Jianquan Wang | Industrial Internet | Best Industrial Research Award

Published on 17/06/202517/06/2025 by TOT Awards

Prof. Jianquan Wang | Industrial Internet | Best Industrial Research Award

Director of the Institute of Industrial Internet at University of Science and Technology Beijing, China

Prof. Jianquan Wang is an eminent scholar and Director of the Institute of Industrial Internet at the University of Science and Technology Beijing (USTB). With a PhD in Electrical Engineering from Beijing University of Posts and Telecommunications (BUPT, 2003), he has dedicated over two decades to pioneering research in industrial internet, 5G communication, time-sensitive networking (TSN), and artificial intelligence. Prof. Wang’s impactful work bridges academia and industry, reflected in his leadership of national projects and collaborations with top enterprises like China Unicom and Hebei Steel Group. A Fellow of the China Institute of Communications and member of several national committees, he has over 100 patents and 48 SCI-indexed publications with nearly 1,000 citations. His commitment to advancing smart manufacturing and industrial automation has earned him accolades, including the “Youth Science and Technology Innovation Leader” award.

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Education

Prof. Jianquan Wang completed his doctoral degree in Electrical Engineering at the prestigious Beijing University of Posts and Telecommunications (BUPT) in 2003. His PhD research laid the foundation for his later focus on industrial internet and time-sensitive networking technologies. Upon earning his doctorate, he immediately began postdoctoral research at BUPT, further refining his expertise in networked systems and communications technology. Prof. Wang’s educational journey is marked by a strong emphasis on interdisciplinary learning, blending electrical engineering, network communications, and automation. His solid academic background has empowered him to lead cutting-edge research and shape future innovations in smart manufacturing, cloud-based control systems, and 5G-TSN convergence.

Work Experience

Prof. Wang serves as Director of the Institute of Industrial Internet at USTB, where he leads research, supervises doctoral candidates, and oversees major industrial collaborations. Since completing his postdoc in 2005, he has played a central role in more than 20 national research projects. His professional engagements span work with China Unicom, Pangang Group, and Hebei Steel, where he has led transformative projects on 5G, TSN, and industrial automation. Prof. Wang is a Principal Investigator on multiple government-funded and enterprise-supported initiatives. Additionally, he contributes to national policy as a member of the Strategic Advisory Committee on Industrial Internet (MIIT).

🏆 Awards & Honors

Prof. Jianquan Wang has been widely recognized for his leadership and innovation. His honors include the Youth Science and Technology Innovation Leader award for his trailblazing work in industrial internet and smart manufacturing. As a Fellow of the China Institute of Communications (CIC) and Fellow of the Royal Society of Health (FRSH), he has been acknowledged for his contributions to advancing communication technologies. His membership on national committees, such as the Strategic Advisory Committee on Industrial Internet (MIIT), reflects his standing as a thought leader. He has received institutional accolades for his work in 5G-TSN integration and industrial automation technologies that have directly impacted Chinese industry.

Research Focus

Prof. Wang’s research focuses on the Industrial Internet, integrating 5G, Time-Sensitive Networking (TSN), and cloud-based control systems to enable intelligent manufacturing. His work emphasizes low-latency communication, network reliability, and AI-enhanced industrial task scheduling. His vision bridges the gap between legacy industrial systems and next-generation smart factories. He actively explores 5G-TSN convergence, enabling seamless industrial communication and control. His projects have advanced cloud-based PLC systems, visual perception technologies for metallurgy, and networked control architectures for large-scale industrial processes. Prof. Wang’s applied research has been implemented by major corporations, contributing to China’s industrial modernization.

🛠️ Skills

Prof. Wang possesses deep expertise in 5G technologies, time-sensitive networking, cloud control systems, and AI for industrial automation. His technical skillset spans industrial task scheduling, optical transmission, cloud-based PLC design, and real-time communication systems. He excels in large-scale project management, interdisciplinary collaboration, and technology transfer. As a seasoned trainer, he is skilled at translating complex technologies into actionable solutions for industry partners. Additionally, Prof. Wang has extensive experience in patent drafting and intellectual property strategy, with over 100 patents to his name. His ability to bridge academic research and industrial practice makes him a leader in smart manufacturing innovation.

Conclusion

➡ Prof. (Dr.) Jianquan Wang is highly suitable for the Best Industrial Research Award.

His research record demonstrates the ideal blend of academic rigor, innovation, and direct industrial application that this award seeks to recognize. The scale of his contributions to national projects, number of patents, leadership in collaborative industry initiatives, and technological advancements in industrial internet domains all align with the award’s objectives.

➡ Strengthening international influence and entrepreneurial outputs would further cement his standing as a global industrial research leader, but his current profile already places him among top contenders for this honor.

Publications to Noted

1️⃣ Title:
A 5G-TSN joint resource scheduling algorithm based on optimized deep reinforcement learning model for industrial networks
Authors: (Author names were not listed in your input — likely includes Jianquan Wang and collaborators)
Journal: Ad Hoc Networks
Year: 2025

2️⃣ Title:
Research on delay upper bound analysis based on network calculus for LEO satellite network
Authors: (Author names were not listed — likely includes Jianquan Wang and collaborators)
Journal: Tongxin Xuebao (Journal on Communications)
Year: 2025

3️⃣ Title:
Multimodal Heterogeneous Data Sensing and Communication Integration for CIoT
Authors: (Author names were not listed — likely includes Jianquan Wang and collaborators)
Journal: IEEE Transactions on Consumer Electronics
Year: 2025

4️⃣ Title:
Intelligent Collaboration Mechanism on Computing, Communication and Control for Industrial Networked Automation System
Authors: (Author names were not listed — likely includes Jianquan Wang and collaborators)
Journal: IEEE Internet of Things Journal
Year: 2025

Kishore Debnath | Manufacturing | Best Researcher Award

Published on 14/03/202515/07/2025 by TOT Awards

Dr. Kishore Debnath | Manufacturing | Best Researcher Award

Associate Professor at China Academy of Building Research, China

Dr. Kishore Debnath is a distinguished academic and researcher in the field of mechanical engineering, specializing in advanced manufacturing and materials science. With a strong foundation in engineering research, he has significantly contributed to machining processes, sustainable manufacturing, and industrial automation. He earned his Ph.D. in Mechanical Engineering from the Indian Institute of Technology (IIT) Roorkee and has since been actively engaged in research and teaching. Currently serving as an Associate Professor at the National Institute of Technology (NIT) Meghalaya, Dr. Debnath has played a key role in academic development, research advancement, and administrative leadership. His work focuses on optimizing machining performance, eco-friendly manufacturing solutions, and computational modeling. Over the years, he has received numerous accolades, including the Excellent Research Contribution Award and multiple Best Paper Awards at prestigious conferences. Through his expertise and leadership, Dr. Debnath continues to shape the future of mechanical engineering research and education.

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ORCID

Education

Dr. Kishore Debnath pursued his Ph.D. in Mechanical Engineering from the Indian Institute of Technology (IIT) Roorkee between 2011 and 2015, where he focused on advanced machining processes and material optimization techniques. Prior to this, he completed his M.Tech. in Mechanical Engineering at the National Institute of Technology (NIT) Rourkela (2009-2011), specializing in manufacturing engineering and process optimization. His research during this period was centered on improving machining efficiency and material sustainability. His undergraduate studies were at the National Institute of Technology (NIT) Agartala, where he earned a B.E. in Mechanical Engineering (2004-2008). His education has provided him with a robust technical foundation and a deep understanding of mechanical and industrial processes, allowing him to make significant contributions to academia and the engineering industry.

work Experience

Dr. Kishore Debnath has an extensive teaching and research career, having served in multiple academic positions. He is currently an Associate Professor at NIT Meghalaya (2023–Present), where he leads various research initiatives and academic programs. Previously, he held the role of Assistant Professor (Grade-I) from 2019 to 2023 and Assistant Professor (Grade-II) from 2015 to 2019 at the same institution. His initial role at NIT Meghalaya was as an Assistant Professor (Consolidated Pay) from July to November 2015. In addition to teaching, he has been deeply involved in academic and administrative responsibilities, including serving as the Professor In-Charge of the Centre for International Relations (2024–Present) and Co-ordinator for the Quality Improvement Programme (2024–Present). He has also held key leadership positions such as Head of the Mechanical Engineering Department (2022–2024) and Member of the Senate (2022–2024), playing a significant role in institutional development.

Research Focus

Dr. Kishore Debnath’s research primarily revolves around advanced machining, manufacturing processes, and material science applications. His work in precision machining and surface engineering has led to improved cutting efficiency and wear resistance in industrial applications. He is actively involved in sustainable manufacturing, where he develops eco-friendly and energy-efficient machining techniques. His expertise in computational modeling and AI-driven process optimization allows for better prediction and control of machining operations. Additionally, he has contributed to industrial automation and the integration of smart manufacturing technologies under Industry 4.0. His research on composite and high-performance materials has applications in the aerospace and automotive industries. Through his innovative contributions, he continues to push the boundaries of manufacturing efficiency and sustainability, helping industries transition to more advanced and environmentally friendly practices.

Awards & Honors🏆

Dr. Kishore Debnath has received numerous awards and honors for his contributions to research and academia. He was honored with the Excellent Research Contribution Award (Young Faculty) for 2022-23 and 2018-19 at NIT Meghalaya. He has also won Best Paper Awards at prestigious conferences, including the 2nd International Conference on Recent Innovations & Developments in Mechanical Engineering (ICRIDME 2024) and the International Conference on Industrial and Manufacturing Systems (CIMS-2020). Additionally, he has been awarded international travel grants, including CSIR-funded financial assistance to attend IMMT-2019 in Dubai, UAE, and SERB-DST-funded support for ISGMA-2014 in South Korea. His research has been recognized with multiple Best Poster Presentation Awards, further solidifying his reputation as a leading researcher in his field. He also secured the Graduate Aptitude Test in Engineering (GATE) Scholarship during his M.Tech. and Ph.D. studies, demonstrating his academic excellence from an early stage.

Conclusion

Publications to Noted

Drilling characteristics of sisal fiber-reinforced epoxy and polypropylene composites

📖 Materials and Manufacturing Processes 29 (11-12), 1401-1409

👥 Authors: K. Debnath, I. Singh, A. Dvivedi

🔢 Citations: 136

📅 Year: 2014

Hole making in natural fiber-reinforced polylactic acid laminates: an experimental investigation

📖 Journal of Thermoplastic Composite Materials 30 (1), 30-46

👥 Authors: P.K. Bajpai, K. Debnath, I. Singh

🔢 Citations: 123

📅 Year: 2017

Rotary mode ultrasonic drilling of glass fiber-reinforced epoxy laminates

📖 Journal of Composite Materials 49 (8), 949-963

👥 Authors: K. Debnath, I. Singh, A. Dvivedi

🔢 Citations: 82

📅 Year: 2015

Experimental investigations on drilling of lignocellulosic fiber-reinforced composite laminates

📖 Journal of Manufacturing Processes 34, 51-61

👥 Authors: M.R. Choudhury, M.S. Srinivas, K. Debnath

🔢 Citations: 76

📅 Year: 2018

Low-frequency modulation-assisted drilling of carbon-epoxy composite laminates

📖 Journal of Manufacturing Processes 25, 262-273

👥 Authors: K. Debnath, I. Singh

🔢 Citations: 58

📅 Year: 2017

On the analysis of force during secondary processing of natural fiber-reinforced composite laminates

📖 Polymer Composites 38 (1), 164-174

👥 Authors: K. Debnath, I. Singh, A. Dvivedi

🔢 Citations: 47

📅 Year: 2017

A new approach to control the delamination and thrust force during drilling of polymer nanocomposites reinforced by graphene oxide/carbon fiber

📖 Composite Structures 253, 112786

👥 Authors: J. Kumar, R.K. Verma, K. Debnath

🔢 Citations: 45

📅 Year: 2020

A review of the research and advances in electromagnetic joining of fiber-reinforced thermoplastic composites

📖 Polymer Engineering & Science 59 (10), 1965-1985

👥 Authors: M.R. Choudhury, K. Debnath

🔢 Citations: 43

📅 Year: 2019

Drilling of metal matrix composites: Experimental and finite element analysis

📖 Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

👥 Authors: V.K. Doomra, K. Debnath, I. Singh

🔢 Citations: 42

📅 Year: 2015

Fabrication methods of metal matrix composites (MMCs)

📖 Materials Today: Proceedings 46, 6840-6846

👥 Authors: A. Kumar, O. Vichare, K. Debnath, M. Paswan

🔢 Citations: 40

📅 Year: 2021

Detection of local defect resonance frequencies using bicoherence analysis

📖 Journal of Sound and Vibration 443, 703-716

👥 Authors: S. Roy, T. Bose, K. Debnath

🔢 Citations: 39

📅 Year: 2019

Cecilia Toledo Hernandez | Industrial | Best Researcher Award

Published on 26/02/202526/02/2025 by TOT Awards

Assoc. Prof. Dr. Cecilia Toledo Hernandez | Industrial | Best Researcher

Professor at Federal Fluminense University, Brazil

Cecilia Toledo Hernández is a distinguished university professor at the Federal Fluminense University (UFF), specializing in Industrial and Production Engineering. She holds a PhD in Mechanical Engineering and has extensive experience in research areas such as Circular Economy, Reverse Logistics, and Computational Simulation. As a leader of the “Industrial Engineering Research Laboratory,” she actively contributes to research on sustainable industrial practices. Cecilia is also an associate reviewer for the RASI Journal and a faculty advisor for junior enterprise projects. Her commitment to education and innovation has earned her an honorable mention for Master’s supervision by the Engineering Council. With a career spanning academia and industry collaboration, she has led various multidisciplinary research projects, particularly in decision-making methodologies and sustainability in logistics. Through her work, she aims to bridge the gap between academia and real-world applications, fostering innovative solutions for industrial and environmental challenges.

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Education

Cecilia Toledo Hernández holds a Bachelor’s degree in Industrial Engineering, a Master’s degree in Human Resources Management, and a PhD in Mechanical Engineering, specializing in Production Engineering. Her academic journey has been driven by a passion for optimizing industrial processes and sustainable logistics. Throughout her studies, she developed expertise in multi-criteria decision-making, computational modeling, and environmental management. Her PhD research focused on integrating reverse logistics into corporate performance metrics, a field she continues to explore in her academic career. As a professor, she actively engages in interdisciplinary education, teaching at the Master’s level in Production Engineering, Business Administration, and Computational Modeling. Cecilia’s educational background combines engineering principles with management strategies, allowing her to contribute significantly to industrial sustainability. Her strong foundation in both technical and managerial aspects enables her to develop innovative research methodologies that benefit academia, industry, and policymaking in Brazil and beyond.

work Experience

Cecilia Toledo Hernández is an Associate Professor in the Department of Production Engineering at UFF, where she teaches and supervises students in Master’s programs. She has led multiple research projects focusing on decision support systems, sustainability, and logistics optimization. She collaborates closely with industry, notably through a research partnership between UFF and MAN Latin America, fostering university-business interactions. As coordinator of key projects such as “Sustainability and Reverse Logistics” and “Computational Modeling for Decision-Making,” she integrates theoretical and practical approaches to improve industrial processes. Cecilia has also served as a consultant on supply chain and logistics strategies for various organizations. Her expertise in production systems has positioned her as a sought-after academic mentor and industry advisor. She actively contributes to scientific literature, editorial boards, and peer-review processes, reinforcing her role as a leader in engineering education and sustainable industrial practices.

Research Focus

Cecilia Toledo Hernández’s research spans Circular Economy, Reverse Logistics, and Computational Modeling applied to decision-making. She explores how sustainability can be integrated into industrial processes to improve efficiency and reduce environmental impact. Her studies on multi-criteria decision-making assist businesses in optimizing logistics and supply chain strategies. Cecilia also investigates the role of Information and Communication Technology (ICT) in environmental management, helping organizations implement smarter and greener solutions. She leads projects on computational modeling for decision support, ensuring that industries adopt data-driven methodologies for strategic planning. A significant part of her research focuses on the automotive and manufacturing sectors, identifying best practices for sustainable operations. As a researcher and mentor, she actively collaborates with students and professionals, bridging academic research with real-world industry needs. Her contributions have shaped policies on sustainable production and supply chain management in Brazil and beyond.

Awards & Honors🏆

Dr. Cecilia Toledo Hernández has received numerous accolades for her contributions to engineering research and education. She was awarded an Honorable Mention by the Engineering Council for her exceptional Master’s supervision at UFF. Her pioneering research in Circular Economy and Reverse Logistics has been recognized in international conferences and symposiums. She has been a key contributor to industry-academic collaborations, earning commendations for her work with MAN Latin America in developing innovative production management solutions. As a faculty advisor for junior enterprise projects, she has played a crucial role in mentoring future industry leaders, leading to recognition from student organizations. Her publications, patents, and consultancy projects have positioned her as a thought leader in her field. In addition, her work in multi-criteria decision-making and computational modeling has been acknowledged through invitations as a guest speaker and journal reviewer for esteemed engineering publications.

Skills 🧠

Dr. Cecilia Toledo Hernández is highly skilled in Production Engineering, Industrial Logistics, and Supply Chain Optimization. She is an expert in Reverse Logistics and Circular Economy, developing sustainable strategies for various industries. Her proficiency in Computational Modeling and Multi-Criteria Decision-Making allows her to design advanced decision-support tools. She possesses strong analytical skills, enabling her to conduct data-driven research on supply chain efficiency and corporate sustainability. As a professor, she has exceptional teaching and mentoring abilities, guiding students in Master’s and PhD programs. She is also an adept researcher and industry consultant, bridging the gap between academia and practical applications. Dr. Hernández has extensive experience in journal editing and peer review, contributing to academic publishing. Her leadership skills shine through in research project coordination and industry collaborations, ensuring impactful results in engineering and environmental sustainability.

Conclusion

Publications to Noted

Reverse Logistics and the Circular Economy: A Study before and after the Implementation of the National Solid Waste Policy in Brazil”

Authors: Elias Carlos Aguirre Rodríguez, Cecilia Toledo Hernández, Eliane Y. Aguirre-Rodríguez, Ana Flávia da Silva, Francisco Antonio Forcellini

Publication Date: August 2, 2024

Journal: Recycling

Citations: As of now, specific citation counts are not available.

“Integração de ferramentas de auxílio a tomada de decisão para a avaliação estratégica em empresa de prestação de serviços”

Authors: Allyce Vitorino Gonçalves, Cecilia Toledo Hernández, Eliane da Silva Christo, Glaudiane Lilian de Almeida, Kelly Alonso Costa

Publication Date: April 25, 2024

Journal: Exacta