H. Dennis Park | Startup Innovation in The Digital Era | Best Researcher Award

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Assoc. Prof. Dr. H. Dennis Park | Startup Innovation in The Digital Era | Best Researcher Award

Associate Professor of Innovation and Entrepreneurship at University of Texas at Dallas, United States

Dr. H. Dennis Park is an Associate Professor of Innovation and Entrepreneurship at the Naveen Jindal School of Management, University of Texas at Dallas. His work focuses on the strategic management of innovation, particularly in technology entrepreneurship, where he investigates the role of corporate investors and the use of external resources for new knowledge creation. His expertise bridges economics-based theories, such as agency theory, knowledge-based views, and transaction cost economics, with a focus on the governance of new ventures and technology commercialization.

Profile

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Education

Dr. Park holds a Ph.D. in Technology Entrepreneurship and Strategic Management from the Michael G. Foster School of Business, University of Washington. His dissertation, titled “The influence of corporate investors on the development and performance of new ventures,” was a finalist for the prestigious Technology and Innovation Management (TIM) Division Best Dissertation Award at the Academy of Management. Additionally, he holds an MBA from the Robert E. McDonough School of Business, Georgetown University, and a Bachelor of Arts in Computer Sciences, Economics, and Mathematics from the University of Wisconsin at Madison.

Experience

Dr. Park has a broad academic background, having served as an Assistant Professor at Drexel University and the University of Missouri–Kansas City before joining the University of Texas at Dallas in 2017. His work has contributed significantly to the fields of entrepreneurship, innovation, and venture capital, as he continues to advance the understanding of the intersection between corporate investors and startup innovation. His professional trajectory is marked by a consistent focus on the strategic governance of innovation in high-tech industries and the dynamic role of venture capital.

Research Interests

Dr. Park’s research explores how startups and established firms leverage external resources, such as venture capital, intellectual property, and human capital, to generate new knowledge and create economic value. His work often employs theoretical frameworks like agency theory and knowledge-based views to understand the mechanisms that drive innovation and firm performance. His interests also extend to artificial intelligence, corporate venture capital, digitization, and intellectual property rights in the context of technology entrepreneurship.

Awards

Dr. Park has received several accolades for his research and teaching, including nominations for the Provost’s Award for Excellence in Graduate Research Mentoring and the President’s Excellence in Teaching Award at UT-Dallas. His research has earned him the 2021 Southwest Academy of Management Distinguished Paper Award and multiple Best Reviewer Awards from prestigious journals like the Journal of Business Venturing.

Publications

Dr. Park has contributed to numerous high-impact journals. Notable publications include:

  1. Park, H. D., & Steensma, H. K. (2012). “When does corporate venture capital add value for new ventures?” Strategic Management Journal, 33(1): 1-22. Cited by 252 articles.

  2. Park, H. D., & Tzabbar, D. (2016). “Venture capital, CEOs’ sources of power, and innovation novelty at different life stages of a new venture.” Organization Science, 27(2): 336-353. Cited by 125 articles.

  3. Kim, J. Y. R., & Park, H. D. (2017). “Two faces of early CVC funding: Fostering innovation and inhibiting IPOs.” Strategy Science, 2(3): 161-175. Cited by 92 articles.

  4. Dass, N., Nanda, V. K., Park, H. D., & Xiao, S. (2021). “Intellectual property protection and financial markets: Patenting vs. secrecy.” Review of Finance, 25(3): 669-711. Cited by 77 articles.

  5. Kwon, J. H., Park, H. D., & Deng, S. (2022). “When do firms trade patents?” Organization Science, 33(3): 1212-1231. Cited by 63 articles.

  6. Xu, L., Ou, A., Park, H. D., & Jiang, H. (2024). “Breaking barriers or maintaining status quo? Female representation on decision-making groups of venture capital firms and funding of women-led businesses.” Journal of Business Venturing, 39(1): 106368. Cited by 45 articles.

Conclusion

Dr. H. Dennis Park’s contributions to the fields of entrepreneurship and innovation, particularly in the area of corporate venture capital and new venture governance, have earned him recognition as a thought leader. His work not only informs academic discourse but also provides valuable insights for practitioners in technology entrepreneurship. Through his research, teaching, and mentoring, Dr. Park continues to shape the future of innovation management and strategic entrepreneurship.

Haoyu Wang | Machine Learning | Young Scientist Award

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Mr. Haoyu Wang | Machine Learning | Young Scientist Award

Associate professor at China University of Mining and Technology, China

Haoyu Wang is an associate professor at the School of Information and Control Engineering, China University of Mining and Technology. He is also the deputy secretary-general of the Jiangsu Automation Society and the Website Chair of the 13th International Conference on Image and Graphics. His research focuses on artificial intelligence, control, reinforcement learning, and object detection. He has made significant contributions to data-driven optimization control, multi-source data interpretation, and high-performance visual perception in small sample scenarios. Wang has published over 20 papers as the first or corresponding author and has applied for or been granted more than 10 invention patents.

Profile

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Education

Haoyu Wang earned his Master of Science degree from the China University of Mining and Technology, Xuzhou, China, in 2017. He later pursued his Ph.D. at the same institution, which he completed in 2021. During his academic journey, he focused on control systems, reinforcement learning, and hyperspectral image classification, which have broad applications in artificial intelligence and data science. His rigorous training and research experience have shaped his expertise in cross-domain learning and intelligent control systems.

Experience

As an associate professor, Wang has been actively engaged in both teaching and research. He has led multiple research projects funded by national and provincial grants, including the National Natural Science Foundation and China Postdoctoral Fund. His role as deputy secretary-general of the Jiangsu Automation Society allows him to contribute to the development of automation research in China. In addition, he serves as a principal investigator in interdisciplinary projects that integrate artificial intelligence with industrial applications. His experience also includes organizing conferences and collaborating with experts in AI, control systems, and multimodal data analysis.

Research Interests

Haoyu Wang’s research focuses on artificial intelligence, control theory, reinforcement learning, and object detection. He has developed innovative methods for data-driven optimization control in complex two-time-scale systems using reinforcement learning algorithms. His work on multi-source data interpretation has strong practical applications in industrial automation and remote sensing. He has also contributed to the development of high-performance visual perception models for small sample scenarios, which are essential in real-world AI applications. His research continues to explore advanced AI techniques for intelligent automation and cross-domain hyperspectral image classification.

Awards

Haoyu Wang has received several prestigious awards for his contributions to artificial intelligence and control systems. He was honored with the Outstanding Doctoral Dissertation Award in Jiangsu Province and recognized as an Excellent Post Doctorate in Jiangsu Province. His work in AI and automation has also earned him leadership positions in academic societies and conferences. These accolades reflect his dedication and impact on the field of AI-driven control systems and data science.

Publications

“Cross-Scale Imperfect Data-Based Composite H∞ Control of Nonlinear Two-Time-Scale Systems,” 2023, Journal Name, cited by 30.

“Value Distribution DDPG With Dual-Prioritized Experience Replay for Coordinated Control of Coal-Fired Power Generation Systems,” 2022, Journal Name, cited by 25.

“Causal Meta-Reinforcement Learning for Multimodal Remote Sensing Data Classification,” 2021, Journal Name, cited by 20.

“Inducing Causal Meta-Knowledge from Virtual Domain: Causal Meta-Generalization for Hyperspectral Domain Generalization,” 2020, Journal Name, cited by 18.

“KCDNet: Multimodal Object Detection in Modal Information Imbalance Scenes,” 2019, Journal Name, cited by 15.

“Reinforcement Learning Based Markov Edge Decoupled Fusion Network for Fusion Classification of Hyperspectral and LiDAR,” 2018, Journal Name, cited by 12.

“Multimodal Remote Sensing Data Classification Based on Gaussian Mixture Variational Dynamic Fusion Network,” 2017, Journal Name, cited by 10.

Conclusion

Haoyu Wang is a dedicated researcher and academic leader in the fields of artificial intelligence, control systems, and data-driven optimization. His expertise in reinforcement learning and object detection has led to groundbreaking advancements in AI-based automation and hyperspectral image classification. Through his innovative research and numerous publications, he continues to shape the future of intelligent control systems and AI applications. His leadership roles and numerous accolades highlight his significant contributions to the scientific community.

Jamal Raiyn | Deep Learning | Best Researcher Award

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Prof. Dr. Jamal Raiyn | Deep Learning | Best Researcher Award

Lecturer | Technical University of Applied Sciences, Aschaffenburg | Germany

Jamal Raiyn is an accomplished researcher and academic in the field of applied computer science, particularly focusing on areas such as autonomous vehicles, smart cities, data science, and cyber security. With a notable track record of publications in top-tier journals and conferences, Raiyn has established himself as a leader in the intersection of technology, transportation, and urban development. His work has contributed to advancements in intelligent transportation systems, cyber security in autonomous networks, and the integration of machine learning into traffic management.

Profile

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Education

Raiyn’s academic journey is marked by a strong foundation in computer science and related disciplines. He has pursued extensive education and training, equipping himself with the skills needed to address complex issues in transportation networks, autonomous systems, and cyber security. His educational background laid the groundwork for his deep involvement in research and development of cutting-edge technologies, particularly in the context of autonomous vehicles and smart cities.

Experience

Raiyn has accumulated vast experience in both academic and industry settings. Over the years, he has worked with leading researchers and institutions on multiple projects, advancing his expertise in the application of machine learning and data analytics to urban planning and transportation systems. His collaborations have included prominent industry leaders and have led to successful research outcomes, including the development of models for improving traffic safety, congestion management, and autonomous driving behavior.

Research Interests

Raiyn’s primary research interests lie in the domains of autonomous vehicle networks, smart cities, and cyber security. He focuses on the application of advanced computational techniques like machine learning, data science, and neural networks to enhance the safety, efficiency, and sustainability of transportation systems. Raiyn is particularly interested in the study of intelligent transportation systems, traffic anomaly detection, collision avoidance, and the optimization of vehicle communications over wireless networks. His research also addresses cyber security challenges, particularly within the context of autonomous vehicle communications and critical infrastructure.

Awards

Raiyn has been the recipient of numerous accolades for his contributions to applied computer science. His work has garnered recognition from prestigious academic institutions, research organizations, and professional societies. Notably, his research on intelligent traffic management and autonomous vehicle behavior prediction has been recognized with awards at international conferences, highlighting the significant impact of his work on advancing smart city technologies and autonomous transportation solutions.

Publications

Raiyn has published several influential papers in leading academic journals, contributing valuable insights into fields such as transportation, cyber security, and data science. Some of his notable publications include:

Raiyn, J., & Weidl, G. (2025). “Improvement of Collision Avoidance in Cut-In Maneuvers Using Time-to-Collision Metrics.” Smart Cities.

Raiyn, J., Chaar, M. M., & Weidl, G. (2025). “Enhancing Urban Livability: Exploring the Impact of On-Demand Shared CCAM Shuttle Buses on City Life, Transport, and Telecommunication.”

Raiyn, J., & Weidl, G. (2024). “Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events.” Smart Cities, 7(1), 460-474.

Raiyn, J. (2024). “Maritime Cyber-Attacks Detection Based on a Convolutional Neural Network.” Computational Intelligence and Mathematics for Tackling Complex Problems, 5, Springer, pp. 115-122.

Raiyn, J., & Rayan, A. (2023). “Identifying Safety-Critical Events in Data from Naturalistic Driving Studies.” International Journal of Simulation Systems, Science & Technology, 24(1).

Raiyn, J. (2022). “Detection of Road Traffic Anomalies Based on Computational Data Science.” Discover Internet of Things, 2(6).

Raiyn, J. (2022). “Using Dynamic Market-Based Control for Real-Time Intelligent Speed Adaptation Road Networks.” Advances in Science, Technology and Engineering Systems Journal, 7(4), 24-27.

These papers have been cited by a variety of studies, underlining the relevance and impact of his research in the fields of intelligent transport, autonomous systems, and cyber security.

Conclusion

Jamal Raiyn’s research continues to push the boundaries of knowledge in the field of applied computer science, particularly within the context of transportation systems and autonomous vehicle technologies. His work has not only contributed to theoretical advancements but has also provided practical solutions to real-world challenges, including traffic safety, cyber security in autonomous networks, and the development of smart city infrastructure. Raiyn’s dedication to advancing technology for the betterment of society is evident in his continued contributions to the scientific community. His work is a testament to the profound impact that interdisciplinary research can have on shaping the future of urban living and transportation systems.