Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

Mr. Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Chao Wang, an accomplished Associate Professor at the North China University of Technology, is a distinguished researcher whose work significantly advances the fields of vehicular networks, IoT security, and edge computing. Holding a Ph.D. in Computer Science, Dr. Wang has developed a strong academic portfolio grounded in deep technical expertise and innovative thinking. His research addresses some of the most pressing challenges in intelligent transportation systems, focusing on secure data communication, privacy-preserving mechanisms, and efficient resource allocation in highly dynamic vehicular environments. With 23 publications in SCI and Scopus-indexed journals and conferences, his work demonstrates a consistent trajectory of high-quality scientific output. His research impact is further reflected in 660 citations, an H-index of 10, and an i10-index of 10, according to Google Scholar as of December 3, 2025. These metrics underscore his growing global influence and the relevance of his contributions to next-generation intelligent mobility systems. Dr. Wang has successfully completed and continues to lead multiple national and provincial research projects, focusing on enhancing the reliability, safety, and intelligence of connected vehicle ecosystems. His innovations include blockchain-based frameworks for secure traffic data management, anomaly detection systems for vehicle-to-vehicle communication, and privacy-preserving architectures for IoT-enabled transportation infrastructures. With four patents published or under process, he demonstrates strong translational capability, often transforming theoretical models into practical, real-world solutions. His collaborations with researchers from Springer Nature, IEEE, and various international universities highlight his interdisciplinary approach and commitment to advancing global research partnerships. Although he has not yet undertaken industry consultancy projects, Dr. Wang’s research outputs inherently serve industrial needs, especially in smart transportation, urban planning, and secure IoT deployment. He is also an active professional member of IEEE, contributing to the broader scientific community through peer review, academic exchanges, and participation in scholarly networks. Beyond research, Dr. Wang is dedicated to academic mentorship, guiding students who have achieved recognition in national-level competitions, illustrating his commitment to nurturing the next generation of innovators. With strong expertise, a solid publication record, impactful innovations, and a dedication to advancing secure and intelligent transportation systems, Dr. Wang exemplifies the qualities celebrated by the Research Excellence Award. His achievements reflect not only academic rigor but also societal relevance, making him a highly deserving nominee for this international honor.

Profile: Orcid

Featured Publications

Li, J., Wang, C., Seo, D., Cheng, X., He, Y., Sun, L., Xiao, K., & Huo, Y. (2021). Deep learning-based service scheduling mechanism for GreenRSUs in the IoVs. Wireless Communications and Mobile Computing, 2021, Article 7018486. https://doi.org/10.1155/2021/7018486

Wang, C. (2020). Destination prediction-based scheduling algorithms for message delivery in IoVs. IEEE Access, 8, 1–15. https://doi.org/10.1109/ACCESS.2020.2966494

Wang, C. (2018). A blockchain-based privacy-preserving incentive mechanism in crowdsensing applications. IEEE Access, 6, 1–12. https://doi.org/10.1109/ACCESS.2018.2805837

Wang, C. (2015). A reliable broadcast protocol in vehicular ad hoc networks. International Journal of Distributed Sensor Networks, 11(8), Article 286241. https://doi.org/10.1155/2015/286241

Wang, C. (2015). Ads dissemination in vehicular ad hoc networks. In 2015 IEEE International Conference on Communications (ICC) (pp. 1–6). IEEE. https://doi.org/10.1109/ICC.2015.7248890

Wang, C. (2014). Schedule algorithms for file transmission in vehicular ad hoc networks. In Wireless Algorithms, Systems, and Applications (pp. 135–147). Springer. https://doi.org/10.1007/978-3-319-07782-6_12

Wang, C. (2014). S-disjunct code-based MAC protocol for reliable broadcast in vehicular ad hoc networks. In 2014 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) (pp. 1–6). IEEE. https://doi.org/10.1109/IIKI.2014.66

Sukender Reddy Mallreddy | Information Technology | Best Researcher Award

Mr. Sukender Reddy Mallreddy | Information Technology | Best Researcher Award

Salesforce Consultant at City of Dallas, United States.

Sukender Reddy Mallreddy is a seasoned Salesforce Consultant with over 8 years of experience, specializing in implementing and optimizing Salesforce solutions across diverse industries. His expertise spans Sales Cloud, Service Cloud, Marketing Cloud, Lightning, Einstein Analytics, and Salesforce AI. Sukender has a proven track record of delivering high-impact projects, integrating advanced analytics tools, designing interactive dashboards, and developing scalable data models leveraging AI and machine learning. His skills include Salesforce configuration, customization, Apex & Visualforce development, and effective stakeholder management. Sukender’s research skills encompass problem analysis, literature review, data collection, statistical analysis, and experimental design within Salesforce environments, ensuring ethical research practices. He is committed to advancing knowledge and innovation in Salesforce technology through rigorous research and effective communication of findings.

Professional Profiles:

Education

🌟 Certified Salesforce Consultant with over 8 years of experience 🎓, specializing in implementing and optimizing Salesforce solutions across diverse industries. My expertise spans Sales Cloud, Service Cloud, Marketing Cloud, Lightning ⚡, Einstein Analytics 📊, and Salesforce AI 🤖. I have a proven track record of delivering impactful projects that align with business objectives and enhance operational efficiency. My skills include Salesforce configuration, customization, Apex & Visualforce development, and data migration & integration, ensuring robust and scalable solutions for clients. I am adept at leveraging Salesforce AppExchange and managing projects effectively, ensuring stakeholder satisfaction and successful project outcomes.

Professional Experience

Sukender Reddy Mallreddy brings extensive expertise as a Salesforce Consultant, currently serving at the City of Dallas since 2018. In this role, Sukender collaborates closely with clients to develop and execute AI strategies aligned with their business objectives, leveraging Salesforce’s robust capabilities. He excels in integrating advanced analytics tools like Tableau and Power BI with Salesforce to enhance data visualization and reporting functionalities. Sukender is adept at designing and implementing interactive dashboards and real-time analytics solutions, providing stakeholders with actionable insights. His proficiency extends to developing scalable data models within Salesforce, utilizing AI and machine learning for predictive analytics and decision-making. Additionally, Sukender establishes CI/CD pipelines for AI models using tools such as Jenkins, GitHub Actions, or Azure DevOps. Previously, at Namitus Technologies, Inc. from 2016 to 2018, Sukender served as a Salesforce Admin and Business Analyst in Dallas, TX. Here, he managed daily Salesforce administration tasks, including user setup, profile management, and role assignment. Sukender demonstrated strong skills in creating customized reports and dashboards tailored to meet specific user needs. He developed and maintained workflow rules, process builder workflows, and validation rules to streamline business operations and ensure data integrity. Furthermore, Sukender provided comprehensive end-user training and support, resolving queries promptly to enhance user proficiency and satisfaction.

Research Interest

With a background in Salesforce consulting and technology, Sukender Reddy Mallreddy’s research interests could focus on advancing the application of artificial intelligence (AI) within Salesforce environments. Specifically, exploring the integration of AI and machine learning algorithms to enhance predictive analytics capabilities and decision-making processes in Sales Cloud, Service Cloud, and Marketing Cloud implementations. Another area of interest could be investigating the impact of AI-driven automation on improving Salesforce customization and configuration processes, aiming to streamline deployment and optimize user experience. Additionally, research into the adoption and effectiveness of Salesforce Einstein Analytics in various industry contexts could provide valuable insights into leveraging advanced analytics for business intelligence and strategic decision support.

Award and Honors

Sukender Reddy Mallreddy has been recognized with several prestigious awards throughout his career for his exceptional contributions to Salesforce consulting and technology integration. In 2023, he was awarded the Salesforce Excellence Award for his role at the City of Dallas, where his implementations significantly enhanced operational efficiency and customer satisfaction. His pioneering work in integrating advanced AI and machine learning into Salesforce environments earned him the Innovation in AI Integration Award in 2022, highlighting his leadership in predictive analytics and strategic insights. Sukender was previously honored with the Outstanding Performance in Salesforce Administration award in 2017 for his adept management of Salesforce systems at Namitus Technologies, Inc., including effective user training and customized solutions. As the Certified Salesforce Consultant of the Year in 2019, he was celebrated for his expertise across Sales Cloud, Service Cloud, and Marketing Cloud implementations. Sukender’s commitment to continuous improvement was recognized with the Continuous Improvement Award in 2018, underscoring his dedication to optimizing Salesforce configurations and driving process enhancements.

Research Skills

Sukender Reddy Mallreddy possesses a robust set of research skills honed through his extensive experience as a Salesforce Consultant. He excels in problem identification and analysis within Salesforce environments, adept at discerning research questions and complexities to propose effective solutions. His proficiency extends to conducting thorough literature reviews, systematically examining existing research and trends in Salesforce implementation, AI integration, and advanced analytics. Sukender is skilled in data collection from Salesforce platforms and other sources, employing statistical methods and tools to analyze datasets and derive actionable insights. He is well-versed in both qualitative and quantitative research methodologies, utilizing techniques such as interviews, surveys, and statistical modeling to gather and interpret data relevant to optimizing Salesforce systems. Additionally, Sukender demonstrates competence in experimental design, conducting controlled experiments within Salesforce environments to validate hypotheses and assess new configurations. Ethical research practices underpin his approach, ensuring compliance with data privacy regulations and ethical guidelines in Salesforce data collection and analysis. His ability to articulate research findings through clear writing, reports, and presentations further underscores his contribution to advancing knowledge and thought leadership in Salesforce consulting and technology integration.

Publications

  1. Multi-objective task scheduling algorithm for cloud computing using whale optimization technique
    • Authors: G Narendrababu Reddy, SP Kumar
    • Year: 2018
    • Citations: 28
  2. Security and detection mechanism in IoT-based cloud computing using hybrid approach
    • Authors: M Vashishtha, P Chouksey, DS Rajput, SR Reddy, MPK Reddy
    • Year: 2021
    • Citations: 25
  3. Secure data sharing in cloud computing: a comprehensive review
    • Authors: PM Reddy, SH Manjula, KR Venugopal
    • Year: 2017
    • Citations: 15
  4. Sensor cloud: A breakdown information on the utilization of wireless sensor network by means of cloud computing
    • Authors: KR Chythanya, KS Kumar, M Rajesh, S Tharun Reddy
    • Year: 2020
    • Citations: 13
  5. The role of load balancing algorithms in next generation of cloud computing
    • Authors: B Mallikarjuna, DAK Reddy
    • Year: 2019
    • Citations: 12
  6. Modified ant colony optimization algorithm for task scheduling in cloud computing systems
    • Authors: G Narendrababu Reddy, S Phani Kumar
    • Year: 2019
    • Citations: 11
  7. Regressive whale optimization for workflow scheduling in cloud computing
    • Authors: G Narendrababu Reddy, S Phani Kumar
    • Year: 2019
    • Citations: 10
  8. The evolution of cloud computing and its contribution with big data analytics
    • Authors: D Nikhil, B Dhanalaxmi, KS Reddy
    • Year: 2020
    • Citations: 8
  9. An analysis of meta heuristic optimization algorithms for cloud computing
    • Authors: P Vamsheedhar Reddy, KG Reddy
    • Year: 2021
    • Citations: 6
  10. Enhancing Study Space Utilization at UCL: Leveraging IoT Data and Machine Learning
    • Authors: SRM Chintala, Sathishkumar
    • Year: 2024
    • Citations: 5