Murtaza Hussain | Artificial Intelligence | Best Researcher Award

Mr. Murtaza Hussain | Artificial Intelligence | Best Researcher Award

PhD Research Scholar at Xi’an Jiaotong University, Singapore

Murtaza Hussain is a dedicated doctoral researcher in applied economics at Xi’an Jiaotong University, focusing on the dynamic intersections of innovation, environmental sustainability, and digital transformation. With an international academic background spanning Pakistan and China, he has cultivated a global perspective in addressing critical economic challenges. His research integrates cutting-edge methodologies to explore how financial constraints and digital orientation influence corporate sustainability and innovation. Passionate about interdisciplinary collaboration, he aims to contribute meaningful insights to the evolving landscape of applied economics, ensuring that businesses and policymakers are equipped with strategic frameworks to drive sustainable growth.

Profile

Orcid

Education

Murtaza Hussain is currently pursuing a Ph.D. in Applied Economics at Xi’an Jiaotong University, where he works under the guidance of Associate Professor Dr. Shaohua Yang. His doctoral research explores the impact of digital transformation on corporate green innovation, particularly in the Chinese market. Prior to his Ph.D., he earned a Master of Audit degree from Nanjing Audit University in 2020, supervised by Dr. Chien-Yu Huang. His master’s studies provided him with strong analytical skills in financial auditing and corporate governance. Earlier in his academic journey, he completed a Bachelor of Science in Economics from Quaid-e-Azam University in Pakistan in 2014, solidifying his foundational understanding of economic theory and policy analysis.

Experience

Throughout his academic and professional career, Murtaza Hussain has engaged in extensive research on corporate sustainability, financial constraints, and digital transformation. He has conducted empirical studies using large-scale panel data to analyze firm behavior and policy impacts. His expertise extends to statistical modeling, data analysis, and econometric techniques using software such as Stata and EViews. Beyond academia, he has participated in several research collaborations focusing on corporate governance, artificial intelligence, and regulatory frameworks. Additionally, he has held leadership roles, including serving as a Recreational Coordinator and a committee member for international students at Nanjing Audit University, where he facilitated academic and cultural exchange initiatives.

Research Interests

Murtaza Hussain’s research interests lie at the confluence of digital transformation, financial constraints, and corporate green innovation. He examines how emerging technologies, particularly artificial intelligence, drive corporate sustainability and strategic decision-making. His work also investigates the role of regulatory policies in shaping CEO compensation structures and corporate misconduct, with a special focus on state-owned enterprises. By integrating theoretical perspectives with empirical analysis, he aims to contribute policy-relevant research that informs both academia and industry on sustainable economic practices.

Awards

Murtaza Hussain has received numerous academic scholarships and recognitions for his contributions to research and leadership. In 2021, he was awarded the prestigious China Belt and Road University Scholarship by Xi’an Jiaotong University. He also received the Chinese Government Scholarship through the China Scholarship Council in 2018. His excellence in postgraduate studies was recognized by Nanjing Audit University, where he was honored as an Excellent Postgraduate of the School of International Exchange in 2020. Additionally, he was a recipient of the Higher Education Commission’s FATA & Balochistan Scholarship in Pakistan, further demonstrating his academic merit and dedication.

Publications

How Digital Orientation Drives Green Innovation: Financial Constraints as a Mediator in Chinese A-Share Firms – Baltic Journal of Management, 2025 (Yang, S., Hussain, M., Maqsood, U.S., Younas, M.W., Zahid, R.M.A.)

Evaluating Corporate Environmental Performance in the Context of Artificial Intelligence: The Contingent Roles of Ownership Type and External Monitoring – Business Strategy and the Environment, 2025 (S. Wang, Y. Yong, M. Hussain, U.S. Maqsood, R.M.A. Zahid)

Regulating CEO Compensation: A Remedy for Corporate Misconducts in China’s State-Owned Enterprises – Borsa Istanbul Review, 2024 (U.S. Maqsood, Q. Li, H. Hussain, M. Hussain, R.M.A. Zahid)

Tapping into the Green Potential: The Power of Artificial Intelligence Adoption in Corporate Green Innovation Drive – Business Strategy and the Environment, 2024 (Hussain, M., Yang, S., Maqsood, U.S., Zahid, R.M.A.)

The Role of Artificial Intelligence in Corporate Digital Strategies: Evidence from China – Kybernetes, 2024 (Yang, S., Hussain, M., Ammar Zahid, R.M., Maqsood, U.S.)

Conclusion

Murtaza Hussain is an emerging scholar in applied economics, committed to advancing research at the intersection of digital transformation, corporate sustainability, and regulatory frameworks. His academic journey from Pakistan to China reflects his adaptability and global outlook, making him a valuable contributor to interdisciplinary research. Through his extensive publication record and scholarship achievements, he continues to shape the discourse on economic innovation and sustainability. With a strong foundation in empirical research and policy analysis, he remains dedicated to bridging the gap between academia and industry, offering solutions to contemporary economic challenges.

Muyang Li | Deep learning | Best Researcher Award

Mr Muyang Li | Deep learning | Best Researcher Award

Tianjin University,  China

Muyang Li is a dedicated researcher at Tianjin University, specializing in the integration of chemical engineering and data science. Currently pursuing his Master’s degree, he has already made significant contributions to the fields of crystallization process optimization, material property prediction, and AI-driven image analysis.

Profile:

🎓 Education:

  • M.S. in Chemical Engineering and Technology (2022–Present), Tianjin University
  • B.S. in Chemical Engineering and Technology (2018–2022), Tianjin University

🔬 Research Focus:

Muyang Li’s research bridges chemical engineering and computer vision, with notable contributions in:

  • Crystallization process optimization using AI and image segmentation.
  • Developing novel methodologies for virtual dataset synthesis and material property prediction.
  • Implementing deep learning techniques (e.g., CNNs, Transformers, YOLOv8) for enhanced industrial applications.

🏆 Achievements:

  • Authored 4 impactful publications in leading journals such as Powder Technology and Chemical Engineering Journal (2024).
  • Recipient of prestigious awards, including the Samsung Scholarship (2020) and First-Class Scholarship for Master Students (2022).
  • Recognized as an Excellent Graduate of Tianjin University (2022).

🧪 Key Research Contributions:

  • Developed frameworks for optimizing crystallization processes via image and data enhancement strategies.
  • Pioneered methods for synthesizing virtual datasets using advanced neural networks like CoCosNet.
  • Advanced deep-learning applications for material properties prediction and dynamic emulsion analysis.

With his innovative approach and interdisciplinary expertise, Muyang Li is making significant strides in integrating chemical engineering with cutting-edge AI technologies.

Publication Top Notes:

1. Enhanced Powder Characteristics of Succinic Acid through Crystallization Techniques for Food Industry Application

  • Authors: Hutagaol, T.J., Liu, J., Li, M., Gao, Z., Gong, J.
  • Journal: Journal of Food Engineering
  • Year: 2025, Volume: 388, Article: 112376
  • Focus: Improved powder properties of succinic acid via advanced crystallization techniques tailored for food industry applications.
  • Citations: 0

2. Modeling and Validation of Multi-Objective Optimization for Mixed Xylene Hybrid Distillation/Crystallization Process

  • Authors: Chen, W., Yao, T., Liu, J., Gao, Z., Gong, J.
  • Journal: Separation and Purification Technology
  • Year: 2025, Volume: 354, Article: 128778
  • Focus: Multi-objective optimization model validation for hybrid distillation/crystallization in mixed xylene processing.
  • Citations: 0

3. A Deep Learning-Powered Intelligent Microdroplet Analysis Workflow for In-Situ Monitoring and Evaluation of a Dynamic Emulsion

  • Authors: Liu, J., Li, M., Cai, J., Gao, Z., Gong, J.
  • Journal: Chemical Engineering Journal
  • Year: 2024, Volume: 499, Article: 155927
  • Focus: Advanced deep-learning workflows for real-time dynamic emulsion monitoring.
  • Citations: 0

4. Predicting Crystalline Material Properties with AI: Bridging Molecular to Particle Scales

  • Authors: Chen, W., Li, M., Yao, T., Gao, Z., Gong, J.
  • Journal: Industrial and Engineering Chemistry Research
  • Year: 2024, Volume: 63(43), pp. 18241–18262
  • Type: Review
  • Focus: Utilizing AI for predicting crystalline material properties from molecular to particle scales.
  • Citations: 0

5. Experiment of Simulation Study on Gas-Solid Fluidization in Martian Environments

  • Authors: Ma, Y., Li, M., Ma, Z., Zhang, L., Liu, M.
  • Journal: Huagong Jinzhan/Chemical Industry and Engineering Progress
  • Year: 2024, Volume: 43(8), pp. 4203–4209
  • Focus: Simulation studies of gas-solid fluidization under Martian environmental conditions.
  • Citations: 0

6. Deep-Learning Based In-Situ Micrograph Analysis of High-Density Crystallization Slurry Using Image and Data Enhancement Strategy

  • Authors: Li, M., Liu, J., Yao, T., Gao, Z., Gong, J.
  • Journal: Powder Technology
  • Year: 2024, Volume: 437, Article: 119582
  • Focus: Application of deep-learning techniques for analyzing high-density crystallization slurry micrographs.
  • Citations: 2