Shrinivas Shirkande | Computer Engineering | Best Academic Researcher Award

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.

Assoc. Prof. Dr Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award |

Assoc. Prof. Dr Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award

Associate professor , at West Ukrainian National University, Ukraine.

Assoc. Prof. Dr. Khrystyna Lipianina-Honcharenko is a dedicated academic and researcher specializing in Information Technology, with a strong foundation in economic cybernetics and artificial intelligence. Based at the West Ukrainian National University in Ternopil, Ukraine, she has steadily progressed through the academic ranks, currently serving as an Associate Professor in the Department of Information Computer Systems and Control. Her work bridges data science, simulation, and socio-economic modeling, with a strong commitment to research excellence and innovation in education and interdisciplinary projects.

Professional Profile

Orcid

Google Scholar

Education 🎓

Dr. Lipianina-Honcharenko holds a Ph.D. in Technical Sciences (2019), with a specialization in Information Technology, and is currently completing her Doctor of Technical Sciences (2025) at West Ukrainian National University. She began her academic journey with a Bachelor’s degree in Economic Cybernetics (2011), followed by a Master’s degree in Information Technologies in Economics (2012). She also completed postgraduate studies in Economic Cybernetics and Informatics between 2013 and 2017. Her education reflects a deep and consistent engagement with technical and analytical disciplines critical to modern digital research.

Experience 💼

Dr. Lipianina-Honcharenko has over a decade of academic experience. She began as a Laboratory Assistant in the Department of Economic Cybernetics and Informatics (2012–2014), before becoming a Lecturer in the same department (2013–2020). She then served as a Senior Lecturer in the Department of Information Computer Systems and Control (2020–2021) and was promoted to Associate Professor in 2021, a role she currently holds. Her teaching and mentorship have consistently focused on data science, IT systems, and modeling, contributing to the development of future tech-savvy professionals.

Research Interests 🔬

Her research interests include data analysis, simulation, machine learning, modeling and forecasting socio-economic processes, and the development of artificial intelligence methods. She actively contributes to cutting-edge research in cyber-physical systems, and has led or participated in numerous national and international projects, including Erasmus+ initiatives, disinformation detection tools (TruScanAI), and digital heritage visualization through augmented and virtual reality. Her work is known for its interdisciplinary applications, blending technology, economics, and societal impact.

Awards 🏆

While specific named awards are not listed, Dr. Lipianina-Honcharenko’s selection and participation in prestigious European research initiatives such as Erasmus+ “Work4CE”, My Farm, and AURA projects highlight her recognized competence and contribution on an international scale. Her leadership in these multi-national projects reflects her credibility and collaborative skills in the global academic community.

Top Noted Publications 📚

1. Decision Tree Based Targeting Model of Customer Interaction with Business Page
Authors: H. Lipyanina, A. Sachenko, T. Lendyuk, S. Nadvynychny, S. Grodskyi
Index: CMIS
Citations: 37
Year: 2020
Pages: 1001–1012

2. Economic Crime Detection Using Support Vector Machine Classification
Authors: A. Krysovatyy, H. Lipyanina-Goncharenko, S. Sachenko, O. Desyatnyuk
Index: MoMLeT+ DS 2917
Citations: 25
Year: 2021
Pages: 830–840

3. Assessing the Investment Risk of Virtual IT Company Based on Machine Learning
Authors: H. Lipyanina, V. Maksymovych, A. Sachenko, T. Lendyuk, A. Fomenko, I. Kit
Index: International Conference on Data Stream Mining and Processing
Citations: 24
Year: 2020
Pages: 167–187

4. Targeting Model of HEI Video Marketing Based on Classification Tree
Authors: H. Lipyanina, S. Sachenko, T. Lendyuk, A. Sachenko
Citations: 22
Year: 2020

5. Concept of the Intelligent Guide with AR Support
Authors: K. Lipianina-Honcharenko, R. Savchyshyn, A. Sachenko, A. Chaban, I. Kit, et al.
Index: International Journal of Computing, Vol. 21, No. 2
Citations: 19
Year: 2022
Pages: 271–277

Conclusion

Assoc. Prof. Dr. Khrystyna Lipianina-Honcharenko exemplifies the qualities of a committed young scientist, with a diverse academic background, substantial international research experience, and a clear focus on interdisciplinary innovation. Her growing portfolio of research, especially in AI and cyber-physical systems, makes her a highly suitable candidate for prestigious recognitions such as the Research for Young Scientist Award. With continued development in international communication and publication outreach, she is well-positioned to make an even broader impact in the global scientific arena.

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

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.