Assoc. Prof. Dr. Shengbin Liang | Data Mining | Excellence in Research Award

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Assoc. Prof. Dr. Shengbin Liang | Data Mining | Excellence in Research Award 

Assoc. Prof. Dr. Shengbin Liang | Data Mining | Henan University | China

Assoc. Prof. Dr. Shengbin Liang, a distinguished academic from Henan University, China, has emerged as a leading researcher in the fields of Precision Medicine, Artificial Intelligence, Deep Learning, and Swarm Intelligence Algorithms. He earned his Master’s degree in Computer Science from Southwest Jiaotong University, China, and later obtained his Ph.D. in Data Science from the City University of Macau, China, where he developed a strong foundation in computational modeling and data-driven healthcare applications. Currently, Assoc. Prof. Dr. Shengbin Liang serves as an Associate Professor at Henan University, while also holding a Postdoctoral Fellowship at the University of Saint Joseph, funded by the FDCT, Macau. His professional experience spans interdisciplinary research collaborations that bridge computer science, data science, and medical informatics, focusing on intelligent diagnostic systems and clinical decision-making through machine learning and deep learning frameworks. His research interests encompass recommendation systems, swarm intelligence optimization, biomedical data analysis, medical text classification, and AI-based healthcare prediction models. Demonstrating exceptional research capability, he has published over 20 SCI/EI-indexed papers in reputed international journals and conferences such as IEEE Transactions, PLOS One, Applied Sciences, and Knowledge and Information Systems, earning more than 180 citations on Scopus. His research skills include expertise in Python, TensorFlow, PyTorch, deep neural network architectures, sentiment analysis models, and multimodal data fusion for healthcare applications. In recognition of his academic excellence, Assoc. Prof. Dr. Shengbin Liang has been granted three national invention patents and has received institutional honors for his innovation and scientific contributions. He is also an active member of the IEEE community, contributing to collaborative research, peer review, and international AI conferences.

Professional Profiles: Google Scholar

Selected Publications

  1. Liang, S., Jiao, T., Du, W., & Qu, S. (2021). An improved ant colony optimization algorithm based on context for tourism route planning. PLoS One, 16(9), e0257317. (Cited by 66)

  2. Liang, S., Zhu, B., Zhang, Y., Cheng, S., & Jin, J. (2020). A double channel CNN-LSTM model for text classification. IEEE International Conference on High Performance Computing and Communications. (Cited by 32)

  3. Li, X., Zhang, Y., Jin, J., Sun, F., Li, N., & Liang, S. (2023). A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications. PLoS One, 18(3), e0282824. (Cited by 19)

  4. Liang, S., Chen, X., Ma, J., Du, W., & Ma, H. (2021). An improved double channel long short‐term memory model for medical text classification. Journal of Healthcare Engineering, 2021(1), 6664893. (Cited by 13)

  5. Liang, S., Jin, J., Ren, J., Du, W., & Qu, S. (2023). An improved dual-channel deep Q-network model for tourism recommendation. Big Data, 11(4), 268–281. (Cited by 9)

  6. Qu, S., Zhou, H., Zhang, B., & Liang, S. (2022). MSPNet: Multi-scale strip pooling network for road extraction from remote sensing images. Applied Sciences, 12(8), 4068. (Cited by 9)

  7. Cui, Y., Liang, S., & Zhang, Y. Y. (2024). Multimodal representation learning for tourism recommendation with two-tower architecture. PLoS One, 19(2), e0299370. (Cited by 7)

Dr. Kianoosh Boroojeni | Data Fusion Awards | Best Researcher Award

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Dr. Kianoosh Boroojeni | Data Fusion Awards | Best Researcher Award 

Dr. Kianoosh Boroojeni, Florida International University, United States

Dr. Kianoosh Boroojeni is an Associate Teaching Professor at the Knight Foundation School of Computing & Information Sciences, Florida International University (FIU). He earned his Ph.D. and M.S. in Computer Science from FIU and a B.Eng. in Computer Engineering from the University of Tehran. His research interests include cybersecurity, generative AI in computer science education, STEM education, and computer networks. With over 50 scientific publications and more than 1,150 citations, Dr. Boroojeni has made significant contributions to his field. He has played a pivotal role in integrating AI-powered tools into computer science education and has collaborated with Google to enhance programming courses. His leadership extends to overseeing programming gateway courses, developing cybersecurity curricula, and promoting inclusive computing education. He has received multiple teaching recognitions and actively mentors students.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award – Kianoosh Boroojeni

Dr. Kianoosh Boroojeni is a highly accomplished researcher and educator in cybersecurity, AI in education, and computer networks, making him a strong candidate for the Best Researcher Award. His academic background, extensive research contributions, and leadership in integrating AI into education highlight his impact in the field.

Education 📚

  • Ph.D., Computer Science – Florida International University, USA (2017)
  • M.S., Computer Science – Florida International University, USA (2016)
  • B.Eng., Computer Engineering – University of Tehran, Iran (2012)

Work Experience 💼

🔹 Associate Teaching Professor – Florida International University (2023 – Present)

  • Leads Programming Gateway Committee to improve programming course success rates 📊
  • Collaborates with Google to integrate Generative AI in CS education 🤖
  • Chairs Faculty & Staff Awards Committee in the College of Engineering & Computing 🏆
  • Supports intensive programming courses like CS I, II & III, Data Structures, and OS 💾

🔹 Assistant Teaching Professor – Florida International University (2017 – 2023)

  • Taught 16+ undergraduate courses and 4 graduate/Ph.D. courses 🏫
  • Developed new cybersecurity courses on Blockchains 🔐
  • Led Google’s Tech-Exchange Program to recruit Hispanic & Black students into Google workforce 🌍
  • Designed and improved online courses to achieve Quality Matters (QM) Certifications ✅
  • Achieved high student evaluations (4.6/5.0 overall) 📈

🔹 Post-Doctoral Fellow – Florida International University (Spring & Summer 2017)

  • Conducted DoD-funded research on network security & privacy 🔎
  • Mentored students in NSF-sponsored Research Experience program 👨‍🏫

🔹 Graduate Assistant – Florida International University (2012 – 2017)

  • Assisted faculty in teaching & grading multiple undergraduate/graduate courses ✍️
  • Collaborated with researchers from Carnegie Mellon & University of British Columbia 🤝

Achievements & Awards 🏅

🏆 Published 50+ scientific papers with 1150+ citations (h-index: 19) 📄
🏆 Led Google-FIU collaboration to integrate LLM-powered AI tools in CS education 🤖
🏆 Chaired Programming Gateway Committee to improve programming course completion rates 🎯
🏆 Successfully developed and taught two new cybersecurity courses on Blockchain 🔐
🏆 Achieved high teaching ratings (4.6/5.0) for multiple CS courses 📊
🏆 Contributed to NSF & DoD research projects on cybersecurity and network security 🏛

Publication Top Notes:

Fundamentals of brooks-iyengar distributed sensing algorithm: Trends, advances, and future prospects

A Multi-time-scale Time Series Analysis for Click Fraud Forecasting using Binary Labeled Imbalanced Dataset