and Geotechnical Engineering
    2024-11 |Ā Journal article
    DOI:Ā 10.1016/j.jrmge.2023.12.027
    CONTRIBUTORS:Ā Ghasem Aghli;Ā Babak Aminshahidy;Ā Hem Bahadur Motra;Ā Ardavan Darkhal;Ā Farshad Sadeghpour;Ā Mehdi Ostadhassan

  • Comparison of geomechanical upscaling methods for prediction of elastic modulus of heterogeneous media

    Geoenergy Science and Engineering
    2024-08 |Ā Journal article
    DOI:Ā 10.1016/j.geoen.2024.212915
    CONTRIBUTORS:Ā Farshad Sadeghpour;Ā Ardavan Darkhal;Ā Yifei Gao;Ā Hem B. Motra;Ā Ghasem Aghli;Ā Mehdi Ostadhassan

Mudassar Raza | Machine Learning | Best Researcher Award

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Prof. Mudassar Raza | Machine Learning | Best Researcher Award

Prof. Dr. Mudassar Raza is a leading AI researcher and academician, serving as a Professor at Namal University, Mianwali, Pakistan. He is a Senior IEEE Member, Chair Publications of IEEE Islamabad Section, and an Academic Editor for PLOS ONE. With 20+ years of teaching and research experience, he has worked at HITEC University Taxila and COMSATS University Islamabad. His research spans AI, deep learning, image processing, and cybersecurity. He has published 135+ research papers with a cumulative impact factor of 215+, 6066+ citations, an H-index of 44, and an I-10 index of 93. He was listed in Elsevierā€™s Worldā€™s Top 2% Scientists (2023) and ranked #11 in Computer Science in Pakistan. Dr. Raza has supervised 3 PhDs, co-supervising 6 more, and mentored 100+ undergraduate R&D projects. He actively contributes to academia, industry collaborations, and curriculum development while serving as a reviewer for prestigious journals. šŸŒšŸ“–

Profile

Education šŸŽ“

  • Ph.D. in Control Science & Engineering (2014-2017) ā€“ University of Science & Technology of China (USTC), China šŸ‡ØšŸ‡³
    • Specialization: Pattern Recognition & Intelligent Systems
  • MS (Computer Science) (2009-2010) ā€“ Iqra University, Islamabad, Pakistan šŸ‡µšŸ‡°
    • CGPA: 3.64 | Specialization: Image Processing
  • MCS (Master of Computer Science) (2004-2006) ā€“ COMSATS Institute of Information Technology, Pakistan
    • CGPA: 3.24 | 80% Marks
  • BCS (Bachelor in Computer Science) (1999-2003) ā€“ Punjab University, Lahore, Pakistan
    • CGPA: 3.28 | 64.25% Marks
  • Higher Secondary (Pre-Engineering) ā€“ Islamabad College for Boys
  • Matriculation (Science) ā€“ Islamabad College for Boys
    Dr. Razaā€™s academic journey is marked by top-tier universities and a strong focus on AI, pattern recognition, and cybersecurity. šŸŽ“šŸ“š

Experience šŸ‘Øā€šŸ«

  • Professor (2024-Present) ā€“ Namal University, Mianwali
    • Teaching AI, Cybersecurity, and Research Supervision
  • Associate Professor/Head AI & Cybersecurity Program (2023-2024) ā€“ HITEC University, Taxila
    • Led AI & Cybersecurity programs, supervised PhDs, and organized industry-academic collaborations
  • Associate Professor (2023) ā€“ COMSATS University, Islamabad
  • Assistant Professor (2012-2023) ā€“ COMSATS University, Islamabad
  • Lecturer (2008-2012) ā€“ COMSATS University, Islamabad
  • Research Associate (2006-2008) ā€“ COMSATS University, Islamabad
    Dr. Raza has 20+ years of experience in academia, R&D, and industry collaborations, contributing significantly to AI, deep learning, and cybersecurity. šŸ«šŸ“Š

Research Interests šŸ”¬

Prof. Dr. Mudassar Razaā€™s research revolves around Artificial Intelligence, Deep Learning, Computer Vision, Image Processing, Cybersecurity, and Parallel Programming. His work includes pattern recognition, intelligent systems, visual robotics, and AI-driven cybersecurity solutions. With 135+ international publications, he has significantly contributed to AIā€™s real-world applications. His research impact includes 6066+ citations, an H-index of 44, and an I-10 index of 93. He leads multiple AI research groups, supervises PhD/MS students, and actively collaborates with industry and academia. His work is frequently cited, placing him among the top AI researchers globally. As an IEEE Senior Member and a PLOS ONE Academic Editor, he is a key figure in AI-driven innovations and technology advancements. šŸ§ šŸ“Š

  • National Youth Award 2008 by the Prime Minister of Pakistan for contributions to Computer Science šŸŽ–ļø
  • Listed in Worldā€™s Top 2% Scientists (2023) by Elsevier šŸŒ
  • Ranked #11 in Computer Science in Pakistan by AD Scientific Index šŸ“Š
  • Senior IEEE Member (ID: 91289691) šŸ”¬
  • HEC Approved PhD Supervisor šŸŽ“
  • Best Research Productivity Awardee at COMSATS University multiple times šŸ†
  • Recognized by ResearchGate with a Research Interest Score higher than 97% of members šŸ“ˆ
  • Reviewer & Editor for prestigious journals including PLOS ONE šŸ“
    Dr. Raza has received numerous accolades for his contributions to AI, research excellence, and academia. šŸŒŸ

Publications šŸ“š