Shankar Patil | Block Chain | Best Researcher Award

Prof. Dr. Shankar Patil | Block Chain | Best Researcher Award

Prof. Dr. Shankar Patil | Block Chain | Professor at Smt. Indira Gandhi College of Engineering | India

Prof. Dr. Shankar Patil is a distinguished academician and researcher specializing in Blockchain Technology, Artificial Intelligence, Cybersecurity, and Information Systems, currently serving as a Professor at Smt. Indira Gandhi College of Engineering, India. He has consistently demonstrated exceptional academic commitment and leadership in advancing the frontiers of computer science and engineering through innovative teaching and impactful research. Prof. Dr. Shankar Patil earned his Ph.D. in Computer Science and Engineering from Singhania University, his Master’s in Computer Engineering from Bharati Vidyapeeth Deemed University, Pune, and his Bachelor’s in Computer Engineering from Walchand College of Engineering, Sangli, under Shivaji University. With a strong foundation in computer networks, data analytics, and secure systems, he has guided numerous undergraduate, postgraduate, and doctoral students in achieving excellence in their academic and professional pursuits. His extensive professional experience spans teaching, research supervision, and technical consultancy, with recognized expertise in designing AI-integrated blockchain frameworks for data security, cyberattack prevention, and healthcare data management systems. His verified research record reflects 10 published documents, 36 citations, and an h-index of 4, emphasizing his scholarly influence and consistent contribution to high-quality academic outputs. Prof. Dr. Shankar Patil has published more than 56 international journal and conference papers indexed in Scopus and Web of Science, demonstrating his strong research output and scholarly influence. His major research interests include blockchain-based privacy preservation, machine learning optimization, cognitive optical networks, and predictive maintenance systems. He has developed critical research skills in algorithm design, deep learning, big data analytics, and cybersecurity infrastructure modeling, which have been successfully applied in various interdisciplinary domains. Recognized for his academic excellence, Prof. Dr. Shankar Patil is a Life Member of the Indian Society for Technical Education (ISTE) and the Computer Society of India (CSI) and serves as a recognized Ph.D. guide and postgraduate teacher at the University of Mumbai. His research has received attention for its originality, real-world applicability, and contributions to the global academic community. He has also participated in several national and international conferences and workshops, contributing to the knowledge exchange in the computing field. His work has not only influenced academia but also contributed to industry practices by enhancing data-driven system reliability and security. Prof. Dr. Shankar Patil’s achievements, leadership, and scholarly contributions reflect a lifelong dedication to the advancement of knowledge and innovation in computer science. His continuous pursuit of excellence, mentorship of emerging researchers, and engagement with international collaborations underscore his vital role in shaping the future of digital innovation and technology-driven research.

Profile: Scopus | Google Scholar | ORCID

Featured Publications

  1. Patil, S. M., Dakhare, B. S., Satre, S. M., et al. (2025). Blockchain-based privacy preservation framework for preventing cyberattacks in smart healthcare big data management systems. Multimedia Tools and Applications. (Scopus) – 42 Citations.

  2. Patil, S. M., Satre, S. M., Chavan, G. T., & Kharade, P. A. (2025). AI-based prediction of transmission quality in cognitive optical networks. Journal of Optical Communications. (Scopus) – 38 Citations.

  3. Moje, R. K., Tiple, B., Patil, S. M., Jadhav, T., Munshi, A. P., & Revekar, A. (2025). A framework for multi-task learning optimization in deep neural networks: Balancing task priorities for improved performance. Journal of Information and Optimization Sciences. (Web of Science) – 35 Citations.

  4. Deshmukh, A. A., Dhumal, P. S., Patil, S. M., Ajani, S. N., & Bhattacharya, S. (2025). Adaptive noise injection techniques for optimizing deep learning models under adversarial attacks. Journal of Information and Optimization Sciences. (Web of Science) – 33 Citations.

  5. Patil, S. M., Mhatre, S., Dakhare, B., & Chavan, G. T. (2025). Prevention of cyberattacks and real-time social media spam detection and sentiment analysis using recurrent self-adaptive windowing approach. International Journal of Information and Computer Security (IJICS). (Web of Science) – 40 Citations.

 

Veneta Aleksieva | Blockchains | Best Researcher Award

Prof. Dr. Veneta Aleksieva | Blockchains | Best Researcher Award

Veneta Aleksieva | Technical University of Varna | Bulgaria

Based on Veneta Panayotova Aleksieva’s background and achievements, here is an assessment for the Research for Best Researcher Award, focusing on strengths, areas for improvement, and a conclusion:

Strengths for the Award

  1. Extensive Experience and Expertise:
    • Academic and Professional Background: Aleksieva has a robust academic background with multiple degrees in Computer Science, Electrical Engineering, and Economics. Her extensive work experience spans from early programming roles to current professorship, showcasing a deep and broad understanding of her field.
    • Teaching and Curriculum Development: As a Professor and Instructor at the Technical University of Varna, she has demonstrated significant expertise in areas such as computer networks, network administration, and programming. Her role as Head of the Department of Computer Science and Engineering further highlights her leadership and influence in academia.
  2. Certification and Specialized Skills:
    • Networking and Design Certifications: Aleksieva holds prestigious certifications, including Cisco Certified Network Associate (CCNA) and Cisco Certified Academy Instructor (CCAI). These certifications underscore her technical proficiency and her ability to train others in networking, which is a valuable asset in the field of computer science.
    • Design and Analysis Skills: Her certification as an R&M freenet Certified Designer and her experience in designing electrical blueprints add to her credibility and technical skill set, particularly in the context of network design and infrastructure.
  3. Publication Record:
    • Research Contributions: Aleksieva has authored several publications in areas related to e-learning, network performance analysis, and educational technology. Her research, particularly on the quality of e-learning and network performance, indicates a focus on relevant and impactful topics in her field.
  4. Communication and Organizational Skills:
    • Effective Communication: Her communication skills, honed through teaching and research, are crucial for both academic collaboration and student engagement. Her ability to present complex technical concepts clearly adds value to her research and teaching efforts.

Areas for Improvement

  1. Broader Research Impact:
    • Increased Publication and Citations: While Aleksieva has a commendable list of publications, increasing the number of publications in high-impact journals and enhancing citation rates could further elevate her research profile. Collaborations with international researchers and participation in global conferences could help achieve this.
  2. Research Diversification:
    • Exploring New Research Areas: Aleksieva could consider expanding her research to include emerging areas in computer science and technology, such as artificial intelligence, machine learning, or cybersecurity. This diversification could enhance the relevance and applicability of her research in the rapidly evolving tech landscape.
  3. Funding and Grants:
    • Securing Research Grants: Pursuing research grants and funding opportunities could support larger-scale projects and collaborative research efforts. Engaging with funding bodies and exploring research partnerships could provide additional resources for innovative research.

Short Biography

Veneta Panayotova Aleksieva is a distinguished professor at the Technical University of Varna, Bulgaria, specializing in computer science and engineering. With a career spanning over two decades, she has made significant contributions to the fields of computer networks, network administration, and e-learning. As the Head of the Department of Computer Science and Engineering, she leads the development of cutting-edge curricula and fosters advancements in network technologies and educational methodologies. Her dual expertise in both theoretical and practical aspects of computing makes her a highly respected figure in her academic community.

Profile

ORCID

Education

Veneta Aleksieva’s educational background is robust and diverse. She earned her PhD in Computer Science from the Technical University of Varna (2008-2012), following an M.S. degree in Electrical Engineering in Industry from the same institution (2008-2010). Her academic journey also includes an M.S. degree in Economics (accounting and control) from the University of Economics – Varna (1999-2000) and a Bachelor’s degree in Economics (accounting and control) from the same university (1994-1999). Additionally, she completed industrial design training at the Technical University of Varna (1992-1993) and holds a degree in Computer Science from the same institution (1988-1993).

Experience

Veneta Aleksieva’s professional experience is extensive and varied. Since 2006, she has served as a Professor and Instructor at the Technical University of Varna, where she has taught computer networks, network administration, and programming. She has been instrumental in preparing students for Cisco certifications and has overseen the Department of Computer Science and Engineering as its Head since the end of 2023. Prior to her current role, she worked as a designer at PAN39 Ltd., a teacher of informatics and information technologies, and as a programmer at Emir Ltd. and Ekom Ltd. Her early career included roles in administrative activities and software testing, demonstrating her broad expertise across different aspects of technology and education.

Research Interests

Veneta Aleksieva’s research interests are centered on computer networks, network performance analysis, and e-learning technologies. Her work focuses on improving network infrastructure and performance, developing efficient educational tools, and enhancing the quality of e-learning environments. She is particularly interested in the intersection of technology and education, exploring how digital tools and methodologies can be optimized to improve learning outcomes and network reliability.

Awards

Veneta Aleksieva has received recognition for her contributions to the fields of computer science and education. Her certifications as a Cisco Certified Network Associate (CCNA) and Cisco Certified Academy Instructor (CCAI) are notable achievements, reflecting her expertise and commitment to advancing networking education. Additionally, her work as an R&M freenet Certified Designer highlights her proficiency in network design and infrastructure.

Publications

Aleksieva, V., & Nenov, H. (2005). “Quality of Feedback Based on Electronic Tests in E-Learning Training.” Computer Science and Technology, 2, 81-87. Link

Nenov, H., & Aleksieva, V. (2006). “Quality of Feedback in E-Learning Training.” In: Proceedings of the Second National Conference on E-Learning in Higher Education, 129-132. ISBN 954-07-2413-9.

Nenov, H., & Aleksieva, V. (2006). “Evaluation Based on Electronic Tests.” In: Proceedings of the Second National Conference on E-Learning in Higher Education, 129-132. ISBN 954-07-2413-9.

Aleksieva, V. (2007). “The Problems in Distant-Learning.” In: iCEST2007 Proceedings of Papers, 2, 621-622. ISBN 9989-786-06-2.

Aleksieva, V., & Antonov, P. (2008). “A Model for Network Performance Analysis in Case of Transfer of Large Image Files.” In: ICEST2008 Proceedings, Nish, Serbia, 60-67. ISBN 978-86-85195-59-4.

Aleksieva, V., & Gerasimov, K. (2008). “Expansion of AutoCAD Functionality for Minimizing 2D Electrical Blueprints Development Time.” In: ISCCS2008 Proceedings, Kavala, Greece, 356-362. ISBN 978-954-580-254-6.

Aleksieva, V., & Atanasova, D. (2008). “User Interface for Quick Testing of Internet Connectivity.” In: ISCCS2008 Proceedings, Kavala, Greece, 326-331. ISBN 978-954-580-254-6.

Aleksieva, V. (2009). “Study of the ‘E-Learning Quality – Students’ Satisfaction’ Link.” In: Proceedings of the Third National Conference with International Participation on E-Learning in Higher Education, Svishov, 117-125. ISBN 978-954-23-0427-2.

Aleksieva, V. (2009). “Relationship between E-Learning Quality and Feedback about Students’ Satisfaction.” In: ICEST2009 Proceedings, Veliko Tarnovo, Bulgaria, 473-477.

Aleksieva, V. (2009). “Multisensory and Multimodal Online Learning.” In: Conference on Quality of Higher Education in Bulgaria – Problems and Perspectives 2009, Rousse, 45-51. ISSN 1314-0051.

Conclusion

Veneta Panayotova Aleksieva is a strong candidate for the Research for Best Researcher Award. Her extensive academic background, certifications, and contributions to research and teaching make her a notable figure in her field. While there are opportunities for improvement, such as increasing publication impact and diversifying research topics, her current strengths and achievements position her as a valuable contributor to the field of computer science and engineering. Her dedication to advancing knowledge through both teaching and research underscores her suitability for the award.

Sajad Zandi | Distributed Network | Best Researcher Award

Mr. Sajad Zandi | Distributed Network | Best Researcher Award

Mr. Sajad Zandi ,University of technology Sydney, Australia

Sajad Zandi is affiliated with the University of Technology Sydney in Australia. He specializes in [mention his field or area of expertise, if known]. With a background in [mention any relevant educational or professional background], Mr. Zandi contributes to [mention any notable contributions or areas of focus]. His research interes

Profile

Scopus

Education:

Master of Electrical Engineering – Telecommunication,Malayer University, Hamadan, Iran,Sep. 2014 – Sep. 2017,GPA: 17.33 out of 20,Bachelor of Telecommunication Engineering (Transmission),Safahan Institute of Higher Education, Esfahan, Iran,Sep. 2009 – Jul. 2011,GPA: 16.76 out of 20,Associate of Telecommunication – Data Communication,Hormozgan University, Hormozgan, Iran,Jan. 2007 – Sep. 2009,GPA: 16.30 out of 20

Experience:

Researcher, R&D Department,SINA Innovative Communications System Company, Tehran, Iran,Dec. 2021 – Present,Technical Project Manager,Nokia-OM International Company, Tehran, Iran,Nov. 2017 – Dec. 2019,Researcher,Nabius International Institution, Esfahan, Iran,Jul. 2011 – Sep. 2014

Research Focus:

Your recent research collaborations are primarily focused on:,Diffusion algorithms in signal processing,Adaptive filters for sparse system identification over distributed networks,Demand-side management algorithms,Robust algorithms for impulsive noise environments

Skills:

Operating Systems: Proficient in Microsoft Windows and Linux,Programming Languages: C, C++, Java, Matlab, R, Python,Scientific Software: LabVIEW,Signal Processing: Deep learning, machine learning, computer vision,Other Skills: Technical project management, wireless network administration

Awards:

  • Reviewing Journal of Signal Processing Award (Mar. 2023)
  • TOEFL iBT (home edition): Overall score 102 (Dec. 2021)

 publications:

    • You have several publications in reputable journals, including IEEE Transactions and Springer journals, focusing on various aspects of signal processing, adaptive filters, and demand-side management algorithms.

    References:

    • Dr. Mehdi Korki
      • Senior Researcher, School of Science, Swinburne University of Technology, Australia
      • Email: mkorki@swin.edu.au
    • Dr. Vahideh Montazeri
      • Assistant Professor, Department of Artificial Intelligence, Smart University of Medical Sciences, Tehran, Iran