Xuechen Liang | Computer Science | Research Excellence Award

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Mr. Xuechen Liang | Computer Science | Research Excellence Award

Master | East China Jiaotong University | China

Mr. Xuechen Liang is a computer science researcher focused on large language models, multi-agent systems, and intelligent analysis in imperfect information settings. His research addresses commentary generation, strategic reasoning, and agent collaboration, with notable contributions to top-tier venues such as IJCAI, EACL, AAAI, and IEEE Access. His work spans personalized role-playing frameworks, self-evolving and memory-augmented agents, psycholinguistically inspired token reduction, and collaborative tuning methods to enhance model efficiency and performance. His scholarly output includes 7 research documents, receiving 8 citations, and reflects an h-index of 2, demonstrating growing academic impact in advanced AI and language model research.

Citation Metrics (Scopus)

10

8

6

4

2

0

Citations
8

Documents
7

h-index
2

Citations

Documents

h-index

Featured Publications

Self-Evolving Agents with Reflective Memory for Complex Decision Tasks

– arXiv Preprint, 2024

Mahir Sharif | Bioinformatics | Best Researcher Award

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Assist. Prof. Dr. Mahir Sharif | Bioinformatics | Best Researcher Award

Prince Sattam ibn Abdelaziz University | Saudi Arabia

Dr. Mahir M. Sharif is an accomplished academic and researcher in the field of Computer Science, specializing in Computational Intelligence and Bioinformatics. He has extensive experience in academia, research, and administration, complemented by leadership roles in multiple universities and colleges. His career reflects a strong commitment to innovation, digital transformation, and applied research in artificial intelligence, deep learning, and assistive technologies.

Publication Profile 

Scopus

Educational Background 

He holds a Ph.D. in Computer Science with a specialization in Computational Intelligence and Bioinformatics from Cairo University. He also earned an M.Sc. in Computer Science from Elneelain University and a B.Sc. in Computer Science from Omdurman Islamic University with distinction.

Professional Experience 

Dr. Sharif has served as an Associate Professor of Computer Science at Stars College for Medical Science and Technology and has held several academic positions, including Assistant Professor at Omdurman Islamic University, Prince Sattam ibn Abdel Aziz University, and other institutions. He has extensive teaching experience in computer science and has contributed as a professional trainer in computer skills and applications. Additionally, he has significant administrative experience, serving as Dean, Deputy Dean, and Head of Departments in various faculties, where he demonstrated strong leadership in academic governance and program development.

Research Interests 

His research focuses on artificial intelligence, deep learning, computational intelligence, bioinformatics, assistive technologies, and smart systems. His recent work includes developing advanced object detection models for visually impaired individuals, enhancing cybersecurity threat detection, and exploring AI-driven applications in IoT and smart cities.

Awards and Honors 

Dr. Sharif has received recognition for his contributions to academia and research through leadership roles, membership in scientific councils, and participation in international conferences and research forums. He has also led and contributed to several funded research projects, notably in AI-driven accessibility technologies and digital platforms for data management.

Research Skills 

He possesses strong expertise in artificial intelligence, machine learning, deep learning algorithms, object detection systems, computational modeling, bioinformatics, and the design of smart solutions. His skills also extend to managing research projects, supervising postgraduate research, and implementing innovative technology-driven approaches to real-world problems.

Publications 

  1. Leveraging Assistive Technology for Visually Impaired People Through Optimal Deep Transfer Learning Based Object Detection Model
    Year: 2025

  2. Advanced object detection for smart accessibility: a Yolov10 with marine predator algorithm to aid visually challenged people
    Year: 2025

  3. Feature enhancement model with up sampling based cyber threat attack detection and classification on imbalanced dataset in Industrial Internet of Things
    Year: 2025

  4. IoT in urban development: insight into smart city applications, case studies, challenges, and future prospects
    Year: 2025

  5. Artificial intelligence with greater cane rat algorithm driven robust speech emotion recognition approach
    Year: 2025

Conclusion 

Dr. Mahir M. Sharif exemplifies a dedicated researcher and academic leader with a strong track record in teaching, research, and administration. His contributions to artificial intelligence applications, assistive technologies, and digital innovation demonstrate his capability to bridge academic research with societal impact. His leadership in funded projects and involvement in international collaborations further highlights his commitment to advancing knowledge and technology for the betterment of education and community development.

Tianyi Yan | Computational Neuroscience | Best Researcher Award

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Prof. Dr. Tianyi Yan | Computational Neuroscience | Best Researcher Award

Vice Dean at School of Medical Technology, Beijing Institute of Technology, China

Tianyi Yan is a prominent researcher and educator in biomedical engineering, dedicated to exploring innovative solutions for brain health and cognitive enhancement. With numerous accolades and a rich publication record, he is shaping the future of neuroscience and technology integration. 🧠✨

Publication Profile : 

Scopus

 

🎓 Educational Background :

Tianyi Yan obtained a PhD in Biomedical Engineering from Okayama University, Japan, in 2004. He also holds an MSc in Biomedical Engineering from Kagawa University (2003) and a BSc in Electronic Engineering from Changchun University of Science and Technology, China (2001).

💼 Professional Experience :

Currently, he serves as the Vice Dean of the School of Medical Technology and the School of Life Sciences at the Beijing Institute of Technology (BIT) since March 2020. He has been a Professor at BIT since 2016 and the Director of the Department of Biomedical Engineering since July 2018. His academic journey began as a Lecturer at BIT in 2011, followed by a post-doctoral position at Okayama University.

📚 Research Interests : 

His research spans several areas, including Brain Science and Neuronal Engineering, Cognitive Neuroscience, Brain-Computer Interfaces, and non-invasive neuromodulation for brain disease diagnosis. He focuses on developing algorithms to study neural degenerative diseases, designing wearable devices for neural feedback, and advancing brain-controlled technologies.

📝 Publication Top Notes :

  1. Y. Yang, Q. Fan, T. Yan, J. Pei, and G. Li, “Network Group Partition and Core Placement Optimization for Neuromorphic Multi-Core and Multi-Chip Systems,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2024.
  2. Y. Huang, Y. Li, Y. Yuan, X. Zhang, W. Yan, T. Li, Y. Niu, M. Xu, T. Yan, X. Li, D. Li, J. Xiang, B. Wang, and T. Yan, “Beta-informativeness-diffusion multilayer graph embedding for brain network analysis,” Frontiers in Neuroscience, vol. 18, no. 1303741, 2024.
  3. S. Liu, M. Liu, D. Zhang, Z. Ming, Z. Liu, Q. Chen, L. Ma, J. Luo, J. Zhang, D. Suo, G. Pei, and T. Yan, “Brain-Controlled Hand Exoskeleton Based on Augmented Reality-Fused Stimulus Paradigm,” IEEE Journal of Biomedical and Health Informatics, 2024.
  4. S. Liu, Z. Ming, M. Liu, D. Zhang, Z. Liu, Q. Chen, L. Ma, J. Luo, D. Suo, J. Zhang, and T. Yan, “Remote-Oriented Brain-Controlled Unmanned Aerial Vehicle for IoT,” IEEE Internet of Things Journal, 2024.
  5. J. Wu, L. Ma, D. Luo, Z. Jin, L. Wang, L. Wang, T. Li, J. Zhang, T. Liu, D. Lv, T. Yan, and B. Fang, “Functional and structural gradients reveal atypical hierarchical organization of Parkinson’s disease,” Human Brain Mapping, vol. 45, no. 4, e26647, 2024.
  6. J. Lu, T. Yan, L. Yang, X. Zhang, J. Li, D. Li, J. Xiang, and B. Wang, “Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability,” NeuroImage, vol. 295, 2024, pp. 120651.
  7. M. Yao, O. Richter, G. Zhao, N. Qiao, Y. Xing, D. Wang, T. Hu, W. Fang, T. Demirci, M.D. Marchi, L. Deng, T. Yan, C. Nielsen, S. Sheik, C. Wu, Y. Tian, B. Xu, and G. Li, “Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip,” Nature Communications, vol. 15, no. 1, p. 4464, 2024.
  8. G. Wang, N. Jiang, Y. Ma, T. Liu, D. Chen, J. Wu, G. Li, D. Liang, and T. Yan, “Connectional-style-guided contextual representation learning for brain disease diagnosis,” Neural Networks, vol. 175, 2024, pp. 106296.
  9. G. Wang, N. Jiang, Y. Ma, D. Suo, T. Liu, S. Funahashi, and T. Yan, “Using a deep generation network reveals neuroanatomical specificity in hemispheres,” Patterns, vol. 5, no. 4, 2024.
  10. G. Wang, N. Jiang, T. Liu, L. Wang, D. Suo, D. Chen, S. Funahashi, and T. Yan, “Using unsupervised capsule neural network reveal spatial representations in the human brain,” Human Brain Mapping, vol. 45, no. 5, e26573, 2024.
  11. L. Wang, S. Li, L. Gong, Z. Zheng, Y. Chen, G. Chen, and T. Yan, “Right parietal repetitive transcranial magnetic stimulation in obsessive-compulsive disorder: A pilot study,” Asian Journal of Psychiatry, vol. 93, Mar. 2024, pp. 103902.
  12. T. Li, T. Liu, J. Zhang, Y. Ma, G. Wang, D. Suo, B. Yang, X. Wang, S. Funahashi, K. Zhang, B. Fang, and T. Yan, “Neurovascular coupling dysfunction of visual network organization in Parkinson’s disease,” Neurobiology of Disease, 2023, pp. 106323.
  13. J. Zhang, Y. Yang, T. Liu, Z. Shi, G. Pei, L. Wang, J. Wu, S. Funahashi, D. Suo, C. Wang, and T. Yan, “Functional connectivity in people at clinical and familial high risk for schizophrenia,” Psychiatry Research, vol. 328, 2023, pp. 115464.
  14. T. Yan, G. Wang, T. Liu, G. Li, C. Wang, and D. Suo, G. Pei, “Effects of Microstate Dynamic Brain Networks Disruption in Different Stages of Schizophrenia,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, vol. 31, 2023, pp. 2688-2697.
  15. T. Li, L. Wang, Z. Piao, K. Chen, X. Yu, Q. Wen, D. Suo, C. Zhang, S. Funahashi, G. Pei, B. Fang, and T. Yan, “Altered Neurovascular Coupling for Multidisciplinary Intensive Rehabilitation in Parkinson’s Disease,” The Journal of Neuroscience, vol. 1, no. 1, 2023, pp. 1204-1222.