Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

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Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | University of Southern California | United States

Mehdi Badami is a dedicated Ph.D. candidate in Environmental Engineering at the University of Southern California (USC) under Prof. Constantinos Sioutas. His expertise lies in air quality improvement, with hands-on experience in air pollution monitoring using advanced instrumentation such as SMPS-CPC, OPS, and Aethalometer 51. He specializes in data-driven environmental assessments, employing Python for pollution source apportionment and emission trend analysis. His research contributes to community-centric environmental policies and sustainable air quality solutions. Passionate about environmental justice, he aims to bridge scientific research with real-world policy implementation. 🌱🔬

Professional Profile:

Google Scholar

Suitability for the Young Scientist Award

Mehdi Badami is a strong candidate for the Young Scientist Award due to his significant contributions to environmental engineering, particularly in air quality improvement. As a Ph.D. candidate at the University of Southern California (USC), his research focuses on air pollution monitoring and data-driven environmental assessments. His expertise in advanced instrumentation (e.g., SMPS-CPC, OPS, Aethalometer 51) and Python-based pollution source apportionment makes him a valuable asset to the field.

Education & Experience 🏢🎓

  • Ph.D. Candidate in Environmental Engineering (2022-Present) – USC, Los Angeles, USA 🇺🇸

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas

  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) – University of Tehran, Iran 🇮🇷

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy

  • B.Sc. in Mechanical Engineering (2012-2016) – K. N. Toosi University of Technology, Iran 🇮🇷

  • Research Assistant – USC Aerosol Lab (2023–Present) 🏭🌫️

    • Conducted air pollution measurements using state-of-the-art monitoring systems
    • Developed Python programs for data automation and pollution trend analysis
    • Led collaborations with institutions like Harvard, UCLA, and Dresden University
    • Mentored Ph.D. students on environmental research projects

  • Research Assistant – Hydro-kinetic Energy Lab, University of Tehran (2017–2022) 🔬💧

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries

  • Teaching Assistant – USC & University of Tehran (2018–2024) 📚👨‍🏫

    • Assisted in courses on climate change, air quality, fluid mechanics, and thermodynamics

Professional Development 🚀

Mehdi Badami has actively contributed to the field of environmental engineering through cutting-edge research on air pollution, sustainability, and emission control. His extensive knowledge of aerosol science, atmospheric chemistry, and data analysis allows him to assess air quality trends with precision. He has developed innovative models for pollution source apportionment, worked on real-time monitoring systems, and collaborated with leading institutions to improve urban air quality. His passion for environmental justice drives his work towards creating actionable solutions that ensure healthier air for communities. His dedication extends beyond academia, as he actively engages in outreach and policy-driven initiatives. 🌿📊

Research Focus 🔍

Mehdi’s research centers on air pollution control, environmental monitoring, and sustainable urban development. His work involves identifying and mitigating pollution sources through field measurements and computational models. He specializes in:

  • Air Quality Assessment 🌫️📊 – Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment 🏭⚖️ – Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science 🌪️💨 – Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies 🤖📉 – Utilizing data science to model pollution trends
  • Climate and Environmental Justice 🌎⚖️ – Advocating for equitable air quality policies in urban communities

Awards & Honors 🏆

  • Outstanding Research Assistant Award – USC, Sonny Astani Department of Civil and Environmental Engineering (2024) 🏅
  • Fellowship Award – USC (2022-2023) 🎓💰 (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Master’s Studies – University of Tehran (2017) 📖🏆
  • Top 0.15% Rank in National Entrance Exam – Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

📄 Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection – Atmospheric Environment (2023) – 📑 Cited by: 11
📄 Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles – Atmospheric Environment (2023) – 📑 Cited by: 7
📄 Numerical study of blood hammer phenomenon considering blood viscoelastic effects – European Journal of Mechanics-B/Fluids (2022) – 📑 Cited by: 7
📄 Development and performance evaluation of online monitors for near real-time measurement of total and water-soluble organic carbon in fine and coarse ambient PM – Atmospheric Environment (2024) – 📑 Cited by: 4
📄 Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipe – Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) – 📑 Cited by: 3
📄 Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface area – Environmental Pollution (2025) – 📑 Cited by: 1

 

 

 

Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

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Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

Prof. Wan Quan Liu, Sun Yat-sen University, China

Prof. Wan Quan Liu is a prominent professor at the School of Intelligent System Engineering at Sun Yat-sen University, where he has been serving since 2021. He earned his Ph.D. in Electrical Engineering from Shanghai Jiaotong University (1991-1993) and holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988), as well as a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985). Previously, he was an ARC Fellow and Senior Lecturer at Curtin University of Technology from 2000 to 2021. Prof. Liu’s research focuses on computer vision, deep learning networks, optimization, and intelligent control systems, where he has made significant contributions that advance these fields.

Professional Profile

Scopus
Orcid

Suitability for the Best Researcher Award:

Prof. Wan Quan Liu’s combination of an extensive educational background, significant research contributions, and recognition in the form of awards makes him an excellent candidate for the Best Researcher Award. His work in computer vision, deep learning, and intelligent control systems is highly relevant in today’s technology-driven landscape, with implications for various sectors including robotics, automation, and artificial intelligence.

The recognition he has received, both at the national and provincial levels, further solidifies his status as a leading researcher in his field. His ongoing research and publications contribute to advancements in critical technologies, making a tangible impact on both academia and industry.

Educational Background:

Prof. Wan Quan Liu earned his PhD in Electrical Engineering from Shanghai Jiaotong University (1991-1993). He holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988) and a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985).

Academic Experience:

Currently, Prof. Liu is a professor at the School of Intelligent System Engineering at Sun Yat-sen University (2021-present). Prior to this, he held various positions, including ARC Fellow and Senior Lecturer at Curtin University of Technology (2000-2021).

Research Interests:

Prof. Liu specializes in computer vision, deep learning networks, optimization, and intelligent control systems, contributing significantly to advancements in these fields.

Awards and Recognition:

His exceptional work has earned him several accolades, including:

  • 2023: National Talented Researcher from the National Education Committee
  • 2022: Pearl Leading Researcher from Guangdong Province

Publication Top Notes:

  • Title: AFS-FCM with Memory: A Model for Air Quality Multi-dimensional Prediction with Interpretability
    • Publication Year: 2024
  • Title: Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection
    • Publication Year: 2024
  • Title: Efficient and Robust Sparse Linear Discriminant Analysis for Data Classification
    • Publication Year: 2024
  • Title: FedREM: Guided Federated Learning in the Presence of Dynamic Device Unpredictability
    • Publication Year: 2024
  • Title: Invertible Residual Blocks in Deep Learning Networks
    • Publication Year: 2024

 

Prof Dr. Weixu liu | Big Data Award | Best Researcher Award

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Prof Dr. Weixu liu | Big Data Award | Best Researcher Award

Prof Dr. Weixu liu, Anhui Medical University, China

Associate Professor Weixu Liu of Anhui Medical University’s Department of Computer Science earned his Ph.D. from Zhejiang University in 2022. Specializing in big data analysis, machine learning, non-destructive evaluation, and structural health monitoring, Dr. Liu has published over 20 peer-reviewed articles and holds numerous patents and software copyrights. A senior member of the China Instrument and Control Society and the Chinese Society for Vibration Engineering, he has been recognized with multiple teaching awards, including a third-class prize in Anhui Province. His leadership in significant projects, such as the Anhui Provincial Outstanding Young Talent Project, and his involvement in national key R&D plans underscore his impactful contributions to the field of computer science and engineering.

Professional Profile:

Scopus

Suitability for the Research for Best Researcher Award

Assoc. Prof. Dr. Weixu Liu is a highly suitable candidate for the Research for Best Researcher Award due to his significant contributions to the fields of big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. His academic achievements, extensive research activities, and innovative contributions highlight his excellence in research and development.

🎓 Academic Expertise

Associate Professor, Department of Computer Science, Anhui Medical University 🎓
Weixu Liu is an accomplished Associate Professor, Deputy Director, and Master Supervisor at Anhui Medical University’s Department of Computer Science. He earned his Ph.D. from Zhejiang University in 2022.

Research Interests and Contributions

Dr. Liu’s research focuses on big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. He has published over 20 peer-reviewed journal articles and holds more than ten national invention patents, twenty utility model patents, and ten national computer software copyrights. His work has been supported by various government and corporate grants.

Professional Achievements

Dr. Liu is a senior member of the China Instrument and Control Society and a member of the Chinese Society for Vibration Engineering. He has received multiple awards for his teaching achievements, including a third-class prize in Anhui Province. He has led several significant projects, including Anhui Provincial Outstanding Young Talent Project and various municipal and national science and technology projects.

Innovations and Impact

Dr. Liu’s research has resulted in substantial scientific and technological advancements, including a conversion of achievements worth 500,000 RMB. His involvement in national key R&D plans and extensive project experience highlights his significant role in advancing the field of computer science and engineering.

Publication Top Notes:

  • Title: Multi-Feature Integration and Machine Learning for Guided Wave Structural Health Monitoring: Application to Switch Rail Foot
    • Citations: 20
    • Year: 2021
  • Title: Numerical Investigation of Locating and Identifying Pipeline Reflectors Based on Guided-Wave Circumferential Scanning and Phase Characteristics
    • Year: 2020
    • Open Access: Yes
  • Title: Sprouting Potato Recognition Based on Deep Neural Network GoogLeNet
    • Citations: 5
    • Year: 2018
  • Title: Phase Characteristic Analysis and Experimental Study on the Guided Wave Reflected from Expressway Guardrail Posts
    • Citations: 3
    • Year: 2017
  • Title: Numerical Simulation and Experimental Investigation on Ultrasonic Guided Waves in Multilayered Pipes Based on SAFE
    • Citations: 14
    • Year: 2014

 

 

Mrs. Marta Zorrilla | Big data Award | Best Researcher Award

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Mrs. Marta Zorrilla | Big data Award | Best Researcher Award

Mrs. Marta Zorrilla, University of cantabria, Spain

Mrs. Marta Zorrilla is a distinguished academic with a Ph.D. in Telecommunication Engineering from Universidad de Cantabria, Spain, complemented by a Bachelor’s and Master’s in the same field. With an H-Index of 10 on Web of Science and 19 on Google Scholar, and 1232 citations, her research has significantly impacted Learning Analytics, Educational Data Mining, and Big Data Technologies. She has developed frameworks for MOOCs, a reference architecture for Big Data, and leads a national R&D project on data stream mining for Industry 4.0. Mrs. Zorrilla has held various teaching and management roles, including Vice-Dean and Director of the Teaching Staff Area at Universidad de Cantabria. She is also a key member of the Software Engineering and Real-Time Group (ISTR), contributing to software engineering, real-time systems, and data science.

🌍 Professional Profile

Orcid

Suitability for the Best Researcher Award

  1. Academic and Research Impact: Mrs. Zorrilla’s research contributions in document databases, learning analytics, big data technologies, and data governance have had a significant impact. Her high citation count and substantial H-index reflect the influence and recognition of her work.
  2. Innovative Contributions: Her pioneering work in developing frameworks for data governance and learning analytics, as well as her contributions to big data technologies, demonstrate innovation and practical applications in critical areas of technology and industry.
  3. Leadership and Mentorship: Mrs. Zorrilla has played a key role in mentoring PhD researchers and has been involved in numerous national and European research projects. Her leadership in these areas highlights her commitment to advancing research and supporting the next generation of scholars.
  4. Teaching Excellence: Her long-standing teaching role and management positions at Universidad de Cantabria showcase her dedication to education and academic administration, further enhancing her profile as a distinguished researcher.
  5. Proven Track Record: Her extensive list of publications, including articles in high-impact journals, and her role in major research projects demonstrate a robust and successful research career.

Academic Qualifications:

She holds a Bachelor in Telecommunication Engineering, a Master in Telecommunication, and a PhD in Telecommunication Engineering, all from Universidad de Cantabria, Spain. 🎓

Research Indicators:

With an H-Index of 10 (Web of Science) and 19 (Google Scholar), and 1232 citations, Mrs. Zorrilla has made substantial contributions to her field. She has 5 Quinquenios and 2 Sexenios. 📈

Research Achievements:

Her early career saw the development of a neural network engine and the founding of Predictia. She has made significant contributions to Learning Analytics and Educational Data Mining, including frameworks for MOOCs and a European project. Her work in Big Data Technologies includes a reference architecture and benchmarks for technology configuration. She has also developed a data governance framework and is the Principal Investigator for a national R&D project on data stream mining for Industry 4.0. 📊

Teaching and Management Roles:

Mrs. Zorrilla has extensive teaching experience in database technologies and data management. She has held management roles including Vice-dean, head of studies, and Director of the Teaching Staff Area at Universidad de Cantabria. 👩‍🏫

Research Group CV Summary:

She is active in the Software Engineering and Real-Time Group (ISTR), focusing on software engineering, real-time systems, databases, and data science, contributing to numerous projects and publications. 🛠️

Publication Top Notes:

  • Title: Fleet Management Systems in Logistics 4.0 Era: A Real-Time Distributed and Scalable Architectural Proposal
    • Year: 2023
  • Title: An I4.0 Data Intensive Platform Suitable for the Deployment of Machine Learning Models: A Predictive Maintenance Service Case Study
    • Year: 2022
  • Title: A Reference Framework for the Implementation of Data Governance Systems for Industry 4.0
    • Year: 2022
  • Title: A Big Data-Centric Architecture Metamodel for Industry 4.0
    • Year: 2021
  • Title: A Data Governance Framework for Industry 4.0
    • Year: 2021

 

 

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

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Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo, University of Chinese Academy of Sciences, China

Prof. Jianfeng Guo is a distinguished professor at the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has been a key figure since 2010 and has served as a professor since 2018. He earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in 2007 and completed postdoctoral research at Tsinghua University. Jianfeng’s research spans Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management. He has led over 60 significant projects, including collaborations with Baidu Big Data Lab and Ant Financial Services Group, and has published more than 90 papers and holds multiple patents and software copyrights. His international experience includes visits to top institutions and collaborations with global software companies.

🌍 Professional Profile

Scopus

🎓 Education

Jianfeng Guo earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in December 2007. He completed postdoctoral research at the CIMS Engineering Research Center of Tsinghua University from January 2008 to December 2009. He was a Senior Visiting Scholar at NEC China Research Institute from August 2009 to March 2010.

🔬 Research Interests

Jianfeng specializes in Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management.

🏢 Current Position

Since March 2010, Jianfeng has been with the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has served as a professor since 2018. He is also the Director of the Research Department for Think Tank Construction at the Institutes of Science and Development, CAS.

🌐 Notable Projects & Collaborations

Jianfeng has led over 60 projects, including NSFC projects, national programs, and enterprise-commissioned projects. He has collaborated with Baidu Big Data Lab and Ant Financial Services Group, contributing to advancements in big data and financial security.

📝 Publications & Patents

He has published more than 90 papers, including over 60 in international journals, and holds 4 invention patents and 15 computer software copyrights.

🌍 International Experience

Jianfeng has visited prestigious institutions such as the University of Oldenburg, Imperial College, and Cambridge University, and worked with international software companies like ASCORA and TIE.

Publication Top Notes:

  • Title: Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars
    • Cited by: 1
    • Year: 2024
  • Title: A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing
    • Cited by: 3
    • Year: 2024
  • Title: Simulation research on the evolution pathway planning of energy supply and demand in China under the dual carbon targets
    • Cited by: 2
    • Year: 2023
  • Title: Electric vehicle adoption and local PM2.5 reduction: Evidence from China
    • Cited by: 7
    • Year: 2023
  • Title: Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model
    • Cited by: 53
    • Year: 2023