Shrinivas Shirkande | Computer Engineering | Best Academic Researcher Award

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Dr. Shrinivas Shirkande | Computer Engineering | Best Academic Researcher Award

Principal, HOD Computer | S B Patil COE Indapur, Pune | India

Dr. Shrinivas T. Shirkande is an accomplished academician, researcher, and academic leader in the field of Computer Engineering. He currently serves as the Additional-charge of Principal and Head of the Computer Engineering Department at S.B. Patil College of Engineering, Indapur, affiliated with Pune University. With a strong background in teaching, research, and administration, he has significantly contributed to institutional development, student mentorship, and scholarly innovation. His expertise spans across computer science fundamentals, software engineering, machine learning, data analytics, cloud computing, cybersecurity, and advanced computational models.

Professional Profile

Scopus | Orcid | Google Scholar

Education

Dr. Shirkande holds a Ph.D. in Computer Engineering, complemented by an M.Tech. in Information Technology and a B.Tech. in Information Technology. His academic journey has been marked by a consistent focus on research-driven approaches and the integration of emerging technologies into teaching and practice.

Experience

He has served in progressively responsible academic roles, beginning as an Ad-Hoc Lecturer and later as an Assistant Professor at reputed institutions including Yadavrao Tasgaonkar College of Engineering and Konkan Gyanpeeth College of Engineering. Since joining S.B. Patil College of Engineering, Indapur, he has held key positions such as Assistant Professor, Head of Department, and Additional-charge Principal. His leadership includes spearheading accreditation processes such as NAAC (Grade A), heading the Institute Innovation Cell and R&D Cell, and organizing national and international conferences. His role as editor, session chair, syllabus reform committee member, and conference organizer further highlights his academic impact.

Research Interests

Dr. Shirkande’s research focuses on artificial intelligence, machine learning, cloud computing, cybersecurity, healthcare IoT, and data analytics. His work includes contributions to cloud job scheduling with multi-component attention graph neural networks, privacy-preserving IoT solutions using attribute-based cryptography, and hybrid CNN models for melanoma detection. He is particularly interested in applying computational intelligence to solve real-world challenges in data-driven systems, healthcare, and security.

Honors

He has received recognition for his contributions as a General Chair and Editor-in-Chief of international conferences, including ICEST, and as a co-convener of ICERAT. He has been acknowledged for leading institutional achievements such as NAAC accreditation success. His roles as reviewer and session chair in IEEE and Springer conferences further establish his standing in the academic community.

Top Noted Publications

Secure group key agreement protocol with elliptic curve secret sharing for authentication in distributed environments – Citations: 16, Indexed: Scopus, Year: 2023.

Deep learning driven QoS anomaly detection for network performance optimization – Journal of Electrical Systems 19 (2), Citations: 9, Indexed: Scopus, Year: 2023.

CR System with Efficient Spectrum Sensing and Optimized Handoff Latency to Get Best Quality of Service – International Journal of Intelligent Systems and Applications in Engineering, Citations: 9, Indexed: Scopus, Year: 2023.

The intersection of technology and public health: opportunities and challenges – South Eastern European Journal of Public Health, Citations: 8*, Indexed: Scopus, Year: 2023.

Hydroponics farming using IoT – International Journal of Research in Applied Science and Engineering Technology, Citations: 5, Indexed: Scopus, Year: 2022.

An Explainable Deep Learning Model for Clinical Decision Support in Healthcare – WSN and IoT, Citations: 4, Indexed: Scopus, Year: 2024.

Conclusion

Through his combined contributions in research, teaching, leadership, and institutional development, Dr. Shrinivas T. Shirkande has established himself as a distinguished academic leader in computer engineering. His work bridges the gap between theory and practice, ensuring that innovative solutions are developed for pressing challenges in cloud computing, healthcare, and security. With an expanding research portfolio, active involvement in international academic networks, and a strong commitment to student and institutional growth, he continues to play a vital role in advancing knowledge and innovation in his field.

Mr Benjamin Kwasi Gyamfi | Information and Communication Sciences | Best Researcher Award |

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Mr. Benjamin Kwasi Gyamfi | Information and Communication Sciences | Best Researcher Award | 

Graduate Teaching Assistant, at Ball State University, United States.

Benjamin Kwasi Gyamfi is a dedicated researcher and finance professional with a strong academic background and extensive experience in financial analysis, information systems, and business research. Passionate about data-driven decision-making, he integrates financial expertise with technology to drive innovative solutions. His work spans research, teaching, leadership, and entrepreneurship, demonstrating a commitment to academic excellence and real-world impact.

Professional Profile

Orcid

Google Scholar

Education 🎓

Benjamin is currently pursuing a Master of Science in Information and Communication Sciences at Ball State University, Muncie, Indiana, with an expected completion in July 2025. He also holds a Master of Business Administration (Finance Specialization) from the Manipal Academy of Higher Education, India, where he conducted research on banking mergers and financial performance. Additionally, he has pursued Chartered Accountancy at the Institute of Chartered Accountants, Ghana, completing all but one final-level paper. His undergraduate studies include a Bachelor of Arts in Economics with Computer Science from the University of Ghana, where he analyzed the impact of microfinance on poverty reduction.

Professional Experience 💼

Currently serving as a Graduate Assistant at Ball State University, Benjamin mentors and teaches Public Speaking to 135 students while assisting in course development and student engagement. He also serves as the Financial Secretary for the Sports Complex Lands Regularization Association, where he manages financial records, audits, and reporting. As the Founder of Attitudinal Breakthrough Foundation, he leads research-driven initiatives focused on community empowerment, education, and business process efficiency. His previous roles include working with Ga North Municipal Assembly as a Management Information Systems Trainee, where he developed business databases for over 7,000 entities and validated financial transactions exceeding $30,000. Additionally, he contributed to Ecobank Ghana Limited as a Subscription Officer during MTN Ghana’s IPO project, handling over 2,000 shareholder records and managing large-scale financial subscriptions.

Research Interests 🌍

Benjamin’s research primarily explores financial performance analysis, microfinance, banking systems, and information technology applications in finance. His past projects have examined the effects of mergers and acquisitions on banking performance, financial ratios in corporate assessments, and geographic information system (GIS) applications in revenue management. His interdisciplinary approach bridges the gap between finance, technology, and economic development, emphasizing innovative strategies for financial sustainability.

Awards & Honors 🏆

Benjamin has earned various certifications and accolades, reflecting his dedication to continuous learning and leadership. He has completed professional training in Google Project Management, Business and Impact Planning (MITx), Leadership Certification (NAD), and Research Methods for Business Students. His ability to integrate finance and technology has positioned him as a thought leader in business process improvements and data governance.

Top Noted Publications 📚

Text Classification: How Machine Learning Is Revolutionizing Text Categorization – H. Allam, L. Makubvure, B. Gyamfi, K. N. Graham, K. Akinwolere | Cited by: 1 | Published: 2024

Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education – H. M. Allam, B. Gyamfi, B. AlOmar | Indexed in: Education Sciences | Cited by: Pending | Published: 2025

Conclusion

With a strong foundation in finance, research, and technology, Benjamin Kwasi Gyamfi is a rising scholar dedicated to advancing financial systems through research and innovation. His expertise in data analytics, financial modeling, and strategic decision-making positions him as a valuable contributor to both academia and industry. As he continues to expand his research footprint, his work will play a pivotal role in shaping the future of financial sustainability and business intelligence.

Assoc. Prof. Dr Mohsen Edalat | Machine Learning | Best Researcher Award |

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Assoc. Prof. Dr. Mohsen Edalat | Machine Learning | Best Researcher Award | 

Associate Professor, at School of Agriculture, Shiraz University, Iran.

Assoc. Prof. Dr. Mohsen Edalat is a highly motivated agronomist, researcher, and academic leader with over 20 years of experience in crop production, farm management, and sustainable agriculture. He has a strong background in agronomy, crop breeding, greenhouse management, and precision agriculture. As an Associate Professor and Senior Farm Manager, he has successfully integrated scientific research with practical applications, optimizing crop yields, genetic selection, and agricultural sustainability. His innovative work in medicinal plant domestication and startup entrepreneurship has contributed significantly to agronomic advancements.

Professional Profile

Scopus

Orcid

Google Scholar

Education 🎓

Ph.D. in Agronomy (2007-2010) – Shiraz University, Iran

M.Sc. in Agronomy (2002-2005) – Shiraz University, Iran

B.Sc. in Agronomy (1993-1997) – Shiraz University, Iran

Professional Experience 💼

Associate Professor, Crop Production & Breeding Dept., Shiraz University (2017–Present)

Senior Farm Manager, Research & Commercial Production (1999–2023) – Managed a 500 ha farm

Dean, School of Agriculture, Shiraz University (2018–2020)

Vice Dean for Financial & Administrative Affairs, Shiraz University (2014–2018)

Assistant Professor, Crop Production & Breeding Dept. (2011–2017)

Lecturer, Shiraz University (1999–2011)

Research Interests 🌍

Dr. Edalat’s research primarily focuses on crop growth modeling, plant breeding, precision agriculture, and sustainable farming practices. He has expertise in mathematical modeling of plant growth, experimental designs, weed science, and data-driven agronomy. His work has also extended to machine learning applications in agriculture, with studies on species distribution modeling, seed viability, and climate-adaptive cropping systems.

Awards & Honors 🏆

Exemplar Faculty Member, Shiraz University (2018) – Voted by students and faculty

Founder of MAYSA PARS GREENTECH (2022) – A startup focused on medicinal herb breeding and production

Developed a New Domestication Procedure (2020) – Successfully domesticated Zataria multiflora (endangered medicinal plant)

Record Agricultural Yields (2020 & 2021) – Achieved 122 tons/ha silage corn and 7,600 kg/ha winter wheat

Scholarship Recipient – Iranian Ministry of Science for Visiting Research at Melbourne University (2010)

Top 5% Student Ranking – B.Sc., M.Sc., and Ph.D.

Top Noted Publications 📚

Assessing and Mapping Multi-Hazard Risk Susceptibility Using a Machine Learning Technique
Authors: H.R. Pourghasemi, N. Kariminejad, M. Amiri, M. Edalat, M. Zarafshar, et al.
Journal: Scientific Reports
Citations: 212
Year: 2020

Is Multi-Hazard Mapping Effective in Assessing Natural Hazards and Integrated Watershed Management?
Authors: H.R. Pourghasemi, A. Gayen, M. Edalat, M. Zarafshar, J.P. Tiefenbacher
Journal: Geoscience Frontiers
Citations: 115
Year: 2020

The Impact of Nitrogen and Organic Matter on Winter Canola Seed Yield and Yield Components
Authors: S.A. Kazemeini, H. Hamzehzarghani, M. Edalat
Journal: Australian Journal of Crop Science
Citations: 76
Year: 2010

Interaction Effects of Deficit Irrigation and Row Spacing on Sunflower (Helianthus annuus L.) Growth, Seed Yield, and Oil Yield
Authors: S.A. Kazemeini, M. Edalat, A. Shekoofa
Journal: African Journal of Agricultural Research
Citations: 69
Year: 2009

Corn Nitrogen Management Using NDVI and SPAD Sensor-Based Data Under Conventional vs. Reduced Tillage Systems
Authors: M. Edalat, R. Naderi, T.P. Egan
Journal: Journal of Plant Nutrition
Citations: 60
Year: 2019

Conclusion

Dr. Mohsen Edalat is a strong candidate for a Best Researcher Award, given his leadership, practical achievements in agriculture, research contributions, and teaching excellence. Strengthening his publication record, international collaborations, and patents would further enhance his competitiveness.

Dr Han Gao | Artificial Intellegence | Best Researcher Award |

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Dr. Han Gao | Artificial Intellegence | Best Researcher Award

postdoctoral fellow, at Harvard University, United States.

Dr. Han Gao is a dedicated researcher specializing in scientific deep learning, computational mechanics, and generative models for spatiotemporal physics. With a strong background in machine learning-driven physics simulations, he has contributed significantly to advancing numerical modeling and data-driven solutions for complex physical systems. His work bridges the gap between deep learning and traditional computational fluid dynamics, with applications in turbulence modeling, inverse problems, and reduced-order modeling.

Professional Profile

Scopus

Google Scholar

Education 🎓

Dr. Gao earned his Ph.D. in Aerospace and Mechanical Engineering from the University of Notre Dame (2018–2023), where he focused on scientific deep learning for forward and inverse modeling of spatiotemporal physics. He also holds a Master’s degree in Mechanical Engineering & Materials Science from Washington University in St. Louis (2016–2018), with research on numerical simulations of jet impingement and rotor blade effects. His academic journey began with a Bachelor’s degree in Mechanical Engineering from Shanghai University of Electric Power (2012–2016).

Professional Experience 💼

Dr. Gao is currently a Postdoctoral & Teaching Fellow at Harvard University (2023–present), where he continues his research in deep learning-driven physics simulations while mentoring students. Previously, he served as a Research & Teaching Assistant at the University of Notre Dame (2018–2023) and Washington University in St. Louis (2016–2018). Additionally, he gained industry experience as a Research Intern at Google Research (2022), where he worked on advanced AI-driven physics simulations.

Research Interests 🌍

Dr. Gao’s research revolves around the integration of deep learning techniques with physics-based modeling, particularly in solving partial differential equations (PDEs), turbulence modeling, generative models, and reduced-order modeling. He has developed novel physics-informed neural networks (PINNs), Bayesian generative models, and machine-learning frameworks for high-dimensional complex systems. His work is widely applicable in computational fluid dynamics (CFD), climate modeling, aerodynamics, and engineering simulations.

Awards & Honors 🏆

Dr. Gao has been recognized for his outstanding contributions to computational mechanics and machine learning applications in physics. His publications in top-tier journals, including Nature Communications, and prestigious machine learning conferences such as NeurIPS, ICML, and ICLR, reflect his impact in the field. He has also received competitive research opportunities, including a Google Research internship, showcasing his industry relevance.

Top Noted Publications 📚

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
L. Sun, H. Gao, S. Pan, J.-X. Wang – 916 citations – Computer Methods in Applied Mechanics and Engineering, 2020

PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain
H. Gao, L. Sun, J.-X. Wang – 567 citations – Journal of Computational Physics, 2021

Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
H. Gao, M. J. Zahr, J.-X. Wang – 240 citations – Computer Methods in Applied Mechanics and Engineering, 2022

Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels
H. Gao, L. Sun, J.-X. Wang – 214 citations – Physics of Fluids, 2021

Predicting physics in mesh-reduced space with temporal attention
X. Han, H. Gao, T. Pfaff, J.-X. Wang, L.-P. Liu – 106 citations – ICLR, 2022

Conclusion

Dr. Han Gao is a highly promising researcher with a strong publication record, interdisciplinary expertise, and experience at prestigious institutions. His contributions to scientific deep learning and computational mechanics make him a strong contender for the Best Researcher Award. To further solidify his case, he could focus on gaining more individual recognitions, expanding his leadership roles, and demonstrating the real-world impact of his research.