Mohammad Renewable energy | Best Researcher Award

Posted on by Research Data Analysis

Assoc Prof Dr. Mohammad Renewable energy | Best Researcher Award

Dr. Lichun Zhu | Agricultural Data Analysis– Islamic Azad University – Semnan Branch | Iran

Profile Verified

Google Scholar

👨‍🏫 Summary

Assoc. Prof. Dr. Mohammad Tolou Askari is an accomplished academic in Power Electrical Engineering, currently serving as an Associate Professor at Islamic Azad University, Semnan Branch. With a strong background in both academia and industry, he has held various leadership roles including Head of International Affairs, Director of the Incubator Technology Center, and Managing Editor for multiple academic journals. His professional career spans over two decades, marked by a focus on electrical systems, power market restructuring, and renewable energy solutions.

🎓 Education

Dr. Askari earned his Ph.D. in Power Electrical Engineering from University Putra Malaysia (CGPA 4.0/4.0), where he focused on dynamic investment modeling in power markets with wind sources. He also holds an M.Sc. from the same university (CGPA 3.87/4.0), with research on transformer life estimation. His B.Sc. and Associate degrees were obtained in Iran, both in Power and Industrial Electricity, respectively.

💼 Professional Experience

Since 2011, he has been an Associate Professor at Islamic Azad University. He has also served as a consultant to Iran Small Industries and contributed to numerous engineering and audit projects for factories and industrial zones. His past roles include instructor at UPM, technical manager at Pouyan Tahvieh Co., and department head at the University of Applied Science and Technology (Mahdishahr). He has experience as a lecturer across several university branches and served in editorial capacities for scientific journals.

💻 Technical Skills

Proficient in MATLAB, Digsilent, EMTP-RV, PVsyst, GAMS, SPSS, MINITAB, LINGO, AutoCAD, E-Views, and Microsoft Office. Also skilled in video editing tools like Camtasia and KineMaster, with certification in ICDL.

🧑‍🏫 Teaching Experience

Dr. Askari has taught a wide range of undergraduate to PhD-level courses, including Renewable Energies, Power System Analysis, Smart Grid Optimization, Reliability, Power Electronics, Engineering Mathematics, and Technical English. He has also led laboratory sessions in machines, electronics, and energy systems.

🔬 Research Interests

His research spans Restructured Power Markets, Renewable Energies (Wind, Solar, Biomass, etc.), Smart Grids, Generation & Transmission Planning, Uncertainty Modeling, Microgrids, Hub Energy, and Power System Resilience. He has led numerous funded projects involving system audits, feasibility studies, and optimization across various industrial sectors.

📚 Selected Publications

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

    • Authors: VG Rahman Ashrafi, Meysam Amirahmadi, Mohammad Tolou-Askari

    • Journal: International Journal of Electrical Power and Energy Systems

    • Year: 2021

Evaluation of lightning current using inverse procedure algorithm

    • Authors: M. Izadi, M.Z.A. Ab Kadir, M.T. Askari, M. Hajikhani

    • Journal: International Journal of Applied Electromagnetics and Mechanics

    • Year: 2013

Optimal resilient operation of hub energy system considering uncertain parameters

    • Authors: M. Paktinat, M. Amirahmadi, M. Tolou-Askari, F. Mousavizadeh

    • Journal: Sustainable Energy, Grids and Networks

    • Year: 2022

A new comprehensive model to simulate the restructured power market for seasonal price signals by considering on the wind resources

    • Authors: M.T. Askari, M.Z.A. Ab Kadir, H. Hizam, J. Jasni

    • Journal: Journal of Renewable and Sustainable Energy

    • Year: 2014

Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market

    • Authors: M.T. Askari, M.Z.A. Kadir, M. Tahmasebi, E. Bolandifar

    • Journal: Journal of Modern Power Systems and Clean Energy

    • Year: 2019

Muhammad Usman Siddiqui | Statistical Analysis | Best Researcher Award

Posted on by Research Data Analysis

Mr. Muhammad Usman Siddiqui | Statistical Analysis | Best Researcher Award

Ausenco | Canada

PUBLICATION PROFILE

Orcid

🔰 INTRODUCTION

MUHAMMAD USMAN SIDDIQUI is a Process Consultant with three years of industry experience in the field of chemical engineering, specializing in geometallurgy, process optimization, and debottlenecking. Known for his analytical mindset and innovation in metallurgical modelling, Usman has contributed significantly to the mining and mineral processing industry through high-impact brownfield projects and advanced data-driven methodologies. His technical expertise and academic achievements mark him as a rising figure in the domain of mineral process engineering.

🎓 EARLY ACADEMIC PURSUITS

USMAN began his academic journey at the UNIVERSITY OF BRITISH COLUMBIA, CANADA, where he earned a Bachelor of Applied Science in Chemical Engineering. His exceptional academic performance earned him a place on the Dean’s Honour List and the Outstanding International Student Award. During his undergraduate studies, Usman exhibited a strong aptitude for statistical analysis, data modelling, and research, which later formed the core of his professional and academic contributions.

🧪 PROFESSIONAL ENDEAVORS

SINCE 2022, USMAN has worked as a Process Consultant and Engineer-in-Training with Ausenco, Canada. His work focuses on process optimization, geometallurgy, and creating metallurgical models for process plants across various global mining projects. He has been actively involved in major consulting roles for feasibility and debottlenecking studies in Sweden, Australia, South Africa, and Mexico. His responsibilities included ore characterization, sample selection, flotation test work planning, and development of flotation and comminution models.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

USMAN’S primary research contributions are in geometallurgy, specifically in the optimization of mine-to-mill processes. He excels in aligning ore feed characteristics with processing capabilities to maximize plant performance and economic return. Usman leveraged his software development skills to design automated tools that streamline geometallurgical and process engineering workflows. His notable research includes advanced sample selection methodologies using statistical techniques to improve the efficiency of geometallurgical studies.

🌍 IMPACT AND INFLUENCE

USMAN’S work has had significant impact on brownfield optimization projects and plant-level decision-making processes. By developing robust metallurgical models and integrating data analysis into field operations, he has improved throughput and plant efficiency across multiple continents. His interdisciplinary approach—merging engineering, data science, and process design—has modernized workflows in mineral processing plants and demonstrated measurable economic improvements for his clients.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

USMAN has authored a peer-reviewed paper in the prestigious journal Mining, Metallurgy & Exploration. His publication titled “An Efficient Sample Selection Methodology for a Geometallurgy Study Utilizing Statistical Analysis Techniques” (June 2024, Volume 41, Pages 2193–2201) presents a novel method for optimizing sample selection processes in mineral studies. His contribution is gaining attention for its practical applications in industry and academia alike.

🏅 HONORS & AWARDS

  • OUTSTANDING INTERNATIONAL STUDENT AWARD (2018)

  • DEAN’S HONOR LIST (2023)
    These accolades underscore his academic excellence and commitment to both learning and innovation in chemical engineering and mineral processing.

🌱 LEGACY AND FUTURE CONTRIBUTIONS

LOOKING AHEAD, USMAN aims to deepen his contributions to advanced process modelling and AI-driven optimization in the mining sector. He is keen on exploring how machine learning can further streamline plant operations and geometallurgical forecasting. His long-term vision includes developing open-source tools for global mining companies and mentoring future engineers in applying data analytics to process engineering challenges.

✍️ FINAL NOTE

MUHAMMAD USMAN SIDDIQUI embodies the next generation of engineering professionals—analytical, interdisciplinary, and impactful. His blend of field experience, academic excellence, and research innovation has already set a strong foundation for a future of leadership in the process engineering and geometallurgy sectors. His continued focus on delivering technical solutions with economic value makes him a promising candidate for recognition and further achievement in the global engineering community.

📚 TOP NOTES PUBLICATIONS 

An Efficient Sample Selection Methodology for a Geometallurgy Study Utilizing Statistical Analysis Techniques

  • Authors: Muhammad Usman Siddiqui, Kevin Erwin, Shaihroz Khan, Rajiv Chandramohan, Connor Meinke

  • Journal: Mining, Metallurgy & Exploration

  • Year: 2024

Yameng He | Predictive Analytics | Best Researcher Award

Posted on by Research Data Analysis

Ms. Yameng He | Predictive Analytics | Best Researcher Award

China University of Mining and Technology | China

PUBLICATION PROFILE

Scopus

👩‍🎓 Summary

Yameng He is a dedicated Ph.D. candidate in Civil Engineering at China University of Mining and Technology. Her research focuses on the geophysical evolution of deep rock masses, the damage mechanisms of concrete structures, and CO2 geological storage. With several published papers in renowned journals and multiple patents in the civil engineering sector, she is a promising young researcher in her field.

🎓 Education

Yameng He earned her Ph.D. in Civil Engineering from China University of Mining and Technology (2020–Present), following her M.S. in Civil Engineering from Shijiazhuang Tiedao University (2017–2020). She completed her B.S. in Civil Engineering at the North China Institute of Aerospace Engineering in 2017.

💼 Professional Experience

Currently, as a Ph.D. student at China University of Mining and Technology, Yameng is engaged in cutting-edge research related to geophysical testing in deep rock masses, CO2 geological storage, and the durability of cement materials. Her work aims to improve infrastructure safety and sustainability in challenging environments.

📚 Academic Publications

Yameng He has co-authored several influential papers, such as the one on the evolution of resistivity and permeability of wellbore cement in geological CO2 storage conditions, published in Construction and Building Materials. She has also contributed to research on concrete damage processes under uniaxial compression and participated in the Annual Meeting of Chinese Geoscience Union (CGU-2021).

🔧 Technical Skills

Yameng’s technical expertise includes the development of multi-field geophysical parameter testing devices, numerical simulations for concrete damage analysis, ultrasonic testing of materials under stress, and deep learning applications for structural health monitoring. These skills enable her to approach complex engineering problems from a highly analytical perspective.

🎓 Teaching Experience

Although primarily focused on her research, Yameng has also participated in teaching activities at China University of Mining and Technology, sharing her knowledge and helping to mentor the next generation of civil engineering professionals.

🔬 Research Interests

Her research spans a range of topics including the geophysical evolution of deep rock masses under hydrothermal conditions, ultrasonic damage detection in concrete, and the impact of CO2 on cement materials in geological storage. Yameng is particularly focused on advancing technologies in multi-physics coupling and structural health monitoring.

📚 Top Notes Publications 

Evolution of resistivity and permeability of wellbore cement after corrosion by supercritical CO2 in geological CO2 storage conditions

  • Authors: Y. He, Yameng, L. Song, Lei, P.G. Ranjtih, P. G., Z. Wang, Zukun, L. Wu, Linjun

  • Journal: Construction and Building Materials

  • Year: 2025

 

Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

Posted on by Research Data Analysis

Prof. Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

College of Water Conservancy and Civil Engineering, Shandong Agricultural University | China

Publication Profile

Scopus

PROF. QIANG YUE – A LEADER IN BIG DATA ANALYTICS AND WATER CONSERVANCY RESEARCH 🌐💧

INTRODUCTION 🌟

Prof. Qiang Yue is a prominent academic and researcher at the College of Water Conservancy and Civil Engineering, Shandong Agricultural University, China. Specializing in Big Data Analytics, Prof. Yue has contributed significantly to the field of water conservancy and civil engineering, focusing on the integration of data science and engineering for sustainable solutions. His interdisciplinary approach is helping shape the future of water management systems and infrastructure development.

EARLY ACADEMIC PURSUITS 🎓

Prof. Yue’s academic journey began with a strong foundation in civil engineering and water conservancy. After completing his undergraduate degree, he pursued advanced studies in related fields, obtaining a Master’s and PhD with a focus on big data analytics and its applications in civil engineering and water resources management. His rigorous academic training set the stage for his future contributions to both engineering and data science.

PROFESSIONAL ENDEAVORS 💼

As a faculty member at Shandong Agricultural University, Prof. Yue has played a key role in developing research programs and teaching in the fields of water conservancy and civil engineering. His work bridges the gap between traditional engineering methods and modern data analytics, incorporating advanced technologies like machine learning and AI in the optimization of water resources and infrastructure planning. Prof. Yue has also collaborated with national and international research institutions, contributing to various large-scale projects focused on water management and sustainable civil engineering practices.

CONTRIBUTIONS AND RESEARCH FOCUS ON Big Data Analytics 🔬

Prof. Yue’s research interests lie at the intersection of Big Data Analytics and civil engineering, particularly in the optimization of water conservancy systems. His work focuses on the application of machine learning algorithms, predictive analytics, and real-time data collection to improve the efficiency of water resource management, flood control, and infrastructure development. Additionally, his research aims to enhance the sustainability of civil engineering projects through data-driven decision-making, making significant strides toward smart cities and sustainable environmental practices.

IMPACT AND INFLUENCE 🌍

Prof. Yue’s research has had a profound impact on both the academic community and the industry. His innovative use of Big Data Analytics in water conservancy and civil engineering has transformed how data is used in real-time decision-making, helping optimize water resource management on a large scale. His work influences policy decisions, infrastructure development projects, and sustainability strategies, improving water conservation efforts in China and beyond. Prof. Yue has also mentored a generation of engineers and researchers, sharing his knowledge and experience to cultivate future leaders in the field.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Prof. Yue has authored numerous papers in high-impact journals, with a focus on Big Data Analytics and its applications in water management and civil engineering. His publications cover topics such as predictive modeling, real-time water quality monitoring, and optimization of water distribution systems using machine learning. His research is widely cited in the academic community, reflecting the significance of his work in the integration of Big Data with engineering practices.

HONORS & AWARDS 🏆

Prof. Yue’s exceptional contributions to Big Data Analytics and water conservancy have earned him various honors and awards, including:

  • Best Paper Award, International Conference on Water Management and Engineering (2022)
  • Outstanding Researcher Award, Shandong Agricultural University (2021)
  • Excellence in Teaching Award, College of Water Conservancy and Civil Engineering (2020)
  • Innovation in Data Science Award (2019)

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Prof. Yue’s work is paving the way for the next generation of engineers who will rely on data analytics to create sustainable and efficient infrastructure solutions. His future contributions promise to further the development of smart cities, improve water resource management, and enhance the overall resilience of urban environments to climate change. As he continues to innovate and mentor young engineers, his legacy will endure, shaping the future of civil engineering and environmental sustainability.

FINAL NOTE 📌

Prof. Qiang Yue’s career has been defined by his commitment to applying cutting-edge technology to real-world problems in water conservancy and civil engineering. His research is reshaping how engineers and policymakers approach water management and sustainability. His ability to blend Big Data Analytics with traditional engineering disciplines is a testament to his vision for the future of infrastructure and environmental protection.

 TOP NOTES PUBLICATIONS 📚

Dynamic health prediction of plain reservoirs based on deep learning algorithms
    • Authors: Z., Zhu; Zhaohui, H.; Wu, Hao; Z., Zhang, Zhicheng; R., Wang, Rui; Q., Yue, Qiang
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2025
Recognition and quantification of apparent damage to concrete structure based on computer vision
    • Authors: J., Liu, Jiageng; H., Sun, Hongyu; Q., Yue, Qiang; Y., Jia, Yanyan; S., Wang, Shaojie
    • Journal: Measurement: Journal of the International Measurement Confederation
    • Year: 2025

Vinit Vijay Deshpande | Algorithm Development | Best Researcher Award

Posted on by Research Data Analysis

Dr. Vinit Vijay Deshpande | Algorithm Development | Best Researcher Award

University of Applied Sciences, Darmstadt | Germany

Publication Profile

Scopus
Orcid

DR. VINIT VIJAY DESHPANDE– BIOGRAPHY 🌱📚

📍 PhD in Computational Mechanics | Researcher, Educator, Innovator

Education 🎓

PhD in Computational Mechanics (Expected Feb 2025)
University of Applied Sciences, Darmstadt, Germany

  • Thesis: “Computational strategies for characterization, reconstruction, and property estimation of ceramic foam” (magna cum laude)
  • Advisor: Prof. Dr. Romana Piat

Master of Technology in Engineering Mechanics (May 2013)
Indian Institute of Technology, Delhi, India

Invited Talks 🗣️

  1. Use of image segmentation to characterize failure modes of struts in ceramic foam under compression
    49th International Conference and Expo on Advanced Ceramics and Composites (ICACC 2025), Daytona Beach, Florida, USA
  2. Application of skeletonization algorithm to investigate failure modes of ceramic foam in uniaxial compression
    4th International Workshops on Advances in Computational Mechanics (IWACOM-IV), Kitakyushu, Japan

Conference Presentations 📅

  • Investigating microstructure failure modes of ceramic foam under uniaxial compression – 16th World Congress on Computational Mechanics (WCCM 2024)
  • Artificial microstructure reconstruction algorithm for stiffness property estimation – 48th ICACC 2024
  • Computational methodology for the relation between volume fraction and compression strength of ceramic foam – 21st International Conference on Fracture and Damage Mechanics (FDM 2023)
    (For the complete list of conferences, refer to the original document.)

Patents 📑

  • 12 Patents on combined braking systems for two-wheelers.
  • 2 Patents on innovative stand concepts for two-wheelers.

Awards & Recognitions 🏆

  • Best Paper Award, Collaborative European Research Conference (CERC) 2020
  • Lieutenant Arpan Banerjee Award for securing the highest CGPA in MTech and D.I.I.T programmes at IIT Delhi (2012-13)

Scholarships 💡

  • Doctoral Fellowship, University of Applied Sciences, Darmstadt
  • DAAD Sandwich Scholarship for master’s thesis in Germany

Teaching Experience 👨‍🏫

  • Teaching Assistant: Laboratory course for ‘Numerical Solutions to Partial Differential Equations’ since Fall 2020

Student Advising 👨‍🎓

  • Supervised 6 Master’s Thesis students in the field of computational mechanics.

Research Interests 🔬

  • Microstructure reconstruction algorithms
  • Constitutive modeling
  • Surrogate modeling using machine learning
  • Microstructure segmentation algorithms

Research Experience  ON Algorithm Development 🧑‍🔬

  • Research Associate – University of Applied Sciences, Darmstadt (Sept 2024 – Present)
    Focus: Conductive polymer composites & microstructure algorithms

  • Scientific Assistant – University of Applied Sciences, Darmstadt (Dec 2019 – Aug 2024)
    Focus: Porous ceramics, fracture modeling, and transfer learning-based neural networks

  • Research Assistant – Karlsruhe Institute of Technology (Sept 2012 – Mar 2013)
    Focus: Topology optimization of carbon-carbon composites

  • Research Assistant – IIT Delhi (June 2012 – Aug 2012)
    Focus: Elastic properties of carbon-carbon composites

Industry Experience 🏭

  • Analyst – Vehicle Dynamics Simulation, Hero MotoCorp (Aug 2013 – Dec 2019)
    Focus: Multibody simulations, vehicle dynamics, stability, ride-comfort, and braking systems
  • Trainee – Computer Aided Engineering, Tata Technologies Ltd (July 2010 – July 2011)
    Focus: Mesh modeling of four-wheelers for safety and durability analysis

Technical Skills 💻

  • Advanced simulation software
  • Computational algorithms for material modeling
  • Finite Element Analysis (FEA) and multibody dynamics simulations
  • Machine learning for data-driven modeling

Top Notes Publications 📚

Biaxial compression failure of brittle foams: A transfer learning-based strategy
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Procedia Structural Integrity
    • Year: 2024
Numerical Strategies to Study Compression Failure in Brittle Foams with 3D Realistic Microstructures
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Advanced Structured Materials
    • Year: 2024
Numerical studies of the elastic properties of ceramic foam by creation of the artificial microstructures after processing of computed tomographic images
    • Authors: Romana Piat; Vinit Vijay Deshpande
    • Journal: AIP Conference Proceedings
    • Year: 2023
Compression failure of porous ceramics: A computational study about the effect of volume fraction on damage evolution and failure
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Mechanics of Materials
    • Year: 2023
Application of statistical functions to the numerical modelling of ceramic foam: From characterisation of CT-data via generation of the virtual microstructure to estimation of effective elastic properties
    • Authors: Vinit Vijay Deshpande; Kay André Weidenmann; Romana Piat
    • Journal: Journal of the European Ceramic Society
    • Year: 2021