Akwasi Amoh Mensah | Control Science| Best Researcher Award

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Mr. Akwasi Amoh Mensah | Control Science| Best Researcher Award

PhD Student at South China University of Technology, China

Mr. Akwasi Amoh Mensah is a dedicated Ph.D. student in Control Science and Engineering at the South China University of Technology, China. His research focuses on advanced control systems, automation technologies, and intelligent optimization techniques with applications across industrial and engineering systems. With a strong foundation in system modeling and control theory, Mr. Mensah is actively contributing to innovative solutions in the field of control science. His scholarly work and technical competence have positioned him as a promising researcher, making him a strong candidate for the Best Researcher Award.

Professional Profile 

🎓 Education

Akwasi Amoh Mensah has pursued a highly distinguished academic journey in engineering and control sciences. He is currently enrolled in a Ph.D. program in Control Science and Engineering at the South China University of Technology, China (2023–2026), with an exceptional GPA of 4.0/4.0. In parallel, he is undertaking an M.Sc. in Industrial Engineering and a Graduate Certificate in Wind Energy at Texas Tech University, USA (2024–2026), both maintaining a perfect GPA. He also holds an M.Sc. in Electrical and Computer Engineering (2021–2023) from South China University of Technology and a B.Sc. in Electrical Engineering and Automation from China Three Gorges University, where he graduated with a GPA of 3.8/4.0.

💼 Professional Experience

Akwasi has accumulated hands-on experience across academia, research, and industry. Currently, he serves as a Graduate Research Assistant at Texas Tech University, developing control systems for semiconductor inspection. Previously, he worked at the South China University of Technology as a Research Assistant, contributing to renewable energy-based power control strategies. His industry exposure includes an internship as an Assistant Electrical Engineer at Guangdong Jinlong Electrical and Mechanical Company, where he designed circuits and managed machine programming. He also held leadership roles at Comens Company Limited in Ghana as a Project and Sales Manager. Earlier roles include a Student Assistantship during his undergraduate studies and several organizational responsibilities in student services and university outreach.

🛠️ Skills and Technical Proficiency

Akwasi possesses a wide array of technical and analytical competencies. His software and programming proficiency include MATLAB, Python, LabVIEW, AutoCAD, SolidWorks, Keil, Proteus, and Comsol Multiphysics. He is skilled in FPGA, C programming, Arduino, and PLC systems. His practical capabilities span circuit design, control theory application, data analysis, electrical systems maintenance, and project management. In addition, his academic research has strengthened his abilities in simulation, scientific writing, and systems optimization.

🏆 Awards and Recognitions

Akwasi’s academic excellence is reflected in his consistent 4.0 GPA across multiple advanced degree programs. His innovative work in control engineering and renewable energy systems has led to numerous peer-reviewed publications in internationally recognized journals and conferences. His research contributions have earned him esteem in both academic and professional engineering communities, setting the stage for future accolades and awards in the field of control systems and smart energy technologies.

🔬 Research Focus

Akwasi Amoh Mensah’s research is centered on advanced control strategies for renewable energy systems, grid stability, and intelligent power generation. His work extensively explores the integration of metaheuristic optimization algorithms (e.g., salp swarm, artificial bee colony, and flower pollination) with grid-forming inverters and observer-based controllers for frequency and voltage regulation. He has published widely on solar and wind power optimization, maximum power point tracking (MPPT), and reinforcement learning for dynamic systems. His interdisciplinary approach bridges artificial intelligence, electrical control systems, and sustainable energy technologies.

📚 Publications Top Note 

📘 1. Second-order inertia automatic generation control based on grid-forming inverters using convergent observers salp swarm algorithm for frequency control

  • Citation (APA):
    Mensah Akwasi, A., Chen, H., Liu, J., Duku, O.-A., & Zeng, X. (2025). Second-order inertia automatic generation control based on grid-forming inverters using convergent observers salp swarm algorithm for frequency control. International Journal of Dynamics and Control. https://doi.org/10.1007/s40435-025-01709-3

  • Authors: Amoh Mensah Akwasi, Haoyong Chen, Junfeng Liu, Otuo-Acheampong Duku, Xin Zeng

  • Year: 2025

  • Journal: International Journal of Dynamics and Control

  • DOI: 10.1007/s40435-025-01709-3

⚡ 2. Grid forming inverters using reduced order-based Luenberger observer for power control

  • Citation (APA):
    Mensah Akwasi, A., Chen, H., & Liu, J. (2025). Grid forming inverters using reduced order-based Luenberger observer for power control. Electric Power Systems Research, 226, 111424. https://doi.org/10.1016/j.epsr.2025.111424

  • Authors: Amoh Mensah Akwasi, Haoyong Chen, Junfeng Liu

  • Year: 2025

  • Journal: Electric Power Systems Research

  • Volume: 226

  • Article Number: 111424

  • DOI: 10.1016/j.epsr.2025.111424

🏁 Conclusion

Dr. Lei Liu exemplifies the qualities of a Best Researcher Award recipient: depth in theoretical research, breadth in global experience, and excellence in teaching and mentorship. His leadership roles, prolific output, and rising trajectory within academic and engineering communities make him a model scholar in the communications field. While areas like applied innovation and interdisciplinary expansion offer room for growth, his current achievements already place him at the forefront of his domain.

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.

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.