M. Shaheer Akhtar | Chemical Engineering | Academic Excellence Recognition Award

Published on by Academic Excellence

Prof. M. Shaheer Akhtar | Chemical Engineering | Academic Excellence Recognition Award

Jeonbuk National University | South Korea

Professor M. Shaheer Akhtar is a distinguished researcher and educator in the field of energy materials and nanotechnology, currently serving as a Full Professor at the Laboratory of Energy-AI and the New & Renewable Energy Materials Development Center (NewREC), Jeonbuk National University, Republic of Korea. He also holds a Visiting Professorship at La Trobe University, Melbourne, Australia, contributing to international collaborations in sustainable energy research. He earned his Ph.D. in Chemical Engineering from Jeonbuk National University in 2008, with a dissertation focused on electrode materials and polymer composite electrolytes for dye-sensitized solar cells. Prior to this, he obtained his M.Sc. and B.Sc. in Chemistry from D.D.U. Gorakhpur University, India. Over the years, he has advanced from Postdoctoral Researcher under the Brain Korea 21 program to Instructor, Assistant Professor, Associate Professor, and now Full Professor, demonstrating consistent academic and research leadership. Professor Akhtar’s research spans nanomaterials synthesis, solar cell development, charge storage, photoelectrochemical characterization, and advanced energy devices including sensors, batteries, and FETs. His scholarly influence is reflected in an impressive 12,000+ citations, an h-index of 60, and over 230 indexed publications, positioning him among leading experts in renewable energy materials. An inspiring teacher, he has designed and taught diverse courses ranging from solar cell fundamentals and catalysis to nanoscience and biomaterials. With strong technical expertise in spectroscopy, photocatalysis, and thin-film technologies, Professor Akhtar continues to drive impactful innovations bridging renewable energy, nanotechnology, and artificial intelligence for sustainable development.

Profiles: Scopus | Orcid

Featured Publications

  • Coherent anode based on mesoporous carbon integrated ZnCo₂O₄ composite for efficient lithium-ion batteries.

  • State-of-charge estimation and prediction by machine learning models using experimental dataset of lithium-ion batteries based on ionic liquid modified LiFSI electrolyte.

  • Coupling of ammonium dihydrogen phosphate additives with LiPF₆ electrolytes for improving thermal stability and performance of lithium-ion batteries.

  • Enhanced ethylenediamine detection using WO₃–BiVO₄ nanoflakes heterostructure with exceptional adsorption capabilities: experimental and theoretical studies.

  • Innovative organic electrolytes for enhanced energy density and performance in supercapacitors.

  • Possibility of highly efficient 2D–3D perovskite/CIGS tandem solar cells with over 30% efficiency.

  • Tailoring porous NiMoO₄ nanotube via MoO₃ nanorod precursor for environmental monitoring: electrochemical detection of micro-sized polyvinylchloride.

  • Nitrogen self-doped desiccated coconut–derived carbon dots as optical nanoprobe sensor for the detection of heavy metal ion Hg²⁺.

 

Siyuan Song | Engineering | Best Researcher Award

Published on by Academic Excellence

Assoc. Prof. Dr. Siyuan Song | Engineering | Best Researcher Award

👤 Assoc. Prof. Dr. Siyuan Song, Arizona State University, United States

Dr. Siyuan Song is an Associate Professor at Arizona State University’s Del E. Webb School of Construction, within the School of Sustainable Engineering and the Built Environment. He specializes in construction safety, AI in construction, and workforce development. Dr. Song earned his Ph.D. in Civil Engineering from the University of Alabama, where he focused on construction equipment productivity. He has a strong background in construction engineering and management, which he combines with cutting-edge research in construction automation and robotics. He is dedicated to advancing safety in the construction industry through innovative training programs and workforce development initiatives. Dr. Song has contributed extensively to the field with a focus on enhancing safety protocols in high-risk environments, such as construction sites and surface mining.

Professional Profile

Google Scholar

🌟  Suitability For the Best Researcher Award

Siyuan Song, Ph.D., is an exceptional candidate for the Research for Best Researcher Award due to his extensive contributions to construction safety, workforce development, and AI in construction. As an Associate Professor at Arizona State University, Dr. Song has built a distinguished academic and professional portfolio. His research focuses on addressing critical issues in construction, such as workplace safety, health training, automation, and robotics. His work aligns with key global challenges, particularly in improving safety and health conditions for construction workers, an area in which he has secured significant research funding.

Dr. Song’s professional achievements include receiving multiple prestigious awards, such as the Best Division Paper Award from the American Society for Engineering Education (ASEE) in 2023, and the Outstanding Contribution to Workplace Industry Training Award at the Immersive Learning Research Network (iLRN) Annual Conference in 2023. His dedication to advancing construction safety is evident in his leadership of numerous research projects funded by organizations like the Department of Labor (OSHA and MSHA), focusing on heat-related illness prevention, hazard awareness, and worker safety.

🎓 Education

Dr. Song completed his Ph.D. in Civil Engineering from the University of Alabama in 2017, where his dissertation focused on “Construction Equipment Travel Path Visualization and Productivity Evaluation.” He also holds a Master of Science in Civil Engineering, with a thesis on “Location-Based Tracking of Construction Equipment for Automated Cycle-Time Analysis.” His undergraduate degree, a Bachelor of Science in Construction Engineering and Management, was awarded by Suzhou University of Science and Technology in 2014. His academic path has been defined by his commitment to developing innovative solutions to enhance safety and productivity in the construction industry.

💼  Professional Experience

Dr. Song has extensive teaching and research experience in the field of construction engineering. He currently serves as an Associate Professor at Arizona State University, where he focuses on AI-driven solutions in construction safety. Prior to this, Dr. Song was an Assistant Professor at the University of Alabama and the University of Southern Mississippi. His career has been marked by a strong focus on workforce safety, training, and the use of technology to address challenges in the construction sector. He has also contributed significantly to research grants related to occupational safety and health.

🏅 Awards and Recognition

Dr. Song has received numerous awards for his contributions to construction safety and engineering education. Notable honors include the 2023 Best Division Paper Award from the American Society for Engineering Education (ASEE) Annual Conference, and the 2023 University of Alabama 18 Under 31 Young Alumni Award. He also earned the 2022 ASCE ExCEEd Teaching Fellow Award for Excellence in Civil Engineering Education. Dr. Song’s early academic achievements were recognized through several awards at Suzhou University of Science and Technology, including the Outstanding Student Awards and Outstanding Student Leader awards, reinforcing his leadership and excellence in the field of engineering.

🌍 Research Skills On Engineering

Dr. Song’s research is focused on construction safety and the integration of AI and robotics into the industry. He has expertise in workforce development, workplace safety training, and the automation of construction processes. His research methods often combine traditional construction engineering approaches with emerging technologies like AI, data analytics, and robotics. Dr. Song is passionate about enhancing safety standards on construction sites and has developed training programs aimed at preventing heat-related illnesses and improving hazard awareness for workers in high-risk environments.

📖 Publication Top Notes

  • Improving tolerance control on modular construction project with 3D laser scanning and BIM: A case study of removable floodwall project
    • Authors: H Li, C Zhang, S Song, S Demirkesen, R Chang
    • Citation: Applied Sciences 10 (23), 8680
    • Year: 2020
  • Construction site path planning optimization through BIM
    • Authors: S Song, E Marks
    • Citation: ASCE International Conference on Computing in Civil Engineering 2019, 369-376
    • Year: 2019
  • Fuzzy Multicriteria Decision‐Making Model for Time‐Cost‐Risk Trade‐Off Optimization in Construction Projects
    • Authors: MA Alzarrad, GP Moynihan, MT Hatamleh, S Song
    • Citation: Advances in Civil Engineering 2019 (1), 7852301
    • Year: 2019
  • Impact variables of dump truck cycle time for heavy excavation construction projects
    • Authors: S Song, E Marks, N Pradhananga
    • Citation: Journal of Construction Engineering and Project Management 7 (2), 11-18
    • Year: 2017
  • A study on assessing the awareness of heat-related illnesses in the construction industry
    • Authors: S Song, F Zhang
    • Citation: Construction Research Congress 2022, 431-440
    • Year: 2022
  • Industrial safety management using innovative and proactive strategies
    • Authors: S Song, I Awolusi
    • Citation: Concepts, Applications and Emerging Opportunities in Industrial Engineering
    • Year: 2020
  • Work-related fatalities analysis through energy source recognition
    • Authors: S Song, I Awolusi, Z Jiang
    • Citation: Construction Research Congress 2020, 279-288
    • Year: 2020
  • A Software-Based Approach for Acoustical Modeling of Construction Job Sites with Multiple Operational Machines
    • Authors: B Sherafat, A Rashidi, S Song
    • Citation: Construction Research Congress 2020, 886-895
    • Year: 2020
  • Steel manufacturing incident analysis and prediction
    • Authors: S Song, Q Lyu, E Marks, A Hainen
    • Citation: Journal of Safety, Health and Environmental Research 14 (1), 331-336
    • Year: 2018
  • Impact of discretionary safety funding on construction safety
    • Authors: S Song, I Awolusi, E Marks
    • Citation: Journal of Safety Health and Environmental Research 13 (2), 378-384
    • Year: 2017