Shagufta Riaz | Engineering | Women Researcher Award

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Dr. Shagufta Riaz | Engineering | Women Researcher Award

Dr. Shagufta Riaz, National Textile University, Pakistan 

Dr. Shagufta Riaz is an Assistant Professor in the Department of Textile Engineering at National Textile University, Faisalabad, Pakistan. With a Ph.D. in Textile Engineering, she specializes in functional textiles, focusing on the use of nanomaterials for textile development. Dr. Riaz has authored several influential publications and has completed various high-impact research projects. She has worked as a researcher at the Wilson School of Textiles in the USA and is actively involved in advancing textile innovations. A member of prestigious international organizations like the Textile Institute and the Pakistan Engineering Council, Dr. Riaz is committed to sustainable textile solutions.

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Suitability of Dr. Shagufta Riaz for the Research for Women Researcher Award

Dr. Shagufta Riaz is a highly accomplished researcher in textile engineering, specializing in functional textiles and nanotechnology applications. Her extensive academic background, including a Ph.D. in Textile Engineering and international research experience at the Wilson School of Textiles, NCSU, USA, demonstrates her expertise in the field. She has significantly contributed to the advancement of sustainable textile innovations, textile finishing, and the development of nanomaterials for multifunctional textile applications. As an HEC Ph.D. Approved Supervisor and a Fellow of the Textile Institute, UK, she has played a crucial role in mentoring young researchers and advancing academic excellence in textile engineering.

Her research portfolio includes several high-impact projects funded at both national and international levels, focusing on crucial areas such as RF-shielding maternity garments, recycling of cellulosic waste for graphene quantum dots, and sustainable bio-processing in textile manufacturing. Additionally, her collaborations with industry highlight her ability to bridge the gap between academic research and practical industrial applications. Notable projects include the development of antibacterial medical gauze, pesticide-resistant clothing, and UV-shielding protective garments, which showcase her commitment to improving textile functionality for real-world challenges.

🎓 Education

Dr. Shagufta Riaz holds a Ph.D. in Textile Engineering from National Textile University, Faisalabad, Pakistan, where she also completed her M.Sc. in Textile Advanced Materials Engineering and B.Sc. in Textile Engineering with distinctions. She further honed her skills as a researcher at the Wilson School of Textiles, North Carolina State University, USA. This educational foundation, coupled with her hands-on research experience, forms the backbone of her expertise in nanotechnology, textile finishing, and sustainable textile innovations.

💼 Professional Experience

Dr. Shagufta Riaz is an Assistant Professor at National Textile University, Faisalabad. She has led and collaborated on multiple research projects, including those in partnership with international institutions and the textile industry. Her professional experience spans research in textile engineering, focusing on nanomaterials and sustainable solutions. Dr. Riaz has consulted on industry projects to optimize processes in textile production, such as designing protective garments and improving fabric properties. Her role as a Ph.D. supervisor and her recognition as a Fellow of the Textile Institute, UK, highlight her significant contribution to academia and industry.

🏅 Awards and Recognition

Dr. Shagufta Riaz’s academic excellence is evidenced by her recognition as a Fellow of the Textile Institute, UK, and a Lifetime Member of the Pakistan Engineering Council. She has received multiple accolades for her contributions to textile engineering, including a significant number of awards for her research in nanotechnology and textile innovations. Her work, recognized internationally, is reflected in numerous high-impact publications and the completion of major research and consultancy projects in collaboration with the textile industry.

🌍 Research Skills On Engineering

Dr. Riaz is an expert in nanotechnology applications in textile engineering, particularly for the development of multifunctional textiles. Her research focuses on the integration of nanomaterials to enhance textile properties such as antimicrobial, UV resistance, and electrical shielding. She has completed several research projects under government and industry funding, contributing valuable advancements in sustainable textiles, functional finishes, and eco-friendly processes. Dr. Riaz’s skills extend to guiding doctoral research and publishing in prestigious journals, marking her as a leading researcher in textile engineering.

📖 Publication Top Notes

  • Fabrication of robust multifaceted textiles by application of functionalized TiO₂ nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus
    • Citations: 95
    • Year: 2019

  • Functional finishing and coloration of textiles with nanomaterials

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Rehman, A. Javid, K. Iqbal, …
    • Citations: 77
    • Year: 2018

  • Modification of silica nanoparticles to develop highly durable superhydrophobic and antibacterial cotton fabrics

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain
    • Citations: 58
    • Year: 2019

  • Electrospun nanofiber-based viroblock/ZnO/PAN hybrid antiviral nanocomposite for personal protective applications

    • Authors: A. Salam, T. Hassan, T. Jabri, S. Riaz, A. Khan, K.M. Iqbal, S. Khan, M. Wasim, …
    • Citations: 41
    • Year: 2021

  • Cationization of TiO₂ nanoparticles to develop highly durable multifunctional cotton fabric

    • Authors: S. Riaz, M. Ashraf, H. Aziz, A. Younus, M. Umair, A. Salam, K. Iqbal, …
    • Citations: 31
    • Year: 2022

  • Layer by layer deposition of PEDOT, silver and copper to develop durable, flexible, and EMI shielding and antibacterial textiles

    • Authors: S. Riaz, S. Naz, A. Younus, A. Javid, S. Akram, A. Nosheen, M. Ashraf
    • Citations: 26
    • Year: 2022

  • Multifunctional formaldehyde-free finishing of cotton by using metal oxide nanoparticles and eco-friendly cross-linkers

    • Authors: N. Sarwar, M. Ashraf, M. Mohsin, A. Rehman, A. Younus, A. Javid, K. Iqbal, …
    • Citations: 24
    • Year: 2019

  • In situ development and application of natural coatings on non-absorbable sutures to reduce incision site infections

    • Authors: R. Masood, T. Hussain, M. Umar, Azeemullah, T. Areeb, S. Riaz
    • Citations: 21
    • Year: 2017

  • Selection and Optimization of Silane Coupling Agents to Develop Durable Functional Cotton Fabrics Using TiO₂ Nanoparticles

    • Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus, M. Raza, A. Nosheen
    • Citations: 20
    • Year: 2021

  • Simultaneous fixation of wrinkle-free finish and reactive dye on cotton using response surface methodology

    • Authors: S. Abid, T. Hussain, A. Nazir, Z.A. Raza, A. Siddique, A. Azeem, S. Riaz
    • Citations: 16
    • Year: 2018

Miaomiao Ma | Engineering | Best Researcher Award

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Prof. Miaomiao Ma | Engineering | Best Researcher Award

Prof. Miaomiao Ma, north china electric power university, China

Dr. Miaomiao Ma, born in February 1982, is a distinguished Chinese researcher specializing in model predictive control, optimal and robust control, and nonlinear control. Currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University, Beijing, he has made significant contributions to renewable power systems and mechatronic systems, particularly in automotive applications. With a strong foundation in control engineering, he has been actively involved in high-impact research and academic collaborations. Dr. Ma has held academic positions in China and Germany, including postdoctoral research at the University of Stuttgart under Prof. Frank Allgöwer. His research focuses on advanced control strategies for energy-efficient and resilient engineering systems. As an accomplished author, he has published extensively in leading journals and conferences, shaping the future of control theory applications in energy and automation. His expertise continues to influence both academia and industry.

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Suitability for the Research for Best Researcher Award – Miaomiao Ma

Dr. Miaomiao Ma is an accomplished researcher in control theory and engineering, particularly in model predictive control, optimal and robust control, and their applications in renewable power and mechatronic systems. His academic journey, from earning a Ph.D. from Jilin University to holding a prominent position as an Associate Professor at North China Electric Power University, highlights a strong foundation in both theoretical and applied research. His international exposure, including post-doctoral research at the University of Stuttgart under the supervision of Frank Allgöwer, further underscores his expertise in control engineering.

Dr. Ma has made significant contributions to the field, as evidenced by his extensive publication record in high-impact journals, including IEEE Transactions on Industrial Electronics, IET Renewable Power Generation, and ISA Transactions. His research primarily focuses on control strategies for micro-grids, wind energy systems, and power system stability, all of which are critical areas in modern energy and automation technologies. His innovative approaches, such as distributed moving horizon control and predictive load frequency control, have practical applications in optimizing energy efficiency and system stability. Additionally, his leadership in securing competitive research grants, including those from the Natural Science Foundation of China, further establishes his credibility as a leading researcher in his field.

🎓 Education 

Dr. Miaomiao Ma earned his Ph.D. in Control Theory and Engineering from Jilin University in 2009, where he developed a disturbance attenuation control scheme for constrained systems under the guidance of Prof. Hong Chen. Prior to that, he completed his Master of Science in Control Theory and Engineering at Jilin University in 2006, focusing on robust control of active suspensions using LMI optimization. His undergraduate studies in Automation, also at Jilin University, provided him with a strong technical foundation in control engineering. Throughout his academic journey, Dr. Ma has consistently demonstrated excellence in control systems, optimization techniques, and predictive control methodologies. His educational background has played a pivotal role in shaping his research trajectory, leading to innovative contributions in model predictive control, nonlinear control strategies, and their applications in renewable energy and automotive systems. His commitment to education and research continues to drive advancements in control engineering.

💼 Professional Experience

Dr. Miaomiao Ma has accumulated extensive academic and research experience, currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University (NCEPU), since January 2015. Prior to this, he was an Assistant Professor at NCEPU from 2009 to 2014. His international exposure includes a postdoctoral research tenure at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany, under Prof. Frank Allgöwer from 2012 to 2013. Additionally, he was a visiting scholar at the same institute in 2007 and 2006. His professional journey has been marked by cutting-edge research in predictive and robust control, contributing significantly to renewable energy integration, micro-grid systems, and automotive control applications. His collaborative efforts with international researchers have strengthened global advancements in power systems and control engineering, solidifying his reputation as a leading figure in his field.

🏅 Awards and Recognition 

Dr. Miaomiao Ma’s contributions to control engineering and renewable energy systems have earned him several prestigious recognitions. He has received multiple research excellence awards for his work in model predictive control and distributed optimization. His papers have been widely cited, earning accolades in high-impact journals such as IEEE Transactions on Industrial Electronics and IET Renewable Power Generation. He has also been an invited speaker at international conferences, sharing insights on predictive control applications. His research projects have been supported by national and international funding agencies, reinforcing his expertise in control systems. Furthermore, Dr. Ma has been recognized as a leading scholar in his field, contributing to advancements in renewable energy integration, micro-grid optimization, and robust control mechanisms. His outstanding research achievements continue to inspire innovation and development in engineering applications worldwide.

🌍 Research Skill On Engineering

Dr. Miaomiao Ma possesses extensive research expertise in model predictive control, nonlinear control, and robust control strategies, particularly in renewable energy and automotive systems. His work focuses on optimizing micro-grid performance through distributed predictive control, ensuring stability in multi-area power systems. He specializes in H-infinity control, disturbance attenuation, and constrained optimization techniques, enhancing control strategies in energy systems. Dr. Ma’s interdisciplinary approach integrates control theory with mechatronics, resulting in innovative solutions for energy efficiency. His research methodologies involve algorithm development, simulation modeling, and real-time control implementations. With a strong publication record in renowned journals and conferences, he has contributed to shaping advanced control strategies for sustainable engineering. His collaborative projects with international researchers and institutions further demonstrate his ability to drive impactful research in modern control engineering applications.

📖 Publication Top Notes

  • Title: Distributed model predictive load frequency control of the multi-area power system after deregulation
    Authors: M Ma, C Zhang, X Liu, H Chen
    Citations: 164
    Year: 2016
    Journal: IEEE Transactions on Industrial Electronics
  • Title: Distributed model predictive load frequency control of multi-area interconnected power system
    Authors: M Ma, H Chen, X Liu, F Allgöwer
    Citations: 134
    Year: 2014
    Journal: International Journal of Electrical Power & Energy Systems
  • Title: Moving Horizon Tracking Control of Wheeled Mobile Robots With Actuator Saturation
    Authors: H Chen, MM Ma, H Wang, ZY Liu, ZX Cai
    Citations: 99
    Year: 2009
    Journal: IEEE Transactions on Control Systems Technology
  • Title: LFC for multi‐area interconnected power system concerning wind turbines based on DMPC
    Authors: M Ma, X Liu, C Zhang
    Citations: 74
    Year: 2017
    Journal: IET Generation, Transmission & Distribution
  • Title: Disturbance attenuation control of active suspension with non-linear actuator dynamics
    Authors: MM Ma, H Chen
    Citations: 58
    Year: 2011
    Journal: IET Control Theory & Applications
  • Title: Power transfer characteristics in fluctuation partition algorithm for wind speed and its application to wind power forecasting
    Authors: M Yang, D Wang, C Xu, B Dai, M Ma, X Su
    Citations: 34
    Year: 2023
    Journal: Renewable Energy
  • Title: Maximum power point tracking and voltage regulation of two-stage grid-tied PV system based on model predictive control
    Authors: M Ma, X Liu, KY Lee
    Citations: 31
    Year: 2020
    Journal: Energies
  • Title: Constrained H₂ control of active suspensions using LMI optimization
    Authors: M Ma, H Chen
    Citations: 28
    Year: 2006
    Conference: Chinese Control Conference
  • Title: Robust MPC for the constrained system with polytopic uncertainty
    Authors: X Liu, S Feng, M Ma
    Citations: 23
    Year: 2012
    Journal: International Journal of Systems Science
  • Title: Moving horizon ℋ∞ control of variable speed wind turbines with actuator saturation
    Authors: M Ma, H Chen, X Liu, F Allgöwer
    Citations: 20
    Year: 2014
    Journal: IET Renewable Power Generation

Kamaraj K | Engineering | Best Researcher Award

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Dr. Kamaraj K | Engineering | Best Researcher Award

Dr. Kamaraj K, KPR Institute of Engineering and Technology, India

Dr. Kamaraj K, an accomplished academic and researcher, holds a Ph.D. in Information and Communication Engineering from Anna University (2021). With over 17 years of academic experience, he is currently an Associate Professor and Head of the Department of Information Technology at KPR Institute of Engineering and Technology, Coimbatore. He has a strong background in software engineering, testing, and agile methodologies, alongside expertise in Extended Reality. Dr. Kamaraj is passionate about integrating technology with real-world applications, emphasizing teamwork and continuous learning. His leadership roles include overseeing ranking, accreditation activities, and Sustainable Development Goals (SDG) initiatives. Dr. Kamaraj’s contributions extend to mentoring and advancing autonomous academic processes. His professional journey is marked by dedication, innovation, and a focus on impactful research, making him a valuable figure in engineering education and research.

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🌟   Summary of Suitability for the Research for Best Researcher Award

Dr. Kamaraj K is a highly accomplished academic professional with a strong foundation in software engineering, software testing, agile methodologies, and extended reality. With over 17.2 years of academic experience, he has consistently demonstrated leadership, innovation, and a commitment to advancing knowledge in his research areas. As an Associate Professor and Head of the Department of Information Technology at KPR Institute of Engineering and Technology, Dr. Kamaraj has contributed significantly to academic and administrative excellence. His responsibilities have encompassed managing accreditation processes, autonomous proceedings, and sustainable development goals (SDG) initiatives, showcasing his multifaceted expertise and organizational capabilities.

Dr. Kamaraj’s impressive academic qualifications, including a Ph.D. in Information and Communication Engineering from Anna University, underline his deep understanding of complex research topics. He has made meaningful contributions to academic literature, publishing papers on strategies for automated test oracle and test case generation, which highlight his ability to address practical challenges in software testing. His professional certifications, such as MTA, IBM DB2-302, and OCA, demonstrate his dedication to continuous learning and mastery of modern tools and technologies.

🎓 Education 

Dr. Kamaraj K’s educational journey is distinguished by academic excellence and a focus on cutting-edge engineering fields. He earned his Ph.D. in Information and Communication Engineering from Anna University in 2021, showcasing his dedication to advanced research in software engineering and testing. His M.Tech. in Software Engineering from Bharathidhasan University (2007) further honed his technical and problem-solving skills, laying a strong foundation for his career. Dr. Kamaraj also holds a B.Tech. in Information Technology from Coimbatore Institute of Engineering and Technology, affiliated with Anna University, which he completed in 2005. These qualifications reflect his commitment to academic rigor and innovation in engineering. His education has equipped him with the knowledge and expertise to lead projects, mentor students, and contribute to advancements in engineering and technology.

💼 Professional Experience 

Dr. Kamaraj K has an extensive career spanning over 17 years in academia, with significant leadership roles in prestigious institutions. Since 2017, he has been serving as Associate Professor and Head of the Department of Information Technology at KPR Institute of Engineering and Technology, Coimbatore. His responsibilities include managing ranking and accreditation activities, mentoring teams, and advancing autonomous academic processes. Prior to this, he worked at Dhanalakshmi Srinivasan College of Engineering, Coimbatore, as Assistant Professor and Department Head from 2012 to 2017. From 2007 to 2012, he contributed to SRM University, Chennai, as Assistant Professor, coordinating academic activities, accreditation processes, and extracurricular events. Dr. Kamaraj’s professional experience showcases his expertise in academic leadership, curriculum development, and student mentorship, underscoring his dedication to fostering excellence in engineering education.

🏅 Awards and Recognition

Dr. Kamaraj K’s illustrious career is marked by numerous recognitions for his academic and professional excellence. He has been acknowledged for his leadership in managing institutional rankings and accreditation activities, including QS I-GAUGE, THE Impact Ranking, and NIRF. Under his guidance, the Department of Information Technology at KPR Institute of Engineering and Technology has achieved significant milestones. Dr. Kamaraj’s contributions to autonomous academic processes and his role in advancing Sustainable Development Goals (SDGs) have been widely recognized. He is also a certified professional in various technical domains, holding certifications such as MTA in Database Management, IBM DB2-302, and Oracle Certified Associate (OCA). His dedication to quality education and impactful research has earned him a reputation as a forward-thinking academic leader.

🌍 Research Focus and Skills On Engineering

Dr. Kamaraj K’s research expertise lies in software engineering, with a focus on software testing, agile methodologies, and extended reality. He is passionate about applying innovative technologies to solve real-world challenges, emphasizing the integration of theory and practice. Dr. Kamaraj is skilled in automated test oracle strategies, test case generation, and reduction techniques, as reflected in his published works. His technical proficiency extends to database management systems, manual testing, and programming, supported by certifications in MTA, IBM DB2, and ISTQB. As a researcher and academic leader, he is dedicated to advancing knowledge in his field through continuous learning and collaboration. Dr. Kamaraj’s ability to mentor students, lead projects, and contribute to impactful research highlights his commitment to driving innovation in engineering and technology.

📖 Publication Top Notes

  1. Title: A Hybridized Artificial Neural Network for Automated Software Test Oracle
    Authors: R.M. K. Kamaraj, B. Lanitha, S. Karthic, P. N. Senthil Prakash
    Journal: Computer Systems Science and Engineering, 45 (2), 1837-1850
    Citations: 12
    Year: 2022
  2. Title: A weight optimized artificial neural network for automated software test oracle
    Authors: K. Kamaraj, C. Arvind, K. Srihari
    Journal: Soft Computing, 24 (17), 13501-13511
    Citations: 9
    Year: 2020
  3. Title: Improved beetle swarm optimization algorithm for energy efficient virtual machine consolidation on cloud environment
    Authors: H. Bhagavathi, S. Rathinavelayatham, K. Shanmugaiah, K. Kanagaraj, …
    Journal: Concurrency and Computation: Practice and Experience, 34 (10), e6828
    Citations: 8
    Year: 2022
  4. Title: Intelligent fuzzy edge computing for real-time decision making in IoT-based digital twin environments
    Authors: K. Prasath, N. Arun, A. Saravanan, B. Kamaraj
    Journal: Journal of Intelligent & Fuzzy Systems, 1-12
    Citations: 1
    Year: 2023
  5. Title: Multiobjective Gannet Dung Beetle Optimization for routing in IoT-WSN
    Authors: S. Sangeetha, K. Kanagaraj, N. Prasath, S. Saradha
    Journal: Peer-to-Peer Networking and Applications, 1-21
    Citations: Not yet available
    Year: 2024
  6. Title: Soybean Leaf Disease Classification using Enhanced Densenet121
    Authors: V. Yogabalajee, K. Sundaram, K. Kanagaraj
    Conference: 2024 10th International Conference on Advanced Computing and Communication
    Citations: Not yet available
    Year: 2024
  7. Title: Meeting Recap Automation: Leveraging NLP and Pretrained Models for Effortless Summaries
    Authors: G.D.P. Kamaraj, K. Dheepakh Bala, T. Divya, S. P.
    Journal: International Journal of Advance Computational Engineering and Networking
    Citations: Not yet available
    Year: 2024
  8. Title: Prediction of Lung Infections with Deep Learning Techniques: A Systematic Review
    Authors: V. Thangamuthu, K. Kamaraj, J.D.K. Hezekiah
    Conference: 2023 3rd International Conference on Innovative Mechanisms for Industry
    Citations: Not yet available
    Year: 2023
  9. Title: Data driven probabilistic detection of fake news using advanced machine learning algorithms
    Authors: K. Kamaraj, R. Giri, S. Dhanush, S. Gokul
    Journal: AIP Conference Proceedings, 2764 (1)
    Citations: Not yet available
    Year: 2023
  10. Title: Speech Based Emotion Recognition System
    Authors: D.K.K. Sri Murugharaj B.R., Shakthy B., Sabari L.
    Journal: International Journal of Engineering Technology and Management Sciences, 7 (1)
    Citations: Not yet available
    Year: 2023

Praveen Sankarasubramanian | Engineering | Best Researcher Award

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Dr. Praveen Sankarasubramanian | Engineering | Best Researcher Award

Dr. Praveen Sankarasubramanian, RMD Research labs, India

Dr. Praveen Sankarasubramanian is a distinguished technologist and researcher with over 13 years of experience in software development, AI, cloud computing, and industrial safety. Currently, he serves as a Senior Software Developer at Pearson India Education Services, specializing in Java, Spring Boot, and AWS Cloud. Dr. Praveen is also the founder of RMD Research Labs, focusing on cutting-edge research in AI, NLP, and safety technologies. His academic expertise is complemented by a Ph.D. in Computer Science and Engineering from VELS University, an M.Tech. in Software Systems from Birla Institute of Technology and Science, and multiple certifications. Dr. Praveen has developed innovative solutions in various domains, including AI-driven safety mechanisms, cloud platforms, and personalized learning systems. His leadership, mentorship, and continuous drive for innovation have made a significant impact on both academic and industry landscapes.

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🎓Education:

Dr. Praveen Sankarasubramanian’s academic journey reflects his dedication to excellence in technology and engineering. He earned a Ph.D. in Computer Science and Engineering from VELS University (March 2018 – August 2023), where he focused on AI, NLP, and cloud-based technologies. His M.Tech. in Software Systems from Birla Institute of Technology and Science, Pilani (2015-2017) provided a solid foundation in advanced software development techniques. Further expanding his expertise, Dr. Praveen completed an Advanced Diploma in Industrial Safety from Bharat Sevak Samaj (2017-2018). Additionally, he pursued a Post Graduate Program in Business Administration with a focus on operations from Symbiosis (2012-2014). His academic background equips him with a diverse skill set, enabling him to tackle complex problems in software engineering, AI, and industrial safety. This foundation has played a key role in his successful integration of theoretical knowledge with practical solutions.

💼Professional Experience:

Dr. Praveen Sankarasubramanian has extensive professional experience, having held leadership roles in major global tech companies. Currently, he is a Senior Software Developer at Pearson India Education Services, where he focuses on cutting-edge technologies such as Java, AWS Cloud, and Spring Boot. Before this, Dr. Praveen was a Senior Software Engineer at Cognizant, where he managed multiple projects in personalized learning and analytics. He oversaw a cross-functional team of 48 members and led seven parallel projects, successfully meeting organizational and project goals. Dr. Praveen’s experience also spans roles at Software AG, GlobalLogic, and 8K Miles Software Services, where he developed cloud-based systems and advanced data analytics solutions. As the founder of RMD Research Labs, he continues to lead research projects in AI and NLP. His career has consistently showcased his ability to merge leadership with technical innovation to drive impactful solutions in both academia and industry.

🔬Research Skills:

Dr. Praveen Sankarasubramanian possesses a diverse and highly advanced skill set in research, combining expertise in artificial intelligence (AI), natural language processing (NLP), machine learning (ML), cloud computing, and industrial safety. His research work spans several impactful areas, such as developing AI-driven safety systems, optimizing cloud platforms, and advancing personalized learning solutions in education technology. Dr. Praveen has also contributed to bandwidth optimization for video solutions and AI for predictive maintenance. His interdisciplinary approach allows him to apply theoretical research to real-world challenges, resulting in the creation of patents and innovative software solutions. Additionally, he has honed his skills in project management, utilizing Agile, Scrum, and JIRA to lead research teams effectively. Dr. Praveen’s research has not only influenced the tech industry but also shaped academic curricula, through his mentorship and contributions to educational resources such as books and journals for students.

🏆Awards and Recognition:

Dr. Praveen Sankarasubramanian’s dedication to innovation and technology has earned him numerous accolades throughout his career. He holds a patent for a system to monitor and handle liquid sodium leakage and fire accidents using AI, which showcases his contribution to industrial safety. His work on bandwidth optimization for video solutions also demonstrates his innovative approach to solving critical tech challenges. Dr. Praveen’s leadership and expertise in cloud computing, AI, and software development have been widely recognized within the tech industry, especially during his tenure at Pearson India and Cognizant. He has also been recognized for his mentorship, having successfully onboarded and guided numerous associates and students in their professional journeys. As a researcher, his contributions have further been acknowledged in academic circles, making him a trusted mentor for the next generation of engineers. His accolades reflect his commitment to excellence, both as a researcher and as a leader.

📖Publications Titles:

  • A System and Method for Monitoring, Sensing, Analyzing, and Handling the Pre-determined Status of Liquid Metals 📊💡
  • AI-driven Safety Mechanisms for Industrial Accidents 🔥🤖
  • Bandwidth Optimization for Video Solutions in Cloud-Based Applications 🌐📹
  • Predictive Maintenance in Industrial Safety Systems Using Machine Learning 🔧🤖
  • Developing Personalized Learning Solutions in Education Technology 🎓📚
  • Cloud Architecture for Scalable SaaS Platforms ☁️💻

🌟Conclusion:

Dr. Praveen Sankarasubramanian is a highly qualified and innovative researcher whose contributions to AI, cloud computing, and industrial safety have made a significant impact. His ability to blend academic knowledge with practical solutions, demonstrated through patents and cutting-edge technologies, highlights his research excellence. With over 13 years of experience, he has successfully led teams, managed complex projects, and mentored the next generation of engineers. Dr. Praveen’s leadership, technical expertise, and dedication to continuous innovation make him a deserving candidate for the Research for Best Researcher Award, marking him as a pioneer in his field.

Top Notable Publications

  • 👤 Enhancing precision in agriculture: A smart predictive model for optimal sensor selection through IoT integration
    • Authors: Sankarasubramanian, P.
    • Citations: 0 🌟
    • Year: 2025 🎓
    • Journal: Smart Agricultural Technology 📖
  • 👤 An efficient crack detection and leakage monitoring in liquid metal pipelines using a novel BRetN and TCK-LSTM techniques
    • Authors: Sankarasubramanian, P.
    • Citations: 0 🌟
    • Year: 2024 🎓
    • Journal: Multimedia Tools and Applications 📖
  • 👤 Protection of Hazardous Places in Industries using Machine Learning
    • Authors: Sankarasubramanian, P.
    • Citations: 1 🌟
    • Year: 2023 🎓
    • Conference: 2023 International Conference on Emerging Smart Computing and Informatics (ESCI 2023) 💼
  • 👤 Artificial intelligence-based detection system for hazardous liquid metal fire
    • Authors: Sankarasubramanian, P., Ganesh, E.N.
    • Citations: 1 🌟
    • Year: 2021 🎓
    • Conference: Proceedings of the 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom 2021) 💼
  • 👤 Realtime Pipeline Fire Smoke Detection Using a Lightweight CNN Model
    • Authors: Kumar, V.K.S., Sankarasubramanian, P.
    • Citations: 5 🌟
    • Year: 2021 🎓
    • Conference: Proceedings of the 2021 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT 2021) 💼
  • 👤 IoT based prediction for industrial ecosystem
    • Authors: Sankarasubramanian, P., Ganesh, E.N.
    • Citations: 1 🌟
    • Year: 2019 🎓
    • Journal: International Journal of Engineering and Advanced Technology 📖

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