Shankar Patil | Block Chain | Best Researcher Award

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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.

 

Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award-7820

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Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award

Mr. Shishir Tewari | Computer Science – Senior Manager at Procore Technologies, United States

Shishir Tewari is a distinguished technology leader and Senior Engineering Manager, renowned for his pioneering work in data engineering, AI/ML, and business intelligence systems. With a professional journey spanning nearly two decades, he has made significant contributions to building robust data platforms, streamlining enterprise analytics, and mentoring high-performing engineering teams across some of the world’s top tech firms including Google, Amazon, and Procore Technologies. His forward-thinking approach to intelligent data infrastructure, combined with his proficiency in cloud ecosystems and scalable processing frameworks, has set new benchmarks in operational excellence and digital innovation. Tewari stands out as a forward-thinking engineer and strategic visionary who continuously transforms data into actionable intelligence.

✅🧑‍💼 Professional Profile Verified

Google Scholar

🎓 Education

Tewari’s strong academic foundation has enabled his seamless navigation through complex data and technology landscapes. He earned his Bachelor of Technology degree in Information Technology from U.P.T.U., India (2002–2006), graduating with a commendable performance. To further specialize in the burgeoning field of analytics, he pursued a Data Science and Analytics specialization at Rutgers University, New Jersey (2018–2019). This academic combination has empowered him to integrate advanced analytical methodologies with practical problem-solving in enterprise settings, giving him a competitive edge in today’s data-centric economy.

💼 Experience

With more than 19 years of hands-on experience, Shishir Tewari has held progressively senior roles at globally respected organizations. At Procore Technologies, where he currently serves as Senior Manager, Data Engineering, he led the development of a next-gen Master Data Management and Marketing Analytics platform enriched by AI/ML, enhancing organizational data consistency and insight. Previously at Google, he managed a global team and optimized financial data processing pipelines across Google Finance, handling 100+ petabytes on GCP. His role at Amazon involved constructing large-scale advertising data infrastructure in AWS, directly supporting over $100M in revenue. During his earlier years at Morgan Stanley, JP Morgan Chase, Panasonic, and Tata Consultancy Services, Tewari built scalable ETL pipelines, optimized legacy systems, and created advanced business intelligence frameworks. Each of these roles reflects his unwavering commitment to excellence in data operations, architecture, and leadership.

🔬 Research Interest

Tewari’s research interests lie at the intersection of data engineering, artificial intelligence, and automation. He is particularly passionate about leveraging machine learning to optimize data quality, processing, and decision-making at enterprise scale. His work focuses on improving the performance of large-scale distributed systems, integrating data governance frameworks, and implementing real-time analytics. He is equally invested in enhancing business intelligence solutions through AI-driven innovation, and his hands-on experience with platforms like AWS, GCP, and Databricks has empowered him to experiment with scalable applications of AI in modern enterprises.

🏆 Awards

Shishir Tewari’s groundbreaking work has been recognized globally through several prestigious awards. He received the 2025 Global Leader Award for Excellence in AI/ML-Driven Data Engineering, honoring his transformative contributions to intelligent automation. In 2024, he was the recipient of the ISTRA International Outstanding Technical/Digital Innovation Award for his role in driving technical innovation in AI and Data Engineering. He also earned the 2025 TITAN Business Awards – Gold Winner title in the Artificial Intelligence category for his strategic leadership and engineering excellence. Further recognition came with his inclusion in the Marquis Who’s Who Biographical Listee, highlighting his impact on global technological advancement.

📚 Publications

Tewari has made valuable scholarly contributions to the AI and data engineering community through multiple publications that reflect his expertise and thought leadership. His book, “AI-Driven Enterprise: Scaling Business Success” (2024), offers insightful frameworks for integrating AI into business operations and is available on Amazon. He has authored/co-authored 7 peer-reviewed articles, collectively cited 30 times, underscoring his influence in the academic domain. Selected key publications include:

  • “AI-Driven Master Data Governance for Enterprise Systems” 📘 (2023, Journal of Data Science), cited by 6
  • “Optimizing Cloud Data Warehouses Using ML Models” ☁️ (2023, Big Data Research), cited by 5
  • “Real-Time Analytics in Distributed Finance Systems” 💹 (2022, Financial Computing Review), cited by 4
  • “AI-Powered Marketing Insights Platform: A Scalable Framework” 📊 (2021, International Journal of AI and Data), cited by 6
  • “Data Lakehouse Implementation and Business Impact” 🌊 (2021, Information Systems Journal), cited by 3
  • “Ethical AI in Data Engineering” 🧠 (2020, Journal of Ethics in Technology), cited by 4
  • “Performance Engineering for ETL Pipelines Using Spark” 🔥 (2019, Data Engineering Review), cited by 2

These publications reflect his practical insight into enterprise data systems and his commitment to bridging theoretical research with real-world engineering applications.

✅ Conclusion

In conclusion, Shishir Tewari exemplifies excellence in data engineering, AI/ML innovation, and digital transformation leadership. His visionary mindset, technical expertise, and consistent delivery of impactful solutions have earned him a well-respected place among global leaders in technology. Whether architecting petabyte-scale infrastructures, mentoring next-generation engineers, or judging international innovation awards, Tewari’s work consistently elevates the standards of modern enterprise engineering. Through his continued research, leadership, and commitment to excellence, he remains a driving force in shaping the future of AI-powered data ecosystems.

Perepi Rajarajeswari | Computer science | Best Researcher Award

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Dr. Perepi Rajarajeswari | Computer science | Best Researcher Award

Associate professor at Vellore Institute of Technology, India

Dr. Perepi Rajarajeswari, an accomplished academician and researcher, holds an impressive academic background, with a PhD in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad. She is currently an Associate Professor in the Department of Software Systems, School of Computer Science and Engineering at Vellore Institute of Technology (VIT), Tamil Nadu. With vast teaching experience in diverse computer science disciplines, Dr. Rajarajeswari has made notable contributions to fields like Blockchain technology, Software Engineering, Data Mining, Artificial Intelligence, and Internet of Things, among others. Over the years, she has garnered respect for her knowledge and expertise in both teaching and research.

Profile:

Google scholar

Education:

Dr. Rajarajeswari’s academic journey began with a Bachelor’s degree (B.Tech) in Computer Science from Sri Venkateswara University, Tirupati, in 2000. She then completed her Master of Technology (M.Tech) in Computer Science at Jawaharlal Nehru Technological University, Hyderabad, in 2008. Dr. Rajarajeswari earned her Ph.D. in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, in 2017. Her educational background has equipped her with a solid foundation in the ever-evolving field of computer science.

Experience:

Dr. Rajarajeswari has a distinguished career as an educator and researcher. She began her career as a lecturer at Madanapalle Institute of Technology and Science in 2000. Over the years, she has progressively advanced in academia. From Assistant Professor to Associate Professor, she has worked at various reputed institutions, including Madanapalle Institute of Technology and Science, Aditya College of Engineering, Kingston Engineering College, and Sreenivasa Institute of Technology and Management Studies. Since 2022, Dr. Rajarajeswari has been serving as an Associate Professor at VIT, contributing significantly to both research and academic development. Her wide-ranging experience in teaching and research has made her a pivotal figure in her academic community.

Research Interests:

Dr. Rajarajeswari’s research interests are multi-disciplinary and encompass cutting-edge areas in computer science and engineering. Her expertise spans Blockchain technology, Software Engineering, Software Architecture, Data Mining, Artificial Intelligence, Cloud Computing, and the Internet of Things. She is particularly passionate about exploring the intersections of these technologies, such as Mobile Cloud Computing and Cyber-Physical Systems, and their real-world applications. Her focus on advanced computational techniques aims to address complex problems in fields such as healthcare, smart systems, and secure architectures.

Awards:

Dr. Rajarajeswari’s work has been recognized by various academic and professional organizations. While specific awards are not detailed, her commitment to excellence in education, research, and innovation has earned her the respect of peers and students alike. Her contributions to sponsored projects and her active participation in research have placed her at the forefront of her field.

Publications:

Dr. Rajarajeswari has authored several influential publications in reputed journals and conferences. Some of her key publications include:

  1. “Thermomagnetic Bioconvection Flow in a Semi trapezoidal Enclosure Filled with a Porous Medium Containing Oxytactic Micro-Organisms: Modeling Hybrid Magnetic Biofuel Cells,” ASME Journal of Heat and Mass Transfer, SCIE Journal, 2025.

  2. “Finite Element Numerical Simulation of Free Convection Heat Transfer in a Square Cavity Containing an Inclined Prismatic Obstacle with Machine Learning Optimization,” Heat Transfer-Wiley, 2025.

  3. “Magneto-convective flow in a differentially heated enclosure containing a non-Darcy porous medium with thermal radiation effects—a Lattice Boltzmann simulation,” Journal of the Korean Physical Society, 2025.

  4. “Deep Learning Techniques for Lung Cancer Recognition,” Engineering, Technology & Applied Science Research, 2024.

  5. “Prediction of Heart Attack Risk and Detection of Sleep Disorders Using Deep Learning Approach,” International Research Journal of Multidisciplinary Scope, 2024.

  6. “Object Oriented Design Approach for the Implementation of Secure Aircraft Management System Based on Machine Learning,” Nanotechnology Perceptions, 2024.

  7. “A Deep Learning Computational Approach for the Classification of COVID-19 Virus,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022.

Her works have been cited by numerous scholars, contributing significantly to advancing research in computational intelligence, data mining, and machine learning.

Conclusion:

Dr. Perepi Rajarajeswari’s academic achievements and research contributions underscore her dedication to advancing the field of Computer Science and Engineering. Her diverse experience, coupled with her deep understanding of contemporary technological issues, places her as a leader in her domain. With a passion for teaching and a commitment to solving real-world problems, Dr. Rajarajeswari continues to inspire students and researchers alike. Through her ongoing work in research and development, she is poised to make further impactful contributions in the fields of AI, Blockchain, Cloud Computing, and more.

Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award

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Prof. Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award 

Professor | University of Paris 8 | France

Based on the detailed profile of Prof. Dr. Larbi Boubchir, here is an analysis of his suitability for the Research for Best Scholar Award, focusing on his strengths, areas for improvement, and a concluding assessment.

Strengths

  1. Extensive Research Contributions: Prof. Boubchir has authored and co-authored over 100 publications, which highlights his prolific output and active engagement in research. His work spans a broad range of topics including artificial intelligence, biometrics, biomedical signal processing, and image processing, demonstrating significant expertise across multiple domains.
  2. Leadership and Organizational Roles: He holds several prominent positions, such as Full Professor, Deputy Director of LIASD, and Head of multiple Master’s programs. His roles in organizing and chairing international workshops and conferences further illustrate his leadership and influence in the academic community.
  3. Recognition and Awards: His achievements include being recognized as an Outstanding Associate Editor by IEEE Access, receiving Best Paper and Best Poster awards, and contributing to notable international research projects. These accolades reflect the high quality and impact of his research.
  4. Diverse Teaching Experience: Prof. Boubchir has a robust teaching background, covering various levels and subjects in computer science, signal and image processing, and artificial intelligence. His pedagogical responsibilities and contributions to curriculum development at several institutions underscore his commitment to education.
  5. Multidisciplinary Research: His work in areas like biometric recognition, biomedical signal processing, and artificial intelligence for cybersecurity highlights his interdisciplinary approach and innovative contributions to multiple fields.

Areas for Improvement

  1. Interdisciplinary Collaboration: While Prof. Boubchir’s research is broad, further collaboration with researchers from different disciplines could enhance the application and impact of his work. For example, integrating perspectives from cognitive sciences or behavioral studies might enrich his research in biometrics and artificial intelligence.
  2. Involvement in Emerging Technologies: Although his research is cutting-edge, staying abreast of emerging technologies such as quantum computing or new AI paradigms could provide additional opportunities for groundbreaking research and keep his work at the forefront of technological advancements.
  3. Increased Focus on Applied Research: While his theoretical and methodological contributions are significant, emphasizing applied research that directly addresses real-world problems and demonstrates practical outcomes could enhance the societal impact of his work.

Short Biography

Prof. Dr. Larbi Boubchir is a distinguished Full Professor of Computer Science at the University of Paris 8, France. With a notable career spanning several institutions, including CNRS and Northumbria University, he has made significant contributions to the fields of artificial intelligence, biometrics, and biomedical signal processing. His role as Deputy Director of the LIASD laboratory and Head of multiple Master’s programs underscores his leadership and influence in both research and education. Prof. Boubchir’s extensive experience in organizing international workshops and conferences further highlights his active engagement with the global academic community.

Profile

ORCID

Education

Prof. Boubchir earned his PhD in Signal and Image Processing from the University of Caen-Basse Normandie in 2007, following a Master of Advanced Studies in Computer Science from Polytech’Tours, University of François-Rabelais, Tours, in 2002. In 2019, he completed his Habilitation à Diriger des Recherches (HDR) at the University of Paris 8, which qualifies him to supervise doctoral research in Computer Science.

Experience

Prof. Boubchir has held numerous academic positions throughout his career. He has been a Full Professor at the University of Paris 8 since 2021, where he also serves as Deputy Director of the LIASD research lab and heads several Master’s programs. Prior to this, he was an Associate Professor at the same institution and held research fellowships at Northumbria University, CNRS, and Qatar University. His diverse teaching experience spans institutions in France, the UK, and Qatar, and includes a range of subjects from computer programming to artificial intelligence.

Research Interests

Prof. Boubchir’s research interests encompass biometrics, artificial intelligence, biomedical signal processing, and image processing. His work involves developing algorithms for biometric recognition, feature engineering, and deep learning applications in biomedical data analysis. He is particularly focused on applications such as biometric authentication, epilepsy detection, and brain-computer interfaces. His interdisciplinary approach combines advanced machine learning techniques with practical applications in security and healthcare.

Awards

Prof. Boubchir has received several prestigious awards, including IEEE Access Outstanding Associate Editor honors (2020, 2021, 2023) and the Best Paper award at the 39th International Conference on Telecommunications and Signal Processing (2016). He also won the Best Poster Award at the 9th International Conference on Software Defined Systems (2022) and achieved recognition for his top papers at IEEE conferences.

Publications

Here are some of Prof. Boubchir’s notable publications:

A Review on Deep Anomaly Detection in Blockchain (2024), Blockchain: Research and Applications.

Enhancing 2D-3D Facial Recognition Accuracy of Truncated-Hidden Faces Using Fused Multi-Model Biometric Deep Features (2024), Multimedia Tools and Applications.

Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control (2023), International Journal of Advanced Computer Science and Applications (IJACSA).

Efficient Multiplier-Less Parametric Integer Approximate Transform Based on 16-Points DCT for Image Compression (2022), Multimedia Tools and Applications.

Lossy Image Compression Based on Efficient Multiplier-Less 8-Points DCT (2022), Multimedia Systems.

EEG Signal Feature Extraction and Classification for Epilepsy Detection (2022), Informatica.

Detecting African Hoofed Animals in Aerial Imagery Using Convolutional Neural Network (2021), IAES International Journal of Robotics and Automation.

Palm Vein Recognition Based on Competitive Coding Scheme Using Multi-Scale Local Binary Pattern with Ant Colony Optimization (2020), Pattern Recognition Letters.

A Novel and Efficient 8-Point DCT Approximation for Image Compression (2020), Multimedia Tools and Applications.

EEG Epileptic Seizure Detection and Classification Based on Dual-Tree Complex Wavelet Transform and Machine Learning Algorithms (2020), Journal of Biomedical Research.

Conclusion

Prof. Dr. Larbi Boubchir is highly suitable for the Research for Best Scholar Award. His impressive research portfolio, leadership roles, teaching contributions, and recognition from the academic community illustrate his exceptional qualifications. His diverse expertise and significant impact in fields such as artificial intelligence, biometrics, and biomedical signal processing make him a strong candidate for this award. To further strengthen his profile, focusing on interdisciplinary collaborations, emerging technologies, and applied research could provide additional avenues for innovation and impact. Overall, Prof. Boubchir’s accomplishments and contributions make him a distinguished candidate deserving of recognition.

Sajad Zandi | Distributed Network | Best Researcher Award

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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