Lijun Chen | Engineering | Best Researcher Award

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Prof. Lijun Chen | Engineering | Best Researcher Award

Professor at Northeast Electric Power University, China

Professor Lijun Chen is a seasoned academic and applied researcher at Northeast Electric Power University, bringing over three decades of expertise in automation, thermophysical measurement, and power plant monitoring systems. 🚀 With early technical training at Fuji Electric (Japan) and a strong industrial foundation at Dalian Huaying High-Tech Co., he seamlessly bridges theory with real-world application. His scholarly portfolio boasts 50+ journal publications 📚 (with 20+ indexed by EI and others in SCI), and six national invention patents that reflect his innovation-driven mindset. ⚙️ He has led multiple national and provincial projects, combining academic research with industrial consulting to optimize thermal power systems. A Senior Member of the China Metrology Society, his dedication is evident through a career filled with impactful collaborations, cutting-edge research, and enduring contributions to the energy sector. 🔧 His work continues to empower sustainable and efficient energy technologies across China and beyond. 🌏

Professional Profile 

Scopus

🎓 Education

Professor Lijun Chen’s educational journey is deeply rooted in engineering excellence. 🌱 He enhanced his technical knowledge through automation testing training at Fuji Electric, Japan (1991–1992), where he gained exposure to international standards and modern industrial practices. This early international training laid the groundwork for a future in advanced automation and instrumentation. He continued sharpening his skills with hands-on industry experience before entering academia. 📐 His educational pursuits were not just theoretical but focused on practical solutions for real-world problems in power systems. His academic foundation, supplemented by immersive industrial exposure, uniquely positions him as a knowledge leader in thermophysical measurement and energy systems. 🔋 The fusion of global learning and domestic execution in his educational journey symbolizes his balanced and forward-thinking approach to engineering education and research. 📊

👨‍💼 Professional Experience

Professor Chen’s professional voyage is an exemplar of bridging industry with academia. 🏭 From 1995 to 1997, he worked at Dalian Huaying High-Tech Co., developing automation solutions for complex power systems. Following this, from 1997 to 2001, he continued innovating at the Institute of Electronic Engineering Technology, sharpening his expertise in electronic control. Since 2001, he has been a cornerstone of the School of Automation Engineering at Northeast Electric Power University. 🧑‍🏫 There, he has led or collaborated on numerous high-impact projects, integrating research with engineering applications. His leadership in thermal power plant control systems has shaped provincial-level R&D initiatives and academic–industry partnerships. 🧠 His work with national and horizontal industry projects exemplifies how academic insight can directly solve operational challenges in the energy sector. 🔌

🔬 Research Interest

Lijun Chen’s research is centered on cutting-edge thermal measurement and automation in power engineering. 🌡️ His core interests span thermophysical parameter estimation, combustion optimization, and defect detection in high-frequency electromagnetic equipment. 🔎 These focus areas have significant industrial value, particularly in enhancing the efficiency, safety, and reliability of thermal power plants. His work addresses critical challenges in energy management and environmental control, making his innovations especially relevant in the current era of carbon reduction and sustainable engineering. 🌍 Professor Chen’s ability to combine hardware innovation with control algorithms demonstrates his multi-disciplinary reach across automation, electronics, and thermodynamics. His projects often involve both modeling and experimental validation, ensuring practical applicability. 📊 His collaborations with institutes and enterprises are further proof of his commitment to solving industry-grade problems with scientifically sound solutions. ⚛️

🏅 Award and Honor

Throughout his illustrious career, Professor Chen has been recognized with multiple provincial science and technology awards, a testament to the real-world impact of his work. 🏆 His patents—six granted at the national level—underscore his creative contributions to the field of power system automation and thermal engineering. 📜 His consistent participation in government-funded and industry-sponsored projects not only highlights his technical capability but also his leadership in driving research innovation. He is a Senior Member of the China Metrology Society and plays a notable role in the Jilin Province Electrical Engineering Society, reflecting his influence in professional circles. 🤝 His efforts have significantly elevated the performance of thermal power systems, earning him peer recognition and respect. His honors are not just awards—they are reflections of decades of dedicated research, innovation, and service to the field. 🔧💡

📚 Publications Top Note 

1. Title: The Feasibility Study on Pulverized Coal Mass Concentration Measurement in Primary Air of Plant Using Fin Resonant Cavity Sensor
Authors: Hao Xu, Yiguang Yang, Lijun Chen, Hongbin Yu, Junwei Cao
Year: 2024
Type: Conference Paper
Source: IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Citations: 0 (as of the latest data)
Summary:
This study explores the application of a fin resonant cavity sensor to measure the mass concentration of pulverized coal in the primary air system of power plants. The authors designed and experimentally validated a resonant cavity-based sensor for real-time and high-flow environment monitoring. Results indicate the method’s strong potential for improving combustion efficiency and operational safety in thermal power systems.

2. Title: Research on Finite-Time Consensus of Multi-Agent Systems
Authors: Lijun Chen, Yu Zhang, Yuping Li, Linlin Xia
Year: 2019
Type: Journal Article
Source: Journal of Information Processing Systems (JIPS)
DOI: 10.3745/JIPS.01.0039
Citations: 1 (confirmed from source journal; citation count may vary on other platforms)
Summary:
This paper proposes a novel consensus protocol that enables finite-time convergence in second-order multi-agent systems. By incorporating the gradient of a global cost function into the standard consensus model, the authors enhance coordination speed and robustness among agents. Theoretical analysis using Lyapunov functions, homogeneity theory, and graph theory supports the method’s effectiveness. Simulations demonstrate superior performance in leader–follower scenarios.

✅ Conclusion 

In conclusion, Professor Lijun Chen exemplifies the model of a research-driven innovator and dedicated academic. 📘 With a career spanning research, teaching, consultancy, and invention, he has contributed immensely to the advancement of thermal power automation and measurement systems. His ability to transform theoretical concepts into tangible industrial solutions highlights his value as both a scholar and engineer. 🔬 His multi-patented technologies and SCI-indexed publications reflect a commitment to quality, while his work with industry partners showcases practical relevance. With unwavering focus and passion for thermodynamics, automation, and sustainability, Professor Chen continues to shape the future of smart thermal energy systems in China and beyond. 🌱 His legacy is one of bridging knowledge with innovation, inspiring a new generation of researchers and engineers. 🌟

Abdus Sobhan | Internet of Things | Best Researcher Award

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Assist. Prof. Dr. Abdus Sobhan | Internet of Things | Best Researcher Award

Assistant Professor at Alcorn State University, United States

Assist. Prof. Dr. Abdus Sobhan is an Assistant Professor at Alcorn State University, United States, specializing in Agricultural and Food Engineering with a strong focus on the Internet of Things (IoT) applications in smart agriculture and food systems. He earned his Ph.D. from South Dakota State University, where his research integrated biosensors and nanocomposites for intelligent food packaging. Dr. Sobhan’s work lies at the intersection of IoT, sensor technology, and food safety, contributing significantly to real-time monitoring and automation in agri-food systems. He has published extensively in high-impact journals and is recognized for his innovation and scholarly excellence. His outstanding contributions have earned him the Best Researcher Award, reflecting his leadership in advancing smart technologies for sustainable agriculture and food security.

Professional Profile 

Education 🎓

Dr. Abdus Sobhan holds a Ph.D. in Agricultural/Food Engineering from South Dakota State University, USA, awarded in 2021. Prior to his doctoral studies, he earned his M.S. in Food Science from Sangmyung University in Cheonan, South Korea, in 2018. His academic journey began with a B.S. in Food Engineering from Hajee Mohammad Danesh Science and Technology University in Dinajpur, Bangladesh, completed in 2014. This diverse and interdisciplinary educational foundation has equipped him with global perspectives and technical expertise in food systems, sensor technology, and packaging innovation.

Professional Experience 💼

Dr. Sobhan is currently serving as an Assistant Professor of Food Science and Technology at Alcorn State University, USA, since February 2024. Prior to this, he worked as a Postdoctoral Associate at the University of Arkansas (2021–2024), contributing to cutting-edge research in agricultural and biological sciences. His early research experience includes working as a Graduate Research Assistant at South Dakota State University from 2018 to 2021, where he explored biosensors and smart food packaging technologies. His professional roles have demonstrated a steady commitment to research excellence, teaching, and scientific innovation.

Skills and Technical Expertise 🛠️

Dr. Sobhan possesses a diverse set of skills that include biosensor development, electrochemical and nanodevice-based sensing, machine learning integration for real-time food safety, and IoT-enabled smart packaging. His hands-on experience with cold plasma treatment, bioresin development, and non-thermal food preservation technologies reflects his cross-disciplinary approach. Additionally, he has proficiency in academic publishing, peer reviewing, and editorial leadership for reputed journals, further enhancing his scientific communication and research dissemination capabilities.

Awards and Honors 🏅

Dr. Sobhan has received several prestigious awards in recognition of his academic and research excellence. Notably, he was honored with the Best Research Award by MDPI in 2025. He received the International Dean’s Award from South Dakota State University in 2018, as well as the Sangmyung Brilliant Research Scholarship in 2017. From 2016 to 2018, he was also the recipient of the Woojun Education and Cultural Foundation Award, highlighting his consistent performance and contributions to food science research.

Research Focus 🔬

Dr. Sobhan’s research primarily centers on biosensor development and real-time food safety monitoring using smart technologies. His work integrates IoT, electrochemical sensing, and nanotechnology to create next-generation food packaging systems that ensure safety and quality. His secondary research areas include medical and healthcare packaging, non-thermal microbial inactivation methods like cold plasma, and machine learning-enhanced diagnostics. His goal is to revolutionize food safety and public health through innovation in sensor and packaging technologies.

📚 Publications Top Note 

    • Title: Biosensors and biopolymer-based nanocomposites for smart food packaging: Challenges and opportunities
      Citations: 94
      Authors: A. Sobhan, K. Muthukumarappan, L. Wei
      Year: 2021

    • Title: Characterization of nanocellulose and activated carbon nanocomposite films’ biosensing properties for smart packaging
      Citations: 59
      Authors: A. Sobhan, K. Muthukumarappan, Z. Cen, L. Wei
      Year: 2019

    • Title: Development of an activated carbon-based nanocomposite film with antibacterial property for smart food packaging
      Citations: 50
      Authors: A. Sobhan, K. Muthukumarappan, L. Wei, T. Van Den Top, R. Zhou
      Year: 2020

    • Title: A biopolymer-based pH indicator film for visually monitoring beef and fish spoilage
      Citations: 48
      Authors: A. Sobhan, K. Muthukumarappan, L. Wei
      Year: 2021

    • Title: Assessment of a biochar-based controlled release nitrogen fertilizer coated with polylactic acid
      Citations: 47
      Authors: Z. Cen, L. Wei, K. Muthukumarappan, A. Sobhan, R. McDaniel
      Year: 2021

    • Title: Rapid detection of Yersinia enterocolitica using a single–walled carbon nanotube-based biosensor for Kimchi product
      Citations: 47
      Authors: A. Sobhan, J. Lee, M. K. Park, J. H. Oh
      Year: 2019

    • Title: Single walled carbon nanotube based biosensor for detection of peanut allergy-inducing protein Ara h1
      Citations: 43
      Authors: A. Sobhan, J. H. Oh, M. K. Park, S. W. Kim, C. Park, J. Lee
      Year: 2018

    • Title: Enzymatic synthesis of formate ester through immobilized lipase and its reuse
      Citations: 42
      Authors: Y. Baek, J. Lee, J. Son, T. Lee, A. Sobhan, J. Lee, S. M. Koo, W. H. Shin, J. M. Oh, et al.
      Year: 2020

🏁 Conclusion

Dr. Abdus Sobhan clearly meets and exceeds the benchmarks of the Research for Best Researcher Award. His work addresses critical global needs in food safety and smart packaging using advanced technologies, making him an ideal and highly deserving candidate.

Tieliang Zeng | Electrical Engineering | Excellence in Researcher Award

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Mr. Tieliang Zeng | Electrical Engineering | Excellence in Researcher Award

Master’s Degree Candidate at The Electrical Engineering College, Guizhou University, China

Tieliang Zeng, a passionate and emerging researcher, is currently pursuing his master’s degree at the Electrical Engineering College, Guizhou University. With a sharp focus on power electronics, his specialization lies in parameter identification of power electronic converters using digital twin technology 🔧🧠. As part of his academic journey, he has contributed to the Guizhou Provincial Key Technology R&D Program ([2024] General 049) and has successfully published one SCI-indexed paper in an MDPI journal 📄. Though early in his career, Tieliang’s commitment to innovation and technical precision is evident through his focused academic work. His field of study is essential to developing smarter, more efficient power systems 🌐⚡. As a budding scholar with a futuristic vision, he aims to expand his research through collaboration, scientific rigor, and practical application. Zeng is certainly a name to watch in the rapidly evolving domain of intelligent electrical systems and digital modeling technologies. 🚀🔬

Professional Profile

ORCID Profile

🎓 Education 

Tieliang Zeng embarked on his higher education journey with an enduring curiosity for electrical systems and smart technologies ⚡📘. He is currently a master’s degree candidate at the Electrical Engineering College of Guizhou University, one of China’s respected institutions in engineering education. His academic path has been defined by a commitment to technical depth and an interest in bridging physical systems with digital simulations through digital twin frameworks 🖥️🔄. With courses covering power electronics, control systems, and system modeling, Tieliang has built a solid theoretical and practical base to support his research. His continuous engagement with both classroom knowledge and real-world problems reflects his drive to excel academically 🎯📚. He is particularly focused on mastering advanced tools and methods for parameter identification in complex converter systems, which forms the foundation of his graduate thesis and current research endeavors. Tieliang’s academic foundation is both robust and forward-thinking. 🧠🧮

💼 Professional Experience 

As a young professional rooted in academia, Tieliang Zeng has initiated his professional journey through research-intensive roles and scholarly projects 🧑‍🔬🔌. His main involvement lies with the Guizhou Provincial Key Technology R&D Program, where he contributes to solving real-world challenges in power electronics through modeling and parameter extraction techniques 📊🔍. Although he has not yet ventured into large-scale consultancy or industrial projects, his participation in a government-funded initiative is a strong testament to his applied research capabilities. Tieliang’s work often involves digital simulations, hardware experimentation, and analytical evaluations – skills that mirror the evolving demands of modern electrical engineering 🌐🔋. Despite being early in his career, his focused technical contributions and publishing experience underscore his potential to make meaningful impacts in both academic and industrial settings in the near future. He’s actively shaping himself as a future innovator in digital twin-based power systems. 🛠️📈

🔬 Research Interests 

Tieliang Zeng’s research compass is firmly directed toward parameter identification in power electronic converters, a core challenge in creating accurate digital twin models 🔄⚡. His exploration dives deep into understanding the dynamic behavior of power systems and how virtual replicas can be developed to monitor, simulate, and control them in real time 🌍🧪. This specialized interest enables improved performance, predictive maintenance, and enhanced design processes in modern electrical infrastructure. His methodology often blends simulation tools, mathematical modeling, and real-world data analysis to ensure accuracy and adaptability 🧠📐. With the energy sector moving rapidly toward smart and autonomous systems, Tieliang’s work is aligned with the global shift toward digitalization and sustainability 🔋🌱. He is eager to refine these models further, enabling high-efficiency and fault-tolerant systems. By focusing his research within this transformative domain, he contributes to the foundational knowledge necessary for tomorrow’s power solutions. 🧬📡

🏆 Awards and Honors 

While Tieliang Zeng has not formally listed any academic awards or honors as of now, his inclusion in a key provincial R&D project and the successful publication of an SCI-indexed paper reflect a merit-based recognition of his talent and research abilities 🧾🏅. Being part of a selective and competitive government-funded research program is in itself an acknowledgment of his capabilities as a skilled researcher 🎯🎓. These achievements at an early stage signal his potential to receive future distinctions as his academic and professional journey unfolds. His scholarly persistence and contribution to innovative topics like digital twins in power systems are laying the groundwork for academic excellence and institutional accolades. With such a trajectory, awards and honors seem to be only a matter of time. His current achievements already reflect a commendable level of discipline, originality, and technical maturity 🌟📘.

Publications Top Notes

  • Title: Digital Twin-Based Multi-Parameter Coordinated Identification Method for Three-Phase Four-Leg Converter

  • Authors: Tieliang Zeng, et al.

  • Journal: Electronics

  • Year: 2025

  • DOI: 10.3390/electronics14102002

  • ISSN: 2079-9292

  • Source: MDPI – Electronics Journal

Conclusion 

In conclusion, Tieliang Zeng stands as a dedicated and promising figure in the field of electrical engineering, particularly in the niche domain of digital twin-based parameter identification for power converters 🔌🧠. As a master’s student with strong research orientation, he is already contributing to meaningful scientific discourse through government-supported projects and peer-reviewed publications 📚💡. Although at the early stages of his career, his focused efforts, analytical mindset, and technical competence set a solid foundation for impactful research and future innovation. Tieliang’s ambitions clearly resonate with the global move toward smart grid solutions and digital infrastructure, positioning him as a valuable asset to both academia and industry 🌍🔬. His journey reflects the beginning of a career with significant potential, where theory and practical application merge to solve complex power challenges. With continued dedication and collaboration, Tieliang Zeng is poised to advance the next wave of digital electrical technologies. 🚀🔧

Vaneet | Machine Learning | Best Researcher Award

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Prof. Dr. Vaneet | Machine Learning | Best Researcher Award

Professor at PURDUE UNIVERSITY, United States

vaneet aggarwal is a distinguished professor and university faculty scholar at purdue university, specializing in reinforcement learning, generative AI, quantum machine learning, and LLM alignment 🤖⚛️. With a Ph.D. from Princeton University 🎓 and extensive experience in industry and academia, he has made groundbreaking contributions to networking, robotics, healthcare, and computational biology 🌍🩺. He has served as a visiting professor at KAUST, IIIT Delhi, and IISc Bangalore 📚 and has led major research initiatives at AT&T Labs and Purdue CLAN Labs. His work has been recognized globally through high-impact publications and awards 🏅.

Professional Profile 

Education & Experience 🎓💼

📌 Education:

  • Ph.D. in Electrical Engineering – Princeton University, 2010 🎓 (GPA 4.0/4.0)
  • M.A. in Electrical Engineering – Princeton University, 2007 🏅 (GPA 4.0/4.0)
  • B.Tech in Electrical Engineering – IIT Kanpur, 2005 🎓 (GPA 9.6/10)

📌 Experience:

  • Purdue University (2015–Present) 🏫 – Professor & University Faculty Scholar
  • KAUST, Saudi Arabia (2022–2023) 🏝️ – Visiting Professor
  • IIIT Delhi (2022–2023) 🌏 – Adjunct Professor
  • Plaksha University (2022–2023) 📡 – Adjunct Professor
  • IISc Bangalore (2018–2019) 🏆 – VAJRA Adjunct Faculty
  • AT&T Labs Research, NJ (2010–2014) 📡 – Senior Member, Technical Staff
  • Columbia University, NY (2013–2014) 📚 – Adjunct Assistant Professor

Professional Development 🚀📚

vaneet aggarwal has consistently contributed to cutting-edge advancements in AI, machine learning, and quantum computing 🧠⚡. As Editor-in-Chief of the ACM Journal of Transportation Systems 🚗📖, he shapes global research trends. He has been a technical lead in Purdue’s AI and security programs, fostering industry collaborations 🤝💡. His leadership in AI decision-making, intelligent infrastructures, and computational biology has driven groundbreaking innovations 🏗️🔬. He frequently mentors Ph.D. students and collaborates with top institutions worldwide, ensuring continuous academic excellence and technological impact 🌍🎯. His work bridges fundamental research with real-world applications, influencing multiple industries 🚀.

Research Focus Areas 🔍💡

🔬 Artificial Intelligence & Machine Learning: Reinforcement learning, generative AI, LLM alignment 🤖
⚛️ Quantum Computing: Quantum machine learning, hidden Markov models 🧠
📡 Networking & Systems: Cloud computing, 5G/6G networks, network virtualization 🌐
🛠️ Optimization & Control: Combinatorial bandits, linear optimization ⚙️
🚗 Transportation & Robotics: AI for intelligent infrastructure and automation 🏎️
🩺 Healthcare & Biomedical AI: Drug discovery, computational biology, medical AI 🧬💊

His research transforms fundamental theories into real-world applications, influencing technology, healthcare, and sustainable infrastructure 🌍.

Awards & Honors 🏅🎖️

🏆 University Faculty Scholar, Purdue University (2024) 🏫
🎖️ Best Paper Award – NeurIPS Workshop on Cooperative AI (2021) 📝
📚 VAJRA Adjunct Faculty, IISc Bangalore (2018–2019) 🔬
🥇 Editor-in-Chief, ACM Journal of Transportation Systems (2022–Present) 🚗📖
🌍 Senior Member, IEEE & ACM ⚡
🏅 Best Research Contributions in AI & Quantum Computing 🤖⚛️

Publication Top Notes

1. Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback

  • Authors: Mohammad Pedramfar, Vaneet Aggarwal
  • Published in: IEEE Transactions on Artificial Intelligence, 2025
  • Summary: This paper addresses the combinatorial multi-armed bandit problem with stochastic submodular rewards and delayed, composite anonymous feedback. The authors analyze three delay models—bounded adversarial, stochastic independent, and stochastic conditionally independent—and derive regret bounds for each. Their findings indicate that delays introduce an additive term in the regret, affecting overall performance.
  • Access: The paper is available as open access.

2. FilFL: Client Filtering for Optimized Client Participation in Federated Learning

  • Authors: Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini, Marco Canini
  • Published in: [No source information available]
  • Summary: This conference paper introduces FilFL, a method to enhance federated learning by optimizing client participation through a filtering mechanism. By selecting a subset of clients that maximizes a combinatorial objective function, FilFL aims to improve learning efficiency, accelerate convergence, and boost model accuracy. Empirical evaluations demonstrate benefits such as faster convergence and up to a 10% increase in test accuracy compared to scenarios without client filtering.
  • Access: The paper is available as open access.

3. Prism Blockchain Enabled Internet of Things with Deep Reinforcement Learning

  • Authors: Divija Swetha Gadiraju, Vaneet Aggarwal
  • Published in: Blockchain: Research and Applications, 2024
  • Summary: This article explores the integration of Prism blockchain technology with the Internet of Things (IoT) using deep reinforcement learning techniques. The approach aims to enhance security, scalability, and efficiency in IoT networks by leveraging the unique features of Prism blockchain and the adaptive capabilities of deep reinforcement learning.
  • Access: The paper is available as open access.

4. GLIDE: Multi-Agent Deep Reinforcement Learning for Coordinated UAV Control in Dynamic Military Environments

  • Authors: Divija Swetha Gadiraju, Prasenjit Karmakar, Vijay K. Shah, Vaneet Aggarwal
  • Published in: Information (Switzerland), 2024
  • Summary: GLIDE presents a multi-agent deep reinforcement learning framework designed for the coordinated control of unmanned aerial vehicles (UAVs) in dynamic military settings. The framework focuses on enhancing mission success rates and operational efficiency by enabling UAVs to adapt to changing environments and collaborate effectively.
  • Access: The paper is available as open access.

5. Near-Perfect Coverage Manifold Estimation in Cellular Networks via Conditional GAN

  • Authors: Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Mohamed-Slim Alouini, Vaneet Aggarwal
  • Published in: IEEE Networking Letters, 2024
  • Summary: This article proposes a method for estimating coverage manifolds in cellular networks using conditional Generative Adversarial Networks (GANs). The approach aims to achieve near-perfect coverage predictions, which are crucial for optimizing network performance and ensuring reliable communication services.
  • Access: The paper is available as open access.

Conclusion

vaneet aggarwal is a highly suitable candidate for the Best Researcher Award, given his strong publication record, leadership, and multidisciplinary impact. If he strengthens his global recognition, large-scale funding acquisition, and public engagement, he could be an even stronger contender for such an award.