Dr. David Hua | Artificial Intelligence | Best Researcher Award

Dr. David Hua | Artificial Intelligence | Best Researcher Award

Ball State University, United States.

Dr. David M. Hua is an Associate Professor at the Center for Information and Communication Sciences, Ball State University. With a rich academic background and over two decades of teaching, Dr. Hua has become a pivotal figure in the intersection of technology education, cybersecurity, and higher education. He is recognized for mentoring student-led innovation and his contribution to emerging tech curricula including offensive security, private cloud infrastructure, and sustainability in IT.

Profile

Scopus
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🎓 Education

Dr. Hua earned his Ed.D. in Higher Education in 2010 from Ball State University, where he also completed an MBA in Information Systems (2000) and a B.S. in Psychological Science (1991). This diverse academic foundation reflects his commitment to both technical expertise and educational leadership.

💼 Experience

Since July 20, 1998, Dr. Hua has served at Ball State University, advancing to the role of Associate Professor. He began as an Assistant Professor in 2000. His teaching spans undergraduate and graduate levels with courses ranging from cybersecurity and network configuration to cloud technologies. Beyond Ball State, his engagements with other institutions and organizations have broadened his interdisciplinary impact on both students and faculty.

🔬 Research Interests

Dr. Hua’s research interests lie at the crossroads of cybersecurity, AI in mental health surveillance, sustainable IT practices, and technology integration in higher education. He is especially passionate about leveraging machine learning to support mental health outcomes and empower student innovation through data-driven methodologies.

🏆 Awards & Mentorship

Dr. Hua has been an active mentor in various student projects, honors theses, and national competitions like the National Cyber League. He’s also served on several doctoral committees, contributing to dissertations in educational leadership and adult learning. His efforts have earned him recognition as a dedicated mentor, innovator, and academic leader.

📚 Publication

AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques
📅 2025 | Big Data and Cognitive Computing
🧾 Cited by: 3 articles (as of early 2025)
👉 DOI: 10.3390/bdcc9010016

Mr. Jin Qilin  | Computer vision | Best Researcher Award

Mr. Jin Qilin  | Computer vision | Best Researcher Award

Hohai University, China.

Qilin Jin is a passionate researcher specializing in the application of artificial intelligence and software engineering. With a focus on integrating AI with real-world engineering challenges, he has made significant strides in areas such as sonar image analysis, defect detection, and structural monitoring. His innovative work has been recognized through impactful publications and contributions to the scientific community.

Profile

Orcid

🎓 Education

Qilin Jin is currently pursuing a Ph.D. in Computer Science, specializing in the applications of artificial intelligence and software engineering to solve complex real-world problems. His doctoral research focuses on leveraging advanced AI algorithms for defect detection and structural analysis. He holds a Master's Degree in Engineering, where his studies centered on intelligent systems and structural monitoring, providing a strong foundation for his innovative contributions to these fields.

💼 Experience

Qilin Jin is an accomplished researcher with extensive experience in developing AI-driven solutions tailored for industrial and engineering applications. His work focuses on creating innovative methods for defect detection and segmentation, leveraging cutting-edge artificial intelligence technologies to enhance accuracy and efficiency. As a dedicated collaborator, Qilin actively contributes to multidisciplinary projects, combining expertise from various domains to address complex challenges in structural monitoring and intelligent systems.

🔍 Research Interests

Artificial Intelligence Applications: Advanced algorithms for defect detection and structural analysis.

Software Engineering: Innovative methods to enhance engineering software development.

Deep Learning: Leveraging deep neural networks for real-time segmentation and detection tasks.

🏆 Awards and Recognitions

Young Innovator Award for contributions to AI-based defect detection in sonar imaging.

Recognized for excellence in research by leading journals like Applied Sciences and Journal of Sound and Vibration.

🖋️ Publications

  1. Jin, Qilin, Han Qingbang, Qian Jianhua, et al. "Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images," Applied Sciences, 2025, 15(2): 597.
    Cited by 5 articles.
  2. Jin Qilin, Han QingBang, Su NaNa, et al. "A deep learning and morphological method for concrete cracks detection," Journal of Circuits, Systems, and Computers, 2023, 4.
    Cited by 3 articles.
  3. Wu Yang, Han QingBang, Jin Qilin, et al. "LCA-YOLOv8-Seg: An Improved Lightweight YOLOv8-Seg for Real-Time Pixel-Level Crack Detection of Dams and Bridges," Applied Sciences, 2023, 13: 10583.
    Cited by 7 articles.
  4. Han YuFeng, Han QingBang, Zhang ShiGong, Su NaNa, Jin Qilin, Shan MingLei. "Semianalytical numerical iterative analysis for a one-dimensional second harmonic wave," Journal of Sound and Vibration, 2022, 8.
    Cited by 2 articles.