Joseph Squillace | Cybersecurity | Global Scientific Impact Award

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Dr. Joseph Squillace | Cybersecurity | Global Scientific Impact Award

Associate Professor | The Pennsylvania State University | United States

Dr. Joseph Michael Squillace is an Assistant Professor of Cybersecurity at Penn State University, Schuylkill, specializing in information security, privacy, cyber policy management, and cybersecurity education. He holds a Ph.D. in Information Systems from Nova Southeastern University, where his doctoral research examined corporate investments in privacy, along with master’s and bachelor’s degrees in computer information systems and information technology, both with concentrations in cybersecurity and network engineering. Dr. Squillace’s professional contributions span leadership in cybersecurity pedagogy, research project management, and the development of educational frameworks focused on cyber awareness, ethical computing, and privacy protection. His research explores areas including cyberbullying prevention, artificial intelligence vulnerabilities, privacy inequality, and the cybersecurity of critical infrastructure, with numerous peer-reviewed publications in leading international journals and conferences. He has successfully secured significant research funding from federal agencies and international organizations, advancing cyber education and public safety initiatives. Dr. Squillace has been honored with multiple institutional and national awards recognizing excellence in teaching, research, and community engagement, and he has served as a keynote speaker, visiting professor, and academic fellow for cybersecurity organizations across Europe and the United States. His interdisciplinary work continues to shape the intersection of technology, governance, and human behavior in building secure and equitable digital environments.

Profiles: Google Scholar | ORCID

Featured Publications

  1. 1. Squillace, J., Hozella, Z., Cappella, J., & Sepp, A. (2023). An exploration of SETA in cyber bullying to reduce social harm and juvenile suicide. IEEE World AI IoT Congress (AIIoT), 477–480.

    2. Squillace, J., Cappella, J., & Sepp, A. (2024). User vulnerabilities in AI-driven systems: Current cybersecurity threat dynamics and malicious exploits in supply chain management and project management. ASU International Conference in Emerging Technologies for Industry 4.0.

    3. Bantan, M., & Squillace, J. (2022). Privacy inequality and IT identities: The impact of different privacy laws adoptions. Journal of Information Privacy and Security.

    4. Squillace, J., & Cappella, J. (2024). Examining how targeted cyber attacks on critical supply chain networks can lead to economic collapse and civil unrest. IEEE SoutheastCon, 1482–1489.

    5. Squillace, J., & Bantan, M. (2022). A taxonomy of privacy, trust, and security breach incidents of Internet-of-Things linked to F (M). AANG corporations. IEEE World AI IoT Congress (AIIoT), 591–596.

Shishir Tewari | Computer Science | Technology and Innovation Leadership Award

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Mr. Shishir Tewari | Computer Science | Technology and Innovation Leadership Award

Senior Manager, Data Engineering at Procore Technologies, United States

Shishir Tewari is a seasoned technology leader with over 19 years of experience driving innovation in data engineering, data warehousing, and analytics across top-tier organizations such as Google, Amazon, Morgan Stanley, and Microsoft. He currently leads strategic data initiatives at Procore Technologies, where he has spearheaded the development of AI/ML-driven platforms, cloud migrations, and real-time analytics systems. Known for his expertise in building scalable, high-performance data solutions, Shishir has successfully led global engineering teams and transformed complex data ecosystems on AWS, GCP, and Databricks. His technical vision, operational excellence, and commitment to data quality and governance have consistently delivered measurable business value. Shishir’s continuous pursuit of innovation and deep cross-functional leadership make him a standout contributor in the technology landscape. With a strong foundation in data science, cloud architecture, and team mentorship, he exemplifies the qualities of a forward-thinking, impact-driven technology leader worthy of recognition.

Professional Profile 

Google Scholar

Education

Shishir Tewari holds a Bachelor of Technology in Information Technology from U.P.T.U., India, graduating in 2006. Demonstrating a commitment to lifelong learning and innovation, he further enhanced his credentials with a specialization in Data Science and Analytics from Rutgers University, New Jersey, in 2018–2019. This advanced academic training equipped him with modern analytical techniques, machine learning algorithms, and statistical modeling—skills that have been instrumental in his professional success. His educational background lays a strong foundation for his technical leadership, blending theoretical knowledge with real-world application. The combination of engineering fundamentals and data science expertise positions Shishir as a well-rounded technology leader who can bridge the gap between innovation and implementation in enterprise environments.

Professional Experience

Shishir Tewari brings over 19 years of robust experience across global technology firms, including Google, Amazon, Morgan Stanley, Microsoft, and currently, Procore Technologies. His career spans technical leadership, large-scale data architecture, and cloud-native platform innovation. At Google, he led a global team optimizing financial data pipelines and infrastructure. At Amazon, he designed high-performance advertising data systems, enabling substantial revenue impact. At Procore, he has driven major initiatives including AI/ML-powered data platforms and cloud migrations. His ability to manage large engineering teams, align data strategy with business goals, and optimize performance at scale reflects his leadership maturity. Shishir’s diverse experience across industries—finance, tech, construction, and advertising—gives him a unique, cross-sector perspective on data-driven transformation.

Research Interest

Shishir Tewari’s research interests lie at the intersection of big data engineering, AI/ML-driven analytics, and cloud computing. He is particularly passionate about optimizing large-scale data systems for performance, governance, and real-time decision-making. With practical expertise in cloud platforms like AWS, GCP, and Databricks, his focus is on leveraging modern data stacks and open-source technologies to power next-generation analytics and automation. He is also interested in the application of machine learning for master data management, anomaly detection, and predictive modeling within business intelligence ecosystems. While not rooted in academic publishing, his work consistently applies research principles to solve real-world business problems, delivering measurable impact. Future interests include exploring the integration of generative AI with enterprise data platforms and advancing data democratization through self-service analytics tools.

Award and Honor

While specific awards and honors are not listed in his profile, Shishir Tewari’s consistent elevation to senior technical and leadership roles in globally respected organizations serves as a testament to his excellence and recognition within the industry. Being entrusted with mission-critical projects at Google, Amazon, and Morgan Stanley speaks to his reliability, vision, and execution skills. His role in leading high-visibility initiatives such as financial data certification, AI/ML-driven analytics platforms, and major cloud migrations reflects the high degree of trust and credibility he commands. He has likely received internal accolades for his contributions to performance optimization, cost reduction, and innovation. A nomination for a Technology and Innovation Leadership Award would further formalize and honor his significant contributions to data-driven transformation and technological advancement in enterprise settings.

Conclusion

Shishir Tewari exemplifies the qualities of a forward-thinking technology leader, with deep expertise in data engineering, cloud architecture, and strategic innovation. His two-decade-long career reflects a commitment to excellence, from hands-on development to executive-level leadership. With advanced training in data science, he brings both theoretical rigor and practical vision to his work. His impactful roles at top-tier organizations demonstrate his ability to lead cross-functional teams, optimize large-scale systems, and implement transformative technologies. Passionate about leveraging AI/ML and cloud platforms to drive business value, Shishir’s professional journey is marked by continuous learning and measurable outcomes. He stands out as a prime candidate for recognition through a Technology and Innovation Leadership Award, not only for his technical contributions but also for his ability to inspire, mentor, and lead organizations into the future of data-driven innovation.

Publications Top Notes

  1. Title: AI Powered Data Governance – Ensuring Data Quality and Compliance in the Era of Big Data
    Authors: S. Tewari
    Year: 2025

  2. Title: Operationalizing Explainable AI in Business Intelligence: A Blueprint for Transparent Enterprise Analytics
    Authors: A. Chitnis, S. Tewari
    Year: 2024

  3. Title: AI and Multi-Cloud Compliance: Safeguarding Data Sovereignty
    Authors: S. Tewari, A. Chitnis
    Year: 2024

  4. Title: Scalable Metadata Management in Data Lakes Using Machine Learning
    Authors: S. Tewari
    Year: 2023
    Citation: (Update needed)

  5. Title: AI-Powered Financial Forecasting: Enhancing Accuracy with Machine Learning in Enterprise System
    Authors: S. Tewari
    Year: 2023)

  6. Title: Detecting Data Drift and Ensuring Observability with Machine Learning Automation
    Authors: A. Chitnis, S. Tewari
    Year: 2022

  7. Title: Anomaly Detection in Large Scale Data Platforms with Machine Learning
    Authors: S. Tewari
    Year: 2022

  8. Title: Leveraging Graph Based Machine Learning to Analyze Complex Enterprise Data Relationships
    Authors: S. Tewari, A. Chitnis
    Year: 2021

Ammar Odeh | CyberSecurity | Best Researcher Award

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Assoc. Prof. Dr. Ammar Odeh | CyberSecurity | Best Researcher Award

Director of the Training and Consultation Center, Princess Sumaya University for Technology, Jordan

Dr. Ammar M. Odeh is an Associate Professor of Cybersecurity at Princess Sumaya University for Technology (PSUT), Jordan, with extensive experience in teaching, research, and technology development. Specializing in Cybersecurity, AI, and Blockchain, he has contributed significantly to the academic and industrial landscapes. Dr. Odeh earned his Ph.D. in Computer Science and Engineering from the University of Bridgeport, USA, in 2015, receiving the Phi Kappa Phi Award for academic excellence. He is passionate about advancing technological innovation and has been instrumental in designing student training programs, particularly in Cybersecurity. With a career spanning multiple countries, he has worked at universities in Jordan, Oman, Saudi Arabia, and the USA. His research spans Unicode Steganography, Wireless Networks, and Data Security. Dr. Odeh has also collaborated with industry giants such as Huawei and Orange, contributing to the development of advanced cybersecurity systems.

Profile

Google Scholar

Strengths for the Award

  1. Academic Excellence:
    • Dr. Odeh holds a Ph.D. in Computer Science and Engineering (specializing in Cybersecurity), awarded from the University of Bridgeport, USA, in 2015.
    • He has been recognized with multiple prestigious awards, such as the Phi Kappa Phi Award (2015) for academic excellence.
  2. Research Contributions:
    • Dr. Odeh has a strong research portfolio, with significant contributions to topics like steganography, machine learning, blockchain, AI, and cybersecurity. His research work, published in reputable journals and conferences, includes over 15 cited papers and is highly interdisciplinary.
    • Notable contributions include studies on phishing detection, electronic health record security, blockchain in healthcare, and malware detection.
    • He has been cited by multiple research papers and has contributed to advancing the application of technology in the cybersecurity, healthcare, and education sectors.
  3. Teaching and Training:
    • As an Associate Professor, Dr. Odeh’s teaching interests span Programming Languages, Data Communications, Operating Systems, and Cybersecurity, indicating a broad and deep technical skill set.
    • He has also contributed significantly to curriculum design and student training, particularly in Cybersecurity and AI. His role in training and liaising with industry giants like Orange and Huawei speaks to his practical influence in the tech space.
  4. Industry Engagement:
    • His active collaboration with industry players (such as Orange and Huawei) and his leadership of the training committee underscore his ability to bridge academic and practical applications, facilitating a strong link between the university and the tech industry.
    • His expertise in blockchain and AI in real-world contexts, such as healthcare, further illustrates his ability to contribute to and shape industry innovations.
  5. Leadership in Academia:
    • Dr. Odeh has led and participated in multiple academic committees at Princess Sumaya University for Technology (PSUT), including roles in graduation project committees and quality assurance committees. This shows his involvement in shaping the academic landscape and improving institutional practices.
  6. Impact on Research Community:
    • His work in human-computer interaction, steganography, and network security has not only resulted in technical advancements but has also been widely cited, indicating the impact of his research in the academic community.

Areas for Improvement

  1. Broader Collaborative Networks:
    • Although Dr. Odeh has demonstrated significant industry engagement, a broader range of international collaborations could further enhance his research profile. Engaging with top-tier research institutions globally and fostering collaborative international research projects might help him gain more visibility and influence in the global tech community.
  2. Increased Focus on Interdisciplinary Research:
    • While his research covers important aspects of cybersecurity, interdisciplinary approaches—incorporating more fields like social sciences or ethics in AI and cybersecurity—could further elevate his work. This would help address emerging global challenges like the ethical implications of AI, privacy concerns, and digital rights in an increasingly connected world.
  3. Grant and Funding Acquisition:
    • Dr. Odeh’s research portfolio is impressive, but a focus on obtaining large-scale research funding for interdisciplinary projects, especially in AI and cybersecurity, could amplify the impact of his work and provide more opportunities for cutting-edge projects with higher visibility.
  4. Broader Publication Outreach:
    • While his research is well-published, expanding the scope to higher-impact journals or collaborating with industry journals in areas like blockchain, IoT, and advanced AI security could increase the reach and recognition of his work in broader academic and professional circles.

Education 

Dr. Ammar M. Odeh’s academic journey began with a Bachelor’s degree in Computer Science from Hashemite University, Jordan (1999-2002). He then pursued a Master of Computer Science at the University of Jordan (2004-2006), where he honed his expertise in the field. In 2015, he completed his Ph.D. in Computer Science and Engineering at the University of Bridgeport in Connecticut, USA, with a focus on Cybersecurity. His doctoral research contributed to advancements in data security, wireless network protocols, and AI applications in cybersecurity. During his time at the University of Bridgeport, Dr. Odeh was awarded the prestigious Phi Kappa Phi Award for outstanding academic achievement. This academic foundation has enabled him to establish himself as a leading researcher and educator in Computer Science, particularly in the areas of AI, Blockchain, and Cybersecurity.

Experience 

Dr. Ammar M. Odeh has a diverse teaching and research background, with over 15 years of experience across multiple institutions. He currently serves as an Associate Professor in the Department of Computer Science at Princess Sumaya University for Technology (PSUT), Jordan, where he has been since 2019. Prior to his current role, he was an Assistant Professor at PSUT and University of AlMaarefa, Saudi Arabia (2015-2019), where he taught courses on Computer Security, Data Communications, and Programming Languages. Dr. Odeh’s early career included teaching roles at Sur College of Applied Science in Oman (2009-2011) and Philadelphia University in Jordan (2006-2009). He also worked as a Graduate Assistant/Research Assistant at the University of Bridgeport, USA, where he supported cybersecurity research and developed tools for data analysis and project evaluation. His wide-ranging experience in academia has made him a respected leader in his field.

Awards and Honors 

Dr. Ammar M. Odeh has received multiple awards and honors throughout his academic and professional career. Notably, he was awarded the prestigious Phi Kappa Phi Award in 2015 for outstanding academic performance at the University of Bridgeport. Dr. Odeh also received a Full Graduate Scholarship from the Computer Science Department at the University of Bridgeport (2012-2015). His work has been recognized with various other accolades, including the UPE Award in 2014. He is an active member of several professional societies, such as the IEEE Communications Society, IEEE Computer Society, ACM, and UPE. These memberships not only validate his expertise in Computer Science but also keep him connected to the latest developments in technology. Dr. Odeh’s ability to bridge academia and industry is reflected in his collaborations with major tech companies like Huawei and Orange, making him a leader in Cybersecurity and Blockchain research.

Research Focus 

Dr. Ammar M. Odeh’s research interests span a broad range of topics in Cybersecurity, AI, and Blockchain Technology. His primary focus includes Unicode Steganography, where he develops techniques for secure communication through hidden text in digital formats. He also explores Wireless Network Security, aiming to enhance data translation security across networks. Additionally, Dr. Odeh is dedicated to Human-Computer Interaction, improving the user experience through innovative security measures. He has contributed to research on the security and privacy of electronic health records, leveraging his expertise in AI and Machine Learning for more effective solutions in healthcare. Dr. Odeh has published several papers on the detection of phishing websites and malware, and his work on blockchain applications in the healthcare sector has garnered significant attention. His interdisciplinary approach to Cybersecurity and AI positions him as a prominent researcher in these rapidly evolving fields.

Publications 

  • Security and privacy of electronic health records: Concerns and challenges 🏥🔒
  • Machine learning techniques for detection of website phishing: A review for promises and challenges 🖥️🔍
  • Analysis of blockchain in the healthcare sector: Application and issues ⛓️💡
  • Performance evaluation of AODV and DSR routing protocols in MANET networks 🌐📶
  • Steganography by multipoint Arabic letters 🅰️🔤
  • PDF malware detection based on optimizable decision trees 📄⚙️
  • Detection in adverse weather conditions for autonomous vehicles via deep learning 🚗🌧️
  • Efficient detection of phishing websites using multilayer perceptron 🌐🛡️
  • Analysis of ping of death DoS and DDoS attacks 💻💥
  • Steganography in Arabic text using Kashida variation algorithm (KVA) 🇸🇦🔐
  • Quantum key distribution by using public key algorithm (RSA) 🔑📡
  • PHIBOOST – A novel phishing detection model using Adaptive boosting approach 📧⚡
  • Steganography in text by using MS Word symbols 📝🔑
  • A lightweight double-stage scheme to identify malicious DNS over HTTPS traffic using a hybrid learning approach 🌐🛡️
  • Security and privacy of electronic health records: Concerns and challenges 🏥🔐
  • Novel steganography over HTML code 🌍🔒
  • Ensemble-Based Deep Learning Models for Enhancing IoT Intrusion Detection 🤖📡
  • Efficient Mobile Sink Routing in Wireless Sensor Networks Using Bipartite Graphs 📡🌱
  • Impact of COVID-19 pandemic on education: Moving towards e-learning paradigm 💻📚

Conclusion

Dr. Ammar M. Odeh stands out as a leading researcher in his fields of specialization, particularly Cybersecurity, AI, and Blockchain. His impressive academic record, substantial research contributions, leadership in teaching and training, and active industry engagement make him a highly deserving candidate for the Best Researcher Award.While there are areas for growth in expanding his collaborative network and pursuing interdisciplinary research, his achievements to date reflect a dedication to advancing technology and education. Dr. Odeh’s work not only contributes to the academic community but also positively impacts industries such as healthcare, cybersecurity, and education.Given his strong credentials, extensive research output, and leadership in both academia and industry, Dr. Ammar Odeh is highly suitable for the Researcher of the Year Award.

Arturo Benayas Ayuso | Computer Science | Best Researcher Award

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Prof. Arturo Benayas Ayuso | Computer Science | Best Researcher Award

PhD Candidate, Universidad Politécnica de Madrid, Spain

Arturo Benayas Ayuso is a highly skilled Naval Architect with a distinguished career in naval shipbuilding and digital transformation. He currently leads the integration of the “El Cano” platform at NAVANTIA, spearheading Industry 4.0 innovations in ship design, construction, and management. His expertise in integrating PLM systems and IoT into shipbuilding projects has positioned him as a leader in naval digitization. Fluent in multiple languages, Arturo also serves as a lecturer, sharing his knowledge of statistics at Universidad Complutense de Madrid. 🚢💡

Publication Profile

ORCID

Education

Arturo holds a Master’s in Naval Architecture from Universidad Politécnica de Madrid and is currently pursuing a PhD, focusing on IoT applications in ship design, shipbuilding, and management. His academic background, combined with his professional experience, allows him to seamlessly bridge the gap between theory and practice in the maritime industry. 🎓📚

Experience

As the Integration Lead of NAVANTIA’s “El Cano” platform, Arturo manages the digitization and PLM integration of naval shipbuilding processes. His past roles include overseeing the FORAN-PLM integration for Spain’s S80 submarine and collaborating on several high-profile naval projects, including the Royal Navy’s CVF program. His work has consistently focused on improving digital workflows in naval engineering using systems like Windchill and Teamcenter PLM. 🛠️⚙️

Research Focus

Arturo’s research revolves around applying IoT technology to ship design and manufacturing. His work aims to enhance the efficiency of shipbuilding processes by integrating advanced digital tools and IoT into ship management systems. This focus on Industry 4.0 in naval architecture ensures future-ready solutions in naval engineering. 🔍🌐

Awards and Honors

Arturo has contributed significantly to both industry and academia, sharing his insights at conferences like RINA and publishing in prestigious industry magazines. His thought leadership in naval shipbuilding and PLM system integration has earned him recognition within the maritime and technology sectors. 🏅📜

Publications

Integrated Development Environment in Shipbuilding Computer Systems – ICAS 2011, cited in studies related to shipbuilding digitization

Automated/Controlled Storage for an Efficient MBOM Process in Shipbuilding Managing IoT Technology – RINA, 2018, discussed in articles on smart ship management

Data Management for Smart Ship: Reducing Machine Learning Cost in IoS Applications – RINA, 2018, frequently referenced in works on IoT and machine learning integration

Chandra Sekhar Kolli | Computer Science | Best Researcher Award

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Dr. Chandra Sekhar Kolli | Computer Science | Best Researcher Award

Associate Professor at Shri Vishnu Engineering College for Women, India

Dr. Chandra Sekhar Kolli is an accomplished academic in Computer Science with extensive teaching experience across multiple prestigious institutions. With a passion for research and a commitment to advancing knowledge in the field, Dr. Kolli has made significant contributions to areas such as machine learning, data science, and cyber security.

Profile

Scopus Profile

Education 🎓

Dr. Kolli holds a Ph.D. in Computer Science from GITAM (Deemed to be University), Visakhapatnam, obtained in 2021. He completed his M.E. in Computer Science Engineering from HITS (Deemed to be University), Chennai, in 2011 with a CGPA of 7.99, and earned his MCA from Andhra University in 2008 with a score of 74%. He also completed his B.Sc. in Computer Science from Andhra University in 2005, achieving a 71% score.

Experience 🏫

Dr. Kolli has over 13 years of teaching experience, currently serving as an Associate Professor at Shri Vishnu Engineering College for Women, Bhimavaram since June 2023. Prior to this role, he held positions such as Senior Assistant Professor at Aditya College of Engineering and Technology, and Assistant Professor at Koneru Lakshmaiah Education Foundation and Madanapalle Institute of Technology & Science, where he contributed significantly to curriculum development and student training.

Research Interests 🔍

Dr. Kolli’s research focuses on deep learning, privacy-enhanced technologies, fraud detection, and machine learning applications in various domains. His work seeks to leverage advanced algorithms to solve real-world problems, particularly in data security and intelligent systems.

Awards 🏆

Dr. Kolli was honored with the Best Teacher Award for the academic year 2019-20 at KLEF (Deemed to be University), Vijayawada. Additionally, he is a WIPRO Certified Faculty, having qualified in the Wipro Talent Next Global Certification in October 2020, showcasing his dedication to professional development in education.

Publications 📚

Dr. Kolli has a substantial publication record, including 16 journal articles and 13 conference publications, all indexed in SCOPUS. Notable publications include:

  1. Deep learning-based credit card fraud detection in federated learning
    • Authors: Venkata Krishna Reddy, V., Vijaya Kumar Reddy, R., Siva Krishna Munaga, M., Maddila, S.K., Sekhar Kolli, C.
    • Journal: Expert Systems with Applications
    • Year: 2024
    • Citations: 0
  2. Classification of defective product for smart factory through deep learning method
    • Authors: Raffik, R., Misra, P.K., Kolli, C.S., Chandol, M.K., Shukla, S.K.
    • Journal: AIP Conference Proceedings
    • Year: 2024
    • Citations: 0
  3. A review on machine learning in agricultural sciences
    • Authors: Rayalu, G.M., Farouq, K.M., Kolli, C.S., Herrera, A.P., Muhammad, R.S.
    • Journal: AIP Conference Proceedings
    • Year: 2024
    • Citations: 0
  4. Privacy enhanced course recommendations through deep learning in Federated Learning environments
    • Authors: Kolli, C.S., Seelamanthula, S., Reddy V, V.K., Reddy, M.R.K., Gumpina, B.R.
    • Journal: International Journal of Information Technology (Singapore)
    • Year: 2024
    • Citations: 1
  5. Deep learning-based privacy-preserving recommendations in federated learning
    • Authors: Kolli, C.S., Krishna Reddy, V.V., Reddy, T.S., Dasari, D.B., Reddy, M.R.
    • Journal: International Journal of General Systems
    • Year: 2024
    • Citations: 2

His research has been widely cited, contributing to the academic community and enhancing knowledge in his areas of expertise.

Conclusion ✨

Dr. Chandra Sekhar Kolli continues to inspire students and colleagues alike with his commitment to teaching and research. With numerous accolades and a solid publication record, he stands out as a prominent figure in the field of Computer Science, making impactful contributions that pave the way for future advancements in technology.

Yanming Zhao | Computer Science | Best Researcher Award

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Prof. Yanming Zhao | Computer Science | Best Researcher Award

Professor at Hebei MINZU Normal University, China

Yanming Zhao is a distinguished Professor at Hebei University of Nationalities, specializing in visual computing and deep neural networks. With a commitment to advancing technology and innovation, he has made significant contributions to the field of computer application technology, evidenced by his extensive research and numerous publications. 🌟

Profile 

Scopus Profile

Education🎓

Yanming graduated with a Master’s degree in Computer Application Technology from the School of Information at Shenyang University of Technology in 2010. His academic background laid a solid foundation for his future research endeavors and leadership in academia.

Experience🏛️💼

As a Master’s Supervisor and experienced researcher, Professor Zhao has participated in over nine provincial-level research projects and has consulted on over 500 industry projects. His work not only showcases his expertise but also his dedication to bridging the gap between academia and industry.

Research Interests🔬📈

Professor Zhao’s research primarily focuses on visual computing and deep neural networks. He has developed innovative algorithms, including the visual selectivity-based 3D graph convolutional algorithm (VS-3DGCN), aimed at enhancing point cloud segmentation performance and addressing key challenges in 3D graph convolutional algorithms.

Awards 🏆

Throughout his career, Yanming has received numerous accolades, including the title of Excellent Scientific and Technological Worker in Hebei Province and Outstanding Expert Managed by Chengde City. These awards reflect his significant contributions to the scientific community and his leadership in research.

Publications

Professor Zhao has published more than 30 academic papers in esteemed journals, such as:

  • Multi-channel depth segmentation network based on 3D graph convolution algorithm and its application in point cloud segmentation
    • Authors: Zhao, Y.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Citations: 0
  • The Multi-View Deep Visual Adaptive Graph Convolution Network and Its Application in Point Cloud
    • Authors: Fan, H., Zhao, Y., Su, G., Zhao, T., Jin, S.
    • Journal: Traitement du Signal
    • Year: 2023
    • Citations: 4
  • Graph Convolution Algorithm Based on Visual Selectivity and Point Cloud Analysis Application
    • Authors: Zhao, Y., Su, G., Yang, H., Jin, S., Yang, J.
    • Journal: Traitement du Signal
    • Year: 2022
    • Citations: 2
  • Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application
    • Authors: Yang, H., Zhao, Y., Su, G., Fan, H., Shang, Y.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 0
  • Design and application of a slow feature algorithm coupling visual selectivity and multiple long short-term memory networks
    • Authors: Zhao, Y., Yang, H., Su, G.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 1

These contributions have garnered a total citation index of 102 times, illustrating the impact of his work on the research community. 📚🔗

Conclusion🌍✨

In summary, Professor Yanming Zhao stands out as a leading figure in the fields of visual computing and deep learning. His extensive research, numerous publications, and accolades make him a deserving candidate for the Best Researcher Award. His ongoing commitment to innovation and excellence continues to inspire colleagues and students alike.

Bo Yang | Computer Science | Best Researcher Award

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Prof Dr. Bo Yang | Computer Science | Best Researcher Award

Full Professor, Northwestern Polytechnical University, China

📡 Dr. Bo Yang is a Professor at the School of Computer Science, Northwestern Polytechnical University (NPU), China. He is an expert in AI-empowered wireless networks, mobile edge/cloud computing, and big data analysis, with significant experience in academia and industry. His work has contributed to advancements in next-generation wireless systems and computational intelligent surfaces.

Publication Profile

Scopus

Strengths for the Award

  1. Extensive Research in AI-Empowered Networks: Bo Yang’s research focuses on cutting-edge technologies like AI-empowered wireless networks, mobile edge/cloud computing, and intelligent surface designs. These are relevant and impactful fields in today’s technological landscape.
  2. International Experience and Collaborations: Bo Yang has worked across multiple prestigious institutions globally, including Singapore University of Technology and Design (SUTD), Prairie View A&M University (USA), and Northwestern Polytechnical University (China). This international exposure has likely enriched his research perspective.
  3. High-Impact Publications: Bo Yang has authored and co-authored numerous influential publications in high-impact journals, such as IEEE Transactions on Wireless Communications and IEEE Transactions on Industrial Informatics, showcasing his research output and influence in the academic community.
  4. Notable Research Funding: Bo Yang has been involved in significant research projects with substantial funding, such as the $6 million USD project for the U.S. Office of Defense, which demonstrates his ability to secure large grants and work on high-stakes, impactful research.
  5. Awards and Nominations: He has been nominated for prestigious awards like the Excellence in Scholarly Research Award at Prairie View A&M University, highlighting his recognition as a strong researcher.

Areas for Improvement

  1. Broader Industry Impact: While Bo Yang’s research contributions are impressive academically, there is limited evidence of direct industry partnerships or commercialization of his research. Engaging more with industry and applying his innovations in commercial products could further bolster his case for the award.
  2. Leadership in Research Initiatives: While Bo Yang has been part of multiple large-scale research projects, more evidence of him leading major projects or research teams would enhance his leadership profile and strengthen his award candidacy.
  3. Public Engagement and Knowledge Dissemination: Expanding his efforts in science communication, such as more public-facing talks or involvement in workshops and seminars, could improve his visibility and influence beyond the academic community.

Education

🎓 Dr. Yang earned his Ph.D. in Information and Communication Engineering from NPU (2010-2017), where his thesis focused on multi-channel medium access for next-generation WLAN. He also holds an M.Sc. in Communication and Information Systems (2007-2010) with a thesis on video coding and wireless transmission, and a B.Sc. in Communication Engineering (2003-2007), during which he interned at Datang Telecom.

Experience

💼 Dr. Yang is currently a Professor at NPU, Xi’an, China, where he leads cutting-edge research on AI-empowered wireless networks. Previously, he was a Research Fellow at the Singapore University of Technology and Design (SUTD) and a Postdoctoral Fellow at Prairie View A&M University (PVAMU), USA. His research projects have been funded by prestigious organizations, including A*STAR in Singapore and the U.S. Office of the Under Secretary of Defense.

Research Focus

🔬 Dr. Yang’s research focuses on AI-powered wireless networks, mobile edge/cloud computing, computational intelligent surfaces, and big data security. His innovative work addresses challenges in next-generation communication systems, with a particular emphasis on reconfigurable intelligent surfaces and federated spectrum learning for wireless edge networks.

Awards and Honors

🏆 Dr. Yang has been honored with several prestigious awards, including the NNSF for Excellent Young Scientists Fund Program (Overseas) in 2022 and a nomination for the Excellence in Scholarly Research Award at PVAMU in 2020. His groundbreaking research projects have been funded by leading organizations worldwide.

Publication Top Notes

📝 Dr. Yang has authored numerous influential papers in high-impact journals. His recent works include:

“DiffSG: A Generative Solver for Network Optimization with Diffusion Model” (2024) – arXiv:2408.06701

“Reconfigurable Intelligent Computational Surfaces for MEC-Assisted Autonomous Driving Networks: Design Optimization and Analysis” (2024) – arXiv:2407.00933

“Filtering Reconfigurable Intelligent Computational Surface for RF Spectrum Purification” (2024) – arXiv:2406.18055

“AI-Empowered Multiple Access for 6G: A Survey of Spectrum Sensing, Protocol Designs, and Optimizations” (2024) – Proceedings of the IEEE, Cited by 39

“A Multi-View Interactive Approach for Multimodal Sarcasm Detection in Social Internet of Things” (2024) – Applied Sciences, Cited by 18

Conclusion

Bo Yang is a highly qualified candidate for the Best Researcher Award due to his significant contributions to AI-empowered networks, his prolific publication record, and involvement in international research collaborations. To enhance his candidacy further, he could focus on increasing industry engagement, leading more research initiatives, and enhancing public engagement with his work. His strengths in cutting-edge technology, global experience, and scholarly impact make him a strong contender for the award.

Alex Mirugwe | Computer Science | Young Scientist Award

Published on by World Top Scientists

Mr. Alex Mirugwe | Computer Science | Young Scientist Award

Data Scientist at Makerere University, School of Public Health, Uganda

Alex Mirugwe is a highly skilled Data Scientist with over 4 years of experience, specializing in applying machine learning and AI to healthcare challenges, particularly in HIV, cancer, and tuberculosis diagnostics. He has a proven track record of developing data-driven solutions that improve patient outcomes in resource-constrained settings. His research has been published in several peer-reviewed journals, and he is proficient in a wide range of data science tools and methodologies. Alex also contributes to academia as an Assistant Lecturer and is involved in curriculum development and student mentoring in computer science.

Profile:

Strengths for the Award:

  1. Specialized Expertise in Healthcare Data Science: Alex Mirugwe has developed machine learning models and AI tools to solve critical health challenges, such as HIV patient care and cervical cancer detection. His work is not only technically sound but has made tangible impacts on healthcare delivery in resource-constrained environments.
  2. Research Contributions and Publications: Alex has authored multiple peer-reviewed journal articles on healthcare applications of AI, including sentiment analysis of public health data, tuberculosis detection, and cancer screening. These publications demonstrate his commitment to advancing the application of AI in public health and data science.
  3. Experience in Machine Learning and AI: His technical expertise spans a range of relevant tools and techniques, including deep learning, transfer learning, and predictive modeling, which are crucial for impactful healthcare interventions. His experience in both teaching and research also ensures that his knowledge is applied and shared within the academic community.
  4. Proven Success in Real-World Applications: Alex’s work on reducing HIV patient data duplication, predicting HIV patient outcomes, and improving cervical cancer screening speaks to his practical problem-solving skills in high-stakes environments. The use of AI to improve healthcare decision-making is well-aligned with global trends toward technology-driven health solutions.
  5. Cross-Disciplinary and Global Approach: Alex’s education, spanning institutions in Uganda and South Africa, and his research interests in global health issues, reflect his broad outlook. His involvement with international collaborators highlights his ability to bridge different disciplines and apply his knowledge across borders.

Areas for Improvement:

  1. More Diverse Research Focus: While Alex has concentrated on significant healthcare issues, expanding his research beyond HIV, cancer, and tuberculosis may enhance his portfolio. Including more work in diverse fields, such as environmental health or genomics, would add breadth to his achievements.
  2. Leadership in Research Projects: Alex has demonstrated technical prowess and teaching capabilities, but more emphasis on leadership roles in large-scale research projects or interdisciplinary initiatives could elevate his profile. Leading a significant multi-institutional study or directing larger research teams may help solidify his standing.
  3. Policy and Implementation Impact: Though Alex has made practical contributions, more evidence of his work leading to large-scale policy changes or national-level healthcare implementations could further strengthen his application. This would demonstrate how his AI models or algorithms scale to influence public health strategies at a systemic level.
  4. International Research Collaborations: Although his work is impactful within Uganda, expanding collaborations with more international research institutes or global health organizations could further enhance his visibility and contribution to global health initiatives.

 

Education:

Alex Mirugwe holds an MSc in Data Science from the University of Cape Town, South Africa, completed in 2021, where he conducted research on automated bird detection using machine learning. His academic performance was strong, with a GPA of 74.52%. Prior to this, he earned a BSc in Computer Engineering from Makerere University, Uganda, in 2019, graduating with a CGPA of 4.18/5.0. His undergraduate dissertation focused on developing a low-cost wireless TV audio transceiver, reflecting his early interest in applying engineering principles to real-world problems. His educational background combines technical proficiency in computer science with a strong emphasis on data science and machine learning applications.

Experience:

Alex Mirugwe is a highly skilled data scientist with over four years of experience applying machine learning and AI to healthcare challenges, particularly in diagnosing HIV, cancer, and tuberculosis. He has successfully developed predictive models to improve patient care and outcomes in resource-limited settings, such as creating algorithms for cervical cancer screening and reducing HIV patient data duplication. His work spans both practical implementation and academic research, with multiple publications on AI-driven health interventions. In addition to his research, Alex is an experienced educator, teaching data science and machine learning courses at the university level.

Research Focus:

Alex Mirugwe’s research focuses on leveraging data science and machine learning to address critical healthcare challenges, particularly in resource-constrained settings. His work encompasses developing predictive models for patient care in HIV treatment, enhancing cervical cancer screening accuracy through AI algorithms, and analyzing public sentiment during health crises, such as the Ebola outbreak. Additionally, he explores various applications of AI in public health, including improving tuberculosis detection and reducing data duplication in electronic medical records. Overall, his research aims to harness advanced data analytics to improve patient outcomes and inform public health strategies, making significant contributions to the field of healthcare data science.

Publications Top Notes:

  • Automating Bird Detection Based on Webcam Captured Images Using Deep Learning
    • Authors: A. Mirugwe, J. Nyirenda, E. Dufourq
    • Year: 2022
    • Citations: Not specified in the provided information.
  • Restaurant Tipping Linear Regression Model
    • Author: A. Mirugwe
    • Year: 2020
    • Citations: Not specified in the provided information.
    • Link: SSRNPaper
  • Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers
    • Authors: A. Mirugwe, C. Ashaba, A. Namale, E. Akello, E. Bichetero, E. Kansiime, J. Nyirenda
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Journal: Life, 14(6), 708.
  • Adoption of Artificial Intelligence in the Ugandan Health Sector: A Review of Literature
    • Author: A. Mirugwe
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Link: Available at SSRN 4735326.

Conclusion:

Alex Mirugwe presents an impressive and well-rounded portfolio, with extensive experience in applying machine learning and AI to tackle critical healthcare challenges. His achievements, particularly in HIV care and cancer screening, demonstrate his ability to leverage data science for real-world health outcomes. While he has a strong research and technical background, focusing on leadership, broadening his research scope, and contributing to systemic policy changes could bolster his case further. He is a strong candidate for the Best Researcher Award, especially within the domain of AI-driven healthcare solutions in resource-constrained settings.

Miin-Shen Yang | Computer Science | Best Researcher Award

Published on by World Top Scientists

Prof Dr. Miin-Shen Yang | Computer Science | Best Researcher Award

Distinguished Professor,Chung Yuan Christian University, Taiwan

👨‍🏫 Miin-Shen Yang is a distinguished scholar and professor specializing in applied mathematics and artificial intelligence. He has made significant contributions to fuzzy clustering, machine learning, and soft computing. Currently serving as a Life Distinguished Professor at Chung Yuan Christian University (CYCU), Taiwan, Dr. Yang is highly regarded in the scientific community for his innovative research. He is also recognized among the top 0.5% of scholars globally by ScholarGPS and Stanford University’s Top 2% Scientists.

Publication Profile

ORCID

Strengths for the Award:

  1. Extensive Academic Background: Miin-Shen Yang has earned degrees in mathematics and statistics from prestigious institutions, with a Ph.D. from the University of South Carolina, USA. His long-standing association with Chung Yuan Christian University (CYCU), Taiwan, adds to his academic credibility.
  2. Research Impact: His research areas—statistics, clustering algorithms, fuzzy clustering, soft computing, pattern recognition, and machine learning—are crucial in modern scientific and technological advancements, especially in the AI-driven era.
  3. Global Recognition: Miin-Shen Yang’s inclusion in Stanford University’s Top 2% Scientists and ScholarGPS’s global top 0.5% demonstrates the international recognition of his work and significant contributions to artificial intelligence, image processing, and related fields.
  4. Editorial Roles: He served as an Associate Editor for IEEE Transactions on Fuzzy Systems and remains on the Editorial Board of Electronics (MDPI). These roles show his influence in shaping scientific discourse in his fields of expertise.
  5. Leadership in Academia: As a Distinguished Professor and previous Chairperson and Dean of the College of Science at CYCU, he has demonstrated not only research expertise but also leadership in academic governance.

Areas for Improvement:

  1. Broader Collaborations: While Miin-Shen Yang’s contributions are notable in the fields of applied mathematics and artificial intelligence, there could be a stronger emphasis on collaborative projects across interdisciplinary fields such as biostatistics or environmental data science, which are becoming increasingly critical for global research challenges.
  2. Applied Research and Industry Connections: Strengthening connections between his academic research and real-world industrial applications could further enhance the societal impact of his work, especially in sectors like healthcare, energy, or environmental sustainability where AI and machine learning are emerging as transformative tools.
  3. Public Engagement and Outreach: Additional efforts to disseminate his research through public engagement activities, workshops, or conferences that target both academic and non-academic audiences could raise the visibility and practical applicability of his findings.

Education

🎓 Miin-Shen Yang holds a B.S. in Mathematics from Chung Yuan Christian University (1977), an M.S. in Applied Mathematics from National Chiao-Tung University (1980), and a Ph.D. in Statistics from the University of South Carolina, Columbia, USA (1989).

Experience

💼 Dr. Yang joined CYCU in 1989 and became a Professor in 1994. He has held several key positions, including Department Chair, Director of the Chaplain’s Office, and Dean of the College of Science. He also served as a Visiting Professor at the University of Washington from 1997 to 1998.

Research Focus

🔬 Dr. Yang’s research interests span applications of statistics, fuzzy clustering, machine learning, soft computing, pattern recognition, and artificial intelligence. His contributions have significantly advanced clustering algorithms and AI-related technologies.

Awards and Honors

🏅 Dr. Yang has been recognized among Stanford University’s Top 2% Scientists and listed among ScholarGPS global top 0.5% scholars. He has also served as an Associate Editor for IEEE Transactions on Fuzzy Systems and is currently an Editorial Board Member for the journal Electronics.

Publications (Top Notes)

📚 Dr. Yang has published extensively on fuzzy clustering and artificial intelligence in leading journals. His works have been widely cited, marking his influence in the field.

“Fuzzy Clustering Algorithms and Applications” – Published in 2015 in Pattern Recognition Letters. Cited by 100+ articles

Conclusion:

Miin-Shen Yang is an exceptional candidate for the Research for Best Research Award, with a strong and diversified research portfolio in applied mathematics, artificial intelligence, and machine learning. His global recognition, academic leadership, and editorial contributions demonstrate his significant impact on the scientific community. While further strengthening his research collaborations across broader disciplines and emphasizing real-world applications could enhance his overall impact, his current achievements make him a highly competitive and deserving nominee for the award.