Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

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Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Assistant Professor, Symbiosis International (Deemed to be University), India

Dr. Saikat Gochhait is an accomplished Indian academic, researcher, and innovator, currently serving as an Assistant Professor at Symbiosis International Deemed University, Pune. With a strong background in management, information technology, and behavioral sciences, he also contributes as a Research Team Member at the Symbiosis Centre for Behavioral Sciences and Adjunct Faculty at the Neuroscience Research Institute, Samara State Medical University, Russia. He is a prolific inventor with several published patents and has been recognized for his contributions to interdisciplinary research in artificial intelligence, neuroscience, and optimization algorithms.

Publication Profile

🎓 Education Background

Dr. Gochhait earned his Doctor of Philosophy (Ph.D.) in Management from Sambalpur University in 2014 🧠, a Master’s in Business Management from the same university in 2009 📊, and a Master’s in Information Technology from Sikkim Manipal University in 2017 💻. His diverse academic training has laid a multidisciplinary foundation that supports his cross-functional research across business, IT, and neuroscience domains.

💼 Professional Experience

With over two decades of experience spanning academia and industry, Dr. Gochhait has held key roles such as Assistant Professor at ASBM University, Khalikote University, and HOD at Sambhram Institute of Technology. His industry experience includes strategic roles at IFGL Refractories Ltd. and Tata Krosaki Refractories Ltd. Currently, at Symbiosis International University, he mentors postgraduate and doctoral students, manages AI-centric research projects, and continues collaborative ventures with prestigious institutions including IIT Roorkee and international universities 🌏.

🏆 Awards and Honors

Dr. Gochhait has been honored as a Senior Member of IEEE in 2019 and recognized by the Alpha Network of the Federation of European Neuroscience Societies in 2024 🌟. His academic excellence has earned him international research fellowships from leading institutions, including the Natural Sciences and Engineering Research Council of Canada, Samara State Medical University (Russia), National Dong Hwa University (Taiwan), and the University of Deusto (Spain), with total grants exceeding USD 20,000 💰.

🔬 Research Focus

Dr. Gochhait’s research is rooted in artificial intelligence, behavioral science, energy prediction, bio-inspired optimization algorithms, and neuroscience-enhanced technology applications 🧬. He is a principal investigator of high-impact government-funded projects such as AI-based load forecasting for dispatch centers and BCI-integrated neurofeedback games. His innovations also extend to smart agriculture and transport systems, reflecting his dedication to societal improvement through technology 🤖🌱.

✅ Conclusion

Blending visionary academic pursuit with innovative problem-solving, Dr. Saikat Gochhait continues to drive global research collaborations, mentor emerging scholars, and contribute meaningful technological solutions to real-world challenges 📚🌍. His evolving body of work bridges disciplines, industries, and nations, making him a respected figure in AI, management, and neuroscience research.

📚 Top Publications

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics, 2024 – Indexed in Scopus/WoS
Cited by: 12 articles

Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 9 articles

Addax Optimization Algorithm: A Novel Nature-Inspired Optimizer for Solving Engineering Applications
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 7 articles

Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks
IEEE Access, 2024 – Indexed in Scopus/WoS
Cited by: 15 articles

URL Shortener for Web Consumption: An Extensive and Impressive Security Algorithm
 Indonesian Journal of Electrical Engineering and Computer Science, 2024 – Indexed in Scopus
 Cited by: 6 articles

Dr. Biao Zhang | Technology | Best Researcher Award

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Dr. Biao Zhang | Technology | Best Researcher Award

Xi’an Research Institute of High-Tech, China

Zhang Biao is a promising doctoral student specializing in Nuclear Science and Technology at the PLA Rocket Force Engineering University, Xi’an, China. With a focus on advancing safety and efficiency in nuclear environments, his research emphasizes radiation field reconstruction and dose-optimized path planning. He has authored multiple peer-reviewed articles in top-tier journals like Annals of Nuclear Energy and Nuclear Technology. Zhang’s contributions to computational modeling and intelligent algorithms mark him as an emerging innovator in his field 🧠⚛️.

Publication Profile

ORCID

🎓 Education Background:

Zhang Biao pursued his higher education at the esteemed PLA Rocket Force Engineering University in Xi’an, Shaanxi, China 🎓. Currently engaged in his doctoral studies, his academic journey is rooted in nuclear science with an inclination toward computational applications in radiation detection and safety mechanisms.

💼 Professional Experience:

Although still in academia, Zhang has demonstrated notable professional-level impact through his published works. He is affiliated with the Xi’an Research Institute of High-Tech and is a proud member of the Chinese Nuclear Society 🧪. His hands-on experience with mathematical modeling and radiation path optimization contributes to future applications in nuclear facility safety.

🏆 Awards and Honors:

While formal accolades are pending, Zhang’s scholarly output—particularly his recent algorithmic improvements in radiation path planning—have earned recognition in high-impact journals and among nuclear technology scholars. His nomination for the Best Researcher Award by the Computer Scientists Awards underscores his rising prominence in scientific research 🥇📚.

🔬 Research Focus:

Zhang Biao’s work revolves around enhancing the safety of radiation environments through efficient detection and computational path planning. His innovations include a modified A* algorithm for minimizing radiation dose exposure and improved reconstruction techniques for gamma-ray source fields using interpolation and mathematical modeling 🔍🛰️.

🔚 Conclusion:

Zhang Biao represents the new generation of nuclear technologists who integrate artificial intelligence with radiation safety science. With multiple first-author publications, innovative algorithms, and a clear vision for nuclear safety, he is well on track to make substantial contributions to science and society 🌏💡.

📚 Top Publications:

A modified A* algorithm for path planning in the radioactive environment of nuclear facilities – Annals of Nuclear Energy, 2025.
Cited by: Referenced in dose optimization and nuclear safety path planning studies.

Path planning of PRM based on artificial potential field in radiation environments – Annals of Nuclear Energy, 2024.
Cited by: Utilized in advanced robotics navigation within hazardous nuclear zones.

Minimum dose walking path planning in a nuclear radiation environment based on a modified A* algorithm –Annals of Nuclear Energy, 2024.
Cited by: Recognized for efficient personnel routing in nuclear facilities.

A comparative study of different radial basis function interpolation algorithms in the reconstruction and path planning of γ radiation fields – Nuclear Engineering and Technology, 2024.
Cited by: Referenced in computational gamma field modeling research.

Reconstruction of γ Dose Rate Field and Algorithm Validation Based on Inverse Distance Weight Interpolation – Nuclear Technology, 2024.
Cited by: Applied in gamma dose field reconstruction validations.

Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

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Dr. Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Postdoc Fellow, Inje University, South Korea

🎓 Sikandar Ali is a passionate AI researcher and educator specializing in Artificial Intelligence applications in healthcare. Currently pursuing a PhD at Inje University, South Korea, he has a strong academic background and extensive research experience in digital pathology, medical imaging, and machine learning. As a team leader of the digital pathology project, he develops innovative AI algorithms for cancer diagnosis while collaborating with a global team of researchers. Sikandar is a recipient of prestigious scholarships, accolades, and recognition for his contributions to AI and healthcare innovation.

Publication Profile

Google Scholar

Education

📘 Sikandar Ali holds a PhD in Artificial Intelligence in Healthcare (CGPA: 4.46/4.5) from Inje University, South Korea, where his thesis focuses on integrating pathology foundation models with weakly supervised learning for gastric and breast cancer diagnosis. He earned an MS in Computer Science from Chungbuk National University, South Korea (GPA: 4.35/4.5), with research on AI-based clinical decision support systems for cardiovascular diseases. His undergraduate degree is a Bachelor of Engineering in Computer Systems Engineering from Mehran University of Engineering and Technology, Pakistan, with a CGPA of 3.5/4.0.

Experience

💻 Sikandar is an experienced researcher and AI specialist. Currently working as an AI Research Assistant at Inje University, he focuses on cutting-edge projects in digital pathology, cancer detection, and medical imaging. Previously, he worked as a Research Assistant at Chungbuk National University, focusing on cardiovascular disease diagnosis using AI. His industry experience includes roles such as Search Expert at PROGOS Tech Company and Software Developer Intern at Hidaya Institute of Science and Technology.

Awards and Honors

🏆 Sikandar has received multiple awards, including the Brain Korean Scholarship, European Accreditation Council for Continuing Medical Education (EACCME) Certificate, and recognition as an outstanding Teaching Assistant at Inje University. He has also earned full travel grants for international conferences, extra allowances for R&D industry projects, and certificates for reviewing research papers in leading journals. Additionally, he is a Guest Editor at Frontiers in Digital Health.

Research Focus

🔬 Sikandar’s research focuses on developing AI algorithms for medical imaging, with expertise in weakly supervised learning, self-supervised learning, and digital pathology. His projects include designing AI systems for cancer detection, COVID-19 prediction, and IPF severity classification. He also works on object detection applications using YOLO models and wearable sensor-based activity detection for pets. His commitment to explainability and interpretability in AI models ensures their practical utility in healthcare.

Conclusion

🌟 Sikandar Ali is a dedicated AI researcher driving innovation in healthcare through artificial intelligence. With his strong educational foundation, diverse research experience, and impactful contributions, he aims to bridge the gap between AI and medicine, making healthcare more efficient and accessible.

Publications

Detection of COVID-19 in X-ray Images Using DCSCNN
Sensors 2022, IF: 3.4

A Soft Voting Ensemble-Based Model for IPF Severity Prediction
Life 2021, IF: 3.2

Metaverse in Healthcare Integrated with Explainable AI and Blockchain
Sensors 2023, IF: 3.4

Weakly Supervised Learning for Gastric Cancer Classification Using WSIs
Springer 2023

Classifying Gastric Cancer Stages with Deep Semantic and Texture Features
ICACT 2024

Computer Vision-Based Military Tank Recognition Using YOLO Framework
ICAISC 2023

Activity Detection for Dog Well-being Using Wearable Sensors
IEEE Access 2022

Cat Activity Monitoring Using Wearable Sensors
IEEE Sensors Journal 2023, IF: 4.3

Deep Learning for Algae Species Detection Using Microscopic Images
Water 2022, IF: 2.9

Comprehensive Review on Multiple Instance Learning
Electronics 2023

Hybrid Model for Face Shape Classification Using Ensemble Methods
Springer 2021

Cervical Spine Fracture Detection Using Two-Stage Deep Learning
IEEE Access 2024

 

Robin Augustine | Artificial Intelligence | Excellence in Research

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Assoc. Prof. Dr. Robin Augustine | Artificial Intelligence | Excellence in Research

Associate Professor, Uppsala University, Sweden

🎓 Associate Professor Robin Augustine is a renowned expert in Medical Engineering and Microwave Technology, leading research at Uppsala University in Sweden. He heads the Microwaves in Medical Engineering Group at the Angstrom Laboratory, Department of Electrical Engineering, and serves as an Associate Editor for IET journals. His interdisciplinary work spans medical sensor development, bioelectromagnetic interactions, and innovative in-body communication technologies. Robin has collaborated globally as a visiting professor and researcher, focusing on advancements in medical engineering through impactful research projects.

Publication Profile

Scopus

Education

📚 Dr. Robin Augustine earned his Ph.D. in Electronics and Optronics Systems from Université de Paris Est Marne La Vallée, specializing in human tissue electromagnetic modeling and its implications for medical sensor design. He holds an MSc in Electronics Science with a focus on Robotics from Cochin University of Science and Technology, and a BSc in Electronics Science from Mahatma Gandhi University. His expertise is further strengthened by advanced training in Diagnostic and Therapeutic Applications of Electromagnetics from Politecnico di Torino, Italy.

Experience

💼 Robin’s career includes extensive experience as a senior lecturer and associate professor at Uppsala University, where he has been leading research in microwave applications for medical technology since 2011. He has held visiting professorships and research roles at institutions such as the Beijing Institute of Nanoenergy and Nanosystems and University Medical Center Maastricht, contributing to medical sensor innovation and orthopedic measurement systems. Robin has also worked internationally, including postdoctoral research in France, with expertise in antenna design, bioelectromagnetics, and microwave characterization.

Research Focus

🔬 Robin’s research focuses on medical engineering, bioelectromagnetics, and intra-body communication, including developing microwave-based sensors for diagnosing conditions like osteoporosis, skin cancer, and muscular atrophy. As a leader in the B-CRATOS and COMFORT projects, he explores body-centric technologies and in-body wireless communication to enhance medical diagnostics. His pioneering work addresses the integration of electromagnetic technology with healthcare, making strides in non-invasive monitoring systems.

Awards and Honours

🏆 Dr. Augustine’s impactful research has attracted numerous grants and awards, including significant EU funding for projects like PERSIMMON and DIAMPS. He has secured research funding from bodies such as the Swedish Research Council, Vinnova, and the Foundation for Strategic Research, supporting his innovative work on body communication systems and medical diagnostics. His research has earned recognition through the Swedish Excellence Grant for Young Researchers and multiple grants for advancing medical engineering solutions.

Publication Top Notes

Biphasic lithium iron oxide nanocomposites for enhancement in electromagnetic interference shielding properties

Rotation insensitive implantable wireless power transfer system for medical devices using metamaterial-polarization converter

Improving burn diagnosis in medical image retrieval from grafting burn samples using B-coefficients and the CLAHE algorithm

 

Christopher Ekeocha | Machine learning | Best Researcher Award

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Mr. Christopher Ekeocha | Machine learning | Best Researcher Award

Graduate Research Assistant, Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS), Nigeria

Christopher Ikechukwu Ekeocha is a dedicated Assistant Research Fellow at the National Mathematical Centre in Abuja, Nigeria, with a keen interest in corrosion mitigation and environmental pollution. His extensive research focuses on developing innovative eco-friendly materials and computational simulation techniques to address corrosion and pollution challenges. He has represented Nigeria internationally at the International Chemistry Olympiad, guiding students to success in countries like Vietnam, Azerbaijan, Georgia, France, and China. 🌍🔬

Publication Profile

ORCID

Strengths for the Award:

  1. Academic Excellence: Christopher Ikechukwu Ekeocha has consistently performed at a high academic level throughout his education. His Ph.D. in Corrosion Technology (CGPA: 4.60/5.0) and Master’s in Environmental Chemistry (CGPA: 3.92/5.0) demonstrate his dedication to research and academic rigor.
  2. Innovative Research: His focus on developing eco-friendly, biomass-based anti-corrosion materials and using machine learning models for corrosion prediction is cutting-edge. His work combines experimental and computational techniques, pushing the boundaries of corrosion technology.
  3. Strong Publication Record: Ekeocha has published extensively in reputable, high-impact journals, with topics ranging from corrosion inhibitors to environmental chemistry. This demonstrates the relevance and quality of his work. Key publications include machine learning models and computational simulations for anti-corrosion research, which have been well-received in the scientific community.
  4. Interdisciplinary Collaboration: He has collaborated on multidisciplinary projects promoting circular economy and eco-friendly techniques for corrosion mitigation. His ability to work across various fields shows adaptability and leadership in research.
  5. Community Contribution: In addition to his academic work, Ekeocha has made significant contributions to the Chemistry Olympiad, leading Nigerian teams and authoring textbooks. His role in this capacity speaks to his leadership and commitment to education and knowledge dissemination.

Areas for Improvement:

  1. Research Diversification: While Ekeocha has made strong contributions in corrosion technology, expanding his research to other areas of environmental chemistry or further enhancing the practical applications of his work could strengthen his overall profile. Engaging in more diverse projects could showcase his versatility.
  2. Industry Engagement: Although his research is well-grounded in academia, there could be a stronger connection with industry to ensure his innovations, especially in corrosion mitigation, are applied in real-world settings. Collaborations with companies focusing on corrosion prevention or environmental impact assessments could enhance the practical impact of his research.
  3. International Recognition: While his publications are gaining recognition, presenting his research at more international conferences or collaborating with foreign institutions could boost his global visibility and increase the influence of his work.

Education

Christopher Ekeocha is affiliated with the Africa Centre of Excellence in Future Energies and Electrochemical Systems (ACE-FUELS) at the Federal University of Technology, Owerri (FUTO). His research emphasizes the permeation of ions across semi-permeable membranes, focusing on membrane thickness, permeation time, and electrolyte concentration. 🎓⚛️

Experience

With over a decade of experience, Christopher Ekeocha has served as an Assistant Research Fellow at the National Mathematical Centre, Abuja, since 2011. He leads Nigeria’s participation in the International Chemistry Olympiad, having represented the country in multiple international events. His expertise lies in corrosion studies, computational modeling, and eco-friendly corrosion inhibitors. 🌱🔧

Research Focus

Christopher’s research centers on the development of mathematical and predictive models for novel corrosion inhibitors. He specializes in using computational simulations and eco-friendly materials to mitigate metallic corrosion and conducting ecological risk assessments of environmental pollution. His work also covers adsorption kinetics, water and solvent treatment using nanoparticles, and pollutant removal with agricultural waste. 📊🔍

Awards and Honours

Ekeocha has gained recognition for his contributions to corrosion research and environmental protection. His participation in the International Chemistry Olympiad as a Nigerian team leader is notable, alongside his extensive academic publications and active role in global scientific conferences. 🏆🌟

Publication Top Notes

Christopher Ikechukwu Ekeocha has authored several influential articles in prestigious journals, including Materials Today Communications, Structural Chemistry, and African Scientific Reports. His works primarily focus on corrosion inhibition, eco-friendly materials, and environmental pollution. 📚✨

Ekeocha, C. I., et al. (2024). Data-Driven Machine Learning Models and Computational Simulation Techniques for Prediction of Anti-Corrosion Properties of Novel Benzimidazole Derivatives. Materials Today Communications https://doi.org/10.1016/j.mtcomm.2024.110156

Ekeocha, C. I., et al. (2024). Theoretical Study of Novel Antipyrine Derivatives as Promising Corrosion Inhibitors for Mild Steel in an Acidic Environment. Structural Chemistry https://doi.org/10.1007/s11224-024-02368-4

Ekeocha, C. I., et al. (2023). Review of Forms of Corrosion and Mitigation Techniques: A Visual Guide. African Scientific Reports, 2(3): 117. https://doi.org/10.46481/asr.2023.2.3.117

Conclusion:

Christopher Ikechukwu Ekeocha is an excellent candidate for the Research for Best Research Award. His innovative contributions in the field of corrosion technology, combined with his interdisciplinary approach and strong academic background, position him well for recognition. His research aligns with global trends toward eco-friendly solutions and computational advancements, making him a strong contender. However, increased industry engagement and further research diversification would further elevate his impact in both academic and practical domains.