Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profileย 

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Education

Dr. Shuai Caoโ€™s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014โ€“2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017โ€“2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization schedulingโ€”work closely aligned with his masterโ€™s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projectsโ€”including โ€œResearch and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturingโ€ (Project Code: 2130218003022) and the โ€œFoshan Science and Technology Innovation Team Projectโ€ (Project Code: FS0AA-KJ919-4402-0060)โ€”he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Caoโ€™s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

 

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Assoc. Prof. Dr Ebrahim Farrokh, Amirkabir University of Technology, Iran

Assoc. Prof. Dr. Ebrahim Farrokh is a distinguished expert in rock mechanics and mining engineering, serving as the Head of Rock Mechanics and Mining Engineering at Amirkabir University of Technology. With a career spanning academia and industry, he specializes in tunnel boring machines (TBMs), underground excavation, and rock stability analysis. He has played a key role in major tunneling projects, providing expertise on TBM operations, rock fragmentation, and ground control. His research has led to numerous influential publications, advancing TBM performance prediction and tunnel design methodologies. Alongside his academic role, he consults for Tunnel Saz Machin Co. and has held managerial positions at Hyundai Engineering and Construction. Recognized with prestigious awards, including the Hardy Memorial Award and SMEโ€™s NAT Conference Scholarship, his contributions continue to shape the field of mining engineering. His work combines theoretical advancements with practical applications, ensuring safer and more efficient underground construction projects. ๐Ÿš†๐Ÿ’ก

Publication Profile

Google Scholoar

Education

  • Ph.D. in Mining Engineering, Penn State University (2009-2012) ๐Ÿ—๏ธ
    Dr. Farrokh earned his Ph.D. at Penn State University, focusing on TBM performance evaluation, advance rate prediction, and rock behavior analysis. His research contributed to innovative methodologies for assessing TBM cutter wear and ground stability.

  • M.Sc. in Mining Engineering, Tehran University (2001-2004) โ›๏ธ
    During his masterโ€™s studies, he specialized in underground excavation, tunnel stability, and mine planning. His thesis examined rock fragmentation techniques and their applications in mechanized tunneling.

  • B.Sc. in Mining Engineering, Yazd University (1997-2001) ๐ŸŒ
    He completed his undergraduate degree at Yazd University, gaining foundational knowledge in rock mechanics, mineral extraction, and geotechnical engineering. His early research explored TBM operational parameters and ground convergence in tunneling projects.

Experience

  • Associate Professor & Head, Rock Mechanics & Mining Engineering, Amirkabir University of Technology (2018-present) ๐ŸŽ“
    Leads research and academic initiatives in TBMs, tunnel stability, and underground mining.

  • Consultant, Tunnel Saz Machin Co. (2018-present) ๐Ÿ—๏ธ
    Provides technical expertise in TBM operations, ground support, and excavation efficiency.

  • TBM Specialist & Manager, Hyundai Engineering & Construction (2013-2017) ๐Ÿšœ
    Managed TBM operations in major tunneling projects, optimizing performance and reducing downtime.

  • Research Assistant, Penn State University (2009-2012) ๐Ÿ“Š
    Conducted cutting-edge research on TBM cutter wear, penetration rate estimation, and tunnel convergence.

Awards and Honors ๐Ÿ†

  • Outstanding Business Performance Award, Hyundai Engineering & Construction (2015) ๐ŸŒŸ
    Recognized for leadership in TBM project execution and efficiency improvements.

  • Outstanding Research Award, Hyundai Engineering & Construction (2014, 2015) ๐Ÿ…
    Awarded for contributions to TBM performance evaluation and geotechnical risk mitigation.

  • NAT Student Conference Scholarship Award, SME (2012) ๐ŸŽ“
    Acknowledged for excellence in mining engineering research and academic achievements.

  • Hardy Memorial Award, Penn State University (2010) ๐Ÿ†
    Prestigious recognition for outstanding research contributions in mining and rock mechanics.

Research Focus

Dr. Farrokhโ€™s research focuses on Tunnel Boring Machines (TBMs) ๐Ÿšœ, specializing in performance evaluation, advance rate prediction, and cutterhead design optimization. In Rock Mechanics ๐Ÿ—๏ธ, he investigates rock properties, ground convergence, and stability assessment for underground projects. His work in Mining Engineering โ›๏ธ explores underground mining methods, rock fragmentation, and geotechnical risk analysis. By integrating theoretical advancements with real-world applications, Dr. Farrokh enhances the efficiency and safety of tunneling and mining operations. His research contributes to optimizing excavation processes, reducing operational risks, and advancing sustainable underground construction. ๐Ÿ“Š๐Ÿ”ฌ

Publications Top Notes

  1. Tunnel Face Pressure Design and Control ๐Ÿ“Š (2020)
  2. Concrete Segmental Lining: Procedure of Design, Production, and Erection of Segmental Lining in Mechanized Tunneling ๐Ÿ“š (2006)
  3. Study of Various Models for Estimation of Penetration Rate of Hard Rock TBMs ๐Ÿ“Š (2012)
  4. Effect of Adverse Geological Conditions on TBM Operation in Ghomroud Tunnel Conveyance Project ๐ŸŒŽ (2009)
  5. Correlation of Tunnel Convergence with TBM Operational Parameters and Chip Size in the Ghomroud Tunnel, Iran ๐Ÿ“Š (2008)
  6. A Discussion on Hard Rock TBM Cutter Wear and Cutterhead Intervention Interval Length Evaluation ๐Ÿ’ก (2018)
  7. Evaluation of Ground Convergence and Squeezing Potential in the TBM-Driven Ghomroud Tunnel Project ๐ŸŒŽ (2006)
  8. Study of Utilization Factor and Advance Rate of Hard Rock TBMs ๐Ÿ“Š (2013)
  9. A Study of Various Models Used in the Estimation of Advance Rates for Hard Rock TBMs ๐Ÿ“Š (2020)
  10. Analysis of Unit Supporting Time and Support Installation Time for Open TBMs ๐Ÿ•’ (2020)

Banumathi S | Engineering and Technology | Women Researcher Award

Banumathi S | Engineering and Technology | Women Researcher Award

Dr Banumathi S, M.Kumarasamy College of Engineering, India

Dr. Banumathi S. is a distinguished academic and researcher in Electrical Engineering โšก, serving as a Professor at M. Kumarasamy College of Engineering with over 26 years of experience ๐Ÿซ. She earned her Ph.D. from Anna University, Chennai ๐ŸŽ“. Dr. Banumathi has published 28 research papers ๐Ÿ“š, including 11 in SCIE journals, and authored a Scopus-indexed book chapter. Her innovative contributions include 4 granted patents and 7 published patents ๐Ÿง‘โ€๐Ÿ”ฌ. A mentor for multiple funded projects ๐Ÿ’ก, she has guided Ph.D. scholars and contributed significantly to sustainable technologies ๐ŸŒ and advanced energy applications โš™๏ธ.

Publication Profile

google scholar

Academic Achievements

Dr. Banumathi earned her Ph.D. in Electrical Engineering from Anna University in 2015 and holds an M.E. in Power Electronics and Drives with First Class distinction (82%) ๐ŸŽ“โšก. With a stellar career spanning over 26 years in academia ๐Ÿ“š, she has made significant contributions to teaching, research, and mentoring young minds ๐ŸŒŸ. Currently, she serves as a Professor at M. Kumarasamy College of Engineering ๐Ÿซ, inspiring future engineers with her expertise in electrical systems and power electronics ๐Ÿ”Œโš™๏ธ. Her dedication to education and innovation continues to shape the next generation of technology leaders. ๐Ÿ’ก๐Ÿ“ˆ

Research Excellence

Dr. Banumathi has made notable contributions to sustainable technologies, electrical insulation materials, and green energy solutions โšก๐ŸŒฑ. She has published 28 journal papers, including SCIE and Scopus-indexed articles ๐Ÿ“šโœจ, and authored a book chapter ๐Ÿ“–. Her research has been presented at prestigious IEEE conferences ๐ŸŒ, showcasing her expertise in innovative energy solutions. With 138 citations on Scopus and 171 on Google Scholar ๐Ÿ“Š๐Ÿ“ˆ, her work has gained significant recognition and impact. Dr. Banumathi’s dedication to advancing sustainable technologies and green energy underscores her commitment to building a cleaner, more sustainable future ๐ŸŒ๐Ÿ’ก.

Experience

Dr. Banumathi S., a distinguished educator, boasts a remarkable 28 years of teaching experience in electrical and electronics engineering. She currently serves as a Professor at M. Kumarasamy College of Engineering, Karur, since 2016, contributing 8.7 years of expertise ๐ŸŒŸ๐Ÿ“š. Previously, she was an Associate Professor and Head at King College of Technology, Namakkal, for 5.10 years ๐Ÿซโœจ. Her journey includes roles as an Assistant Professor at Selvam College of Technology (1.11 years), HOD/EEE at PGP Polytechnic College (7.2 years), and Lecturer at M.P.N.M.J Polytechnic (2.9 years) ๐Ÿ› ๏ธ๐ŸŽ“. Dr. Banumathi’s dedication inspires countless students ๐Ÿ’ก๐Ÿ™Œ.

Achievements

Dr. Banumathi S is a distinguished researcher with 15 journal publications, including SCI/E, WoS, and Scopus-indexed papers ๐Ÿ“šโœจ. She holds Anna University Supervisor Recognition and has successfully guided one Ph.D. scholar, with two more in progress ๐ŸŽ“. Her innovative contributions include 4 granted patents and 7 published patents ๐Ÿ’ก๐Ÿ“œ. As a subject expert, she supported the AICTE MODROB-Rural Scheme (2019-2020) and mentors two MSME IdeaHackathon projects worth โ‚น12.75 lakhs ๐Ÿ’ผ๐Ÿš€. Dr. Banumathi authored a Scopus-indexed book chapter and a book ๐Ÿ“–. She has organized national and international conferences ๐ŸŒ, showcasing her dedication to academic excellence.

Research Focus

Dr. Banumathi’s research focuses on advanced materials and technologies for electrical and energy applications โšก๐Ÿ”ฌ. Her work spans photocatalytic materials, green synthesis of nanoparticles ๐ŸŒฑ๐Ÿงช, and innovative dielectric mediums, including vegetable oils ๐ŸŒฟ๐Ÿ›ข๏ธ and biopolymers, for high-voltage insulation. She explores partial discharge characteristics, aging effects, and breakdown strengths of alternative insulating mediums, contributing to sustainable and efficient energy systems ๐ŸŒ๐Ÿ”‹. Her studies on supercapacitors and microgrid energy management highlight her multidisciplinary approach. Through cutting-edge investigations in material science and electrical engineering, Dr. Banumathi significantly advances sustainable energy solutions and dielectric innovations. ๐Ÿ“ˆโš™๏ธ๐Ÿ’ก

Publication Top Notes

Rapid sun-light driven photocatalytic functions of 3D rGO/ZnO/Ag heterostructures via improved charge transfer kinetics

Green Synthesis of ZnMn2O4ย Nanoparticles for Supercapacitor Applications

Analysis of Breakdown Strength and Physical Characteristics of Vegetable Oils for High Voltage Insulation Applications

Analysis of Partial Discharge Characteristics of Olive and Castor Oil as Dielectric Medium for HV Applications

Investigation of dielectric and mechanical properties of Lignocellulosic Rice Husk Fibril for high and medium voltage electrical insulation applications

Investigations on PD characteristics of vegetable oils for high voltage applications

Power Management For Pv-Wind And Hybrid Energy Storage Integrated Micro Grid