Md. Kamrul Islam | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Md. Kamrul Islam | Engineering | Best Researcher Award

Assoc. Prof. Dr. Md. Kamrul Islam, King Faisal University, Saudi Arabia 

Dr. Md. Kamrul Islam, an Australian national, currently serves as an Associate Professor at King Faisal University, KSA. With over two decades of experience in civil and transportation engineering, he holds a PhD from the University of New South Wales, Australia, and advanced degrees from the University of Tokyo and DUET, Bangladesh. Dr. Islam’s research focuses on stochastic modeling, asphalt performance, and public transport systems. He has successfully led more than 50 research projects funded by Deanship of Scientific Research and collaborated with premier institutions like University of Illinois and Texas A&M. His excellence has been recognized with prestigious awards such as the Furuichi Kimitake Prize and Institute Gold Medal. Dr. Islam is also a proactive academic mentor, guiding numerous undergraduate projects and contributing to international academic collaborations. His technical, analytical, and conceptual skills have made a significant impact on the field of engineering.

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Summary of Suitability for the Research for Best Researcher Award – Md. Kamrul Islam

Dr. Md. Kamrul Islam, affiliated with King Faisal University, Saudi Arabia, and an Australian citizen, presents a promising profile for the Research for Best Researcher Award. As a faculty member at a reputed institution in the Gulf region, he is likely engaged in cutting-edge research and academic collaboration, contributing significantly to his field. His dual academic and cultural experience, having connections in both Australia and the Middle East, potentially strengthens his international outreach and research dissemination impact.

Given the rigorous environment of King Faisal University, which emphasizes innovation and scholarly contributions, Dr. Islam’s ongoing involvement likely includes authoring peer-reviewed articles, mentoring postgraduate researchers, and participating in international conferences. If his work spans applied or interdisciplinary domains, it would further align with the award’s emphasis on impactful and forward-looking research contributions.

🎓 Education 

Dr. Md. Kamrul Islam’s academic journey showcases his deep-rooted expertise in transportation and civil engineering. He earned his PhD in Transportation Engineering from the University of New South Wales, Australia, in 2014. His doctoral thesis focused on stochastic modeling of public transit performance, leading to several high-impact journal publications. Prior to this, he obtained his Master’s in Engineering with a major in Transportation Planning from the University of Tokyo, Japan, in 2006. His master’s research on urban systems and consumption behavior across East Japan equipped him with advanced simulation and data analysis skills. Dr. Islam began his academic pursuit with a B.Sc. in Civil Engineering from DUET, Bangladesh, in 2002, where he graduated with top honors and was later accredited by Engineers Australia as meeting professional engineer standards. His educational background has laid the foundation for his exceptional contributions to engineering research and teaching.

💼 Professional Experience

Dr. Md. Kamrul Islam has extensive academic and industry experience. He is currently an Associate Professor (since September 2024) and was formerly an Assistant Professor (2015–2024) at the Department of Civil and Environmental Engineering, King Faisal University (KFU), KSA. At KFU, he spearheaded multi-institutional research collaborations and managed projects under the Saudi Aramco Chair on Asphalt Pavement. Before joining KFU, he held faculty positions at DUET, Bangladesh, from 2003 to 2015, progressing from Lecturer to Assistant Professor. His international experience includes roles as a Casual Graduate Academic at UNSW, Australia, and as a Civil Engineer at Pacific Consultant International in Japan, where he contributed to deep-sea port planning. Earlier, he worked as a Project Implementation Officer for the Ministry of Food and Disaster Management, Bangladesh. Throughout his career, he has balanced rigorous academic teaching, research leadership, and field-level infrastructure planning with exceptional professionalism.

🏅 Awards and Recognition

Dr. Md. Kamrul Islam’s outstanding academic and research contributions have earned him multiple prestigious accolades. In 2006, he received the Furuichi Kimitake Prize from the University of Tokyo for excellence in engineering graduation, recognizing his innovative thesis and academic merit. Earlier, in 2002, he was honored with the Institute Gold Medal by the Board of Governors of DUET, Bangladesh, for securing top marks in his undergraduate studies. His research success is further exemplified by securing and completing over 50 research projects sponsored by the Deanship of Scientific Research (DSR) at King Faisal University. These achievements are a testament to his commitment to advancing engineering through research, innovation, and academic collaboration. Additionally, his role in fostering international research networks and mentoring undergraduate students highlights his dedication to academic excellence and leadership in civil and transportation engineering.

🌍 Research Skill On Engineering

Dr. Md. Kamrul Islam exhibits a dynamic portfolio of advanced research skills. He specializes in transportation engineering, stochastic modeling, and asphalt material performance. His PhD research demonstrated his ability to analyze complex transit systems using computational techniques and large-scale algorithms in MATLAB. At KFU, he led multidisciplinary projects addressing sulfur-extended asphalt, pavement benchmarking, and life-cycle assessments. Dr. Islam has developed significant expertise in analytical modeling, data simulation, and numerical approximation, often applied to real-world transport networks. His work involves integrating academic theory with field-based applications, allowing for policy-relevant insights and innovations in civil infrastructure. He has also mastered collaborative research management, coordinating with leading institutions in the USA and Japan. With strong technical acumen, conceptual clarity, and problem-solving approaches, he continues to contribute to academic advancement and sustainable engineering solutions.

📖  Publication Top Notes

  • Title: A review of the evolution of technologies to use sulphur as a pavement construction material
    Authors: N. Sakib, A. Bhasin, M.K. Islam, K. Khan, M.I. Khan
    Journal: International Journal of Pavement Engineering, 22(3), 392-403
    Citations: 40
    Year: 2021

  • Title: Towards sustainable road safety in Saudi Arabia: Exploring traffic accident causes associated with driving behavior using a Bayesian belief network
    Authors: M.M. Rahman, M.K. Islam, A. Al-Shayeb, M. Arifuzzaman
    Journal: Sustainability, 14(10), 6315
    Citations: 33
    Year: 2022

  • Title: Climate change in Bangladesh: Temperature and rainfall climatology of Bangladesh for 1949–2013 and its implication on rice yield
    Authors: E. Alam, A.E.E. Hridoy, S.M.S.H. Tusher, A.R.M.T. Islam, M.K. Islam
    Journal: PLOS ONE, 18(10), e0292668
    Citations: 29
    Year: 2023

  • Title: Predicting road crash severity using classifier models and crash hotspots
    Authors: M.K. Islam, I. Reza, U. Gazder, R. Akter, M. Arifuzzaman, M.M. Rahman
    Journal: Applied Sciences, 12(22), 11354
    Citations: 28
    Year: 2022

  • Title: Coupling of machine learning and remote sensing for soil salinity mapping in coastal area of Bangladesh
    Authors: S.K. Sarkar, R.R. Rudra, A.R. Sohan, P.C. Das, K.M.M. Ekram, S. Talukdar, …
    Journal: Scientific Reports, 13(1), 17056
    Citations: 24
    Year: 2023

  • Title: A bulk queue model for the evaluation of impact of headway variations and passenger waiting behavior on public transit performance
    Authors: M.K. Islam, U. Vandebona, V.V. Dixit, A. Sharma
    Journal: IEEE Transactions on Intelligent Transportation Systems, 15(6), 2432-2442
    Citations: 23
    Year: 2014

  • Title: Reliability analysis of public transit systems using stochastic simulation
    Authors: M.K. Islam, U. Vandebona
    Journal: Not specified
    Citations: 21
    Year: 2010

  • Title: Greenhouse gas emissions in the industrial processes and product use sector of Saudi Arabia—An emerging challenge
    Authors: M.M. Rahman, M.S. Rahman, S.R. Chowdhury, A. Elhaj, S.A. Razzak, …
    Journal: Sustainability, 14(12), 7388
    Citations: 20
    Year: 2022

  • Title: A critical, temporal analysis of Saudi Arabia’s initiatives for greenhouse gas emissions reduction in the energy sector
    Authors: M.M. Rahman, M.A. Hasan, M. Shafiullah, M.S. Rahman, M. Arifuzzaman, …
    Journal: Sustainability, 14(19), 12651
    Citations: 19
    Year: 2022

  • Title: Flood hazard mapping using GIS-based statistical model in vulnerable riparian regions of sub-tropical environment
    Authors: A. Ghosh, U. Chatterjee, S.C. Pal, A.R.M. Towfiqul Islam, E. Alam, M.K. Islam
    Journal: Geocarto International, 38(1), 2285355
    Citations: 18
    Year: 2023

Karthik K | Engineering | Best Researcher Award

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Dr. Karthik K | Engineering | Best Researcher Award

Dr. Karthik K, Vellore Institute of Technology, Vellore, India

Karthik K is an accomplished academician and researcher specializing in computer vision, deep learning, and medical imaging. With over a decade of experience in teaching and research, he has contributed significantly to the field of artificial intelligence in healthcare applications. Currently serving as an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, he has previously worked at St. Joseph Engineering College and NITK, Surathkal. His research is backed by strong academic credentials, numerous publications, and active collaborations with esteemed institutions like NITK, NITPy, and VIT AP. Karthik has received the VIT Seed Grant for AI-driven cricket commentary generation and has applied for prestigious research grants. His contributions to automated medical scan quality enhancement and content-based medical image retrieval have been widely recognized. An active IEEE and IAENG member, he continues to drive innovation in AI and deep learning for intelligent healthcare applications.

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Evaluation of Dr. Karthik K for the Research for Best Researcher Award

Dr. Karthik K, currently an Assistant Professor Sr. Grade I at the Vellore Institute of Technology (VIT), has demonstrated strong research contributions in the fields of computer vision, deep learning, and medical imaging. His research spans content-based medical image retrieval, automated radiography report retrieval, and deep learning-based medical scan quality enhancement, which have direct applications in intelligent healthcare systems. With six journal publications in SCI and Scopus-indexed journals, along with 145 citations, his academic impact is notable.

In addition to his research, Dr. Karthik has published book chapters, submitted a patent, and collaborated with reputed institutions such as NITK, NITPy, and VIT AP. His contributions to AI-driven healthcare applications, particularly in medical image classification and enhancement, showcase his innovative approach to solving real-world medical challenges. Furthermore, his ongoing VIT Seed Grant project on AI-generated cricket commentary and a DST-SURE research grant under review indicate his continued commitment to advancing AI applications across multiple domains.

🎓 Education 

Karthik K has built a strong academic foundation in the fields of computer science and engineering. He pursued his Bachelor’s and Master’s degrees with a focus on artificial intelligence, deep learning, and medical imaging. His research interests led him to work as a Research Fellow at NITK Surathkal, where he contributed to the DST-ECR-funded project on deep learning frameworks for intelligent healthcare applications. During his tenure, he gained extensive expertise in content-based medical image retrieval and automated medical scan enhancements. His academic journey has been marked by continuous learning and contributions to research, with publications in renowned journals and conferences. Karthik’s passion for AI-driven innovations is evident in his scholarly work, patents, and ongoing research projects. His educational background has laid the foundation for his teaching and research career, equipping him with the knowledge and skills to drive advancements in AI, deep learning, and medical imaging applications.

💼 Professional Experience 

Karthik K brings over 10 years of experience in academia and research. He is currently an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, where he specializes in AI, computer vision, and medical imaging. Prior to this, he was an Assistant Professor at St. Joseph Engineering College, Vamanjoor, Mangaluru (2020–2023) and an Assistant Lecturer at NITK, Surathkal (2015–2017). His professional journey includes a research fellowship at NITK Surathkal, where he worked on a DST-ECR-funded project developing deep learning frameworks for intelligent healthcare. Karthik has contributed significantly to AI-driven innovations, collaborating with institutions like NITK, NITPy, and VIT AP. His expertise extends to consultancy projects, editorial appointments, and patents. He has published extensively in SCI and Scopus-indexed journals and remains actively involved in advancing deep learning applications for medical imaging, making significant contributions to academia and industry collaborations.

🏅 Awards and Recognition

Karthik K has been recognized for his contributions to artificial intelligence and medical imaging research. He received the VIT Seed Grant (2023–2025) for his innovative project on AI-driven cricket commentary generation. Additionally, he has applied for the DST-SURE research grant, currently under review. His work in content-based medical image retrieval and deep neural networks for healthcare applications has been acknowledged in multiple international journals and conferences. Karthik has published several book chapters with ISBN numbers, showcasing his expertise in AI and deep learning. He actively collaborates with esteemed institutions and has been invited for editorial appointments in reputed journals. His research contributions have earned him membership in professional organizations such as IEEE and IAENG. With over 145 citations in SCI and Scopus-indexed publications, his work continues to impact the field of intelligent healthcare applications. His commitment to research excellence makes him a strong contender for prestigious awards.

🌍 Research Skills On Engineering

Karthik K possesses extensive research skills in computer vision, deep learning, and medical imaging. His expertise includes developing AI-driven frameworks for intelligent healthcare applications, enhancing medical scan quality, and implementing deep neural networks for automated medical image retrieval. He has successfully led research projects, including a DST-ECR-funded initiative at NITK Surathkal and ongoing consultancy projects. His ability to integrate AI with real-world healthcare challenges has resulted in significant innovations such as ViewNet for scan orientation and automated radiography report retrieval. Karthik’s research has been published in SCI and Scopus-indexed journals, contributing to the broader scientific community. He is skilled in grant writing, patent filing, and interdisciplinary collaborations, with active partnerships with NITK, NITPy, and VIT AP. His research acumen, combined with hands-on experience in deep learning and AI applications, positions him as a leader in advancing intelligent healthcare solutions through cutting-edge technology.

 📖 Publication Top Notes

  • Title: A deep neural network model for content-based medical image retrieval with multi-view classification
    Authors: K Karthik, SS Kamath
    Citation: 60
    Year: 2021
  • Title: A hybrid feature modeling approach for content-based medical image retrieval
    Authors: K Karthik, SS Kamath
    Citation: 16
    Year: 2018
  • Title: COVIDDX: AI-based Clinical Decision Support System for Learning COVID-19 Disease Representations from Multimodal Patient Data
    Authors: V Mayya, K Karthik, KS Sowmya, K Karadka, J Jeganathan
    Citation: 13
    Year: 2021
  • Title: Analysis and prediction of fantasy cricket contest winners using machine learning techniques
    Authors: K Karthik, GS Krishnan, S Shetty, SS Bankapur, RP Kolkar, TS Ashwin, …
    Citation: 13
    Year: 2021
  • Title: MSDNet: A deep neural ensemble model for abnormality detection and classification of plain radiographs
    Authors: K Karthik, S Sowmya Kamath
    Citation: 12
    Year: 2023
  • Title: Deep neural models for automated multi-task diagnostic scan management—quality enhancement, view classification and report generation
    Authors: K Karthik, S Kamath
    Citation: 12
    Year: 2021
  • Title: Automatic quality enhancement of medical diagnostic scans with deep neural image super-resolution models
    Authors: K Karthik, SS Kamath, SU Kamath
    Citation: 6
    Year: 2020
  • Title: An automated robotic arm: a machine learning approach
    Authors: NSK Rao, NJ Avinash, HR Moorthy, K Karthik, S Rao, S Santosh
    Citation: 5
    Year: 2021
  • Title: Automated view orientation classification for x-ray images using deep neural networks
    Authors: K Karthik, S Kamath
    Citation: 3
    Year: 2021
  • Title: GAN-Based Encoder-Decoder Model for Multi-Label Diagnostic Scan Classification and Automated Radiology Report Generation
    Authors: R Kumar, K Karthik, SS Kamath
    Citation: 3

Siyuan Song | Engineering | Best Researcher Award

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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.

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🌟  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