Saifullah Khalid | Artificial Intelligence | Innovative Research Award

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Dr. Saifullah Khalid | Artificial Intelligence | Innovative Research Award

Principal Scientist | IBMM RESEARCH | Sudan

Dr. Saifullah Khalid is a distinguished aviation and aerospace researcher renowned for his groundbreaking work in AI-driven aviation systems, air traffic management optimization, and unmanned aerial systems. With dual PhDs in engineering and a career spanning advanced aeronautical research, he serves as Principal Scientist at IBMM Research, Sudan. His academic background includes a PhD in Electronics and Communication Engineering from SN University, India (2013). Dr. Khalid’s expertise encompasses autonomous UAV systems, quantum-inspired optimization algorithms, sustainable aviation power systems, and digital tower operations. He has authored over 270 publications, including 38 Web of Science-indexed papers, and holds an impressive portfolio of 85 patents—50 as sole inventor—setting two world records for patent achievements. His professional experience extends to teaching and mentoring, supervising PhD candidates in AI-based air route optimization and guiding over 200 engineering projects. A committed academic leader, he has developed ICAO-compliant curricula and serves as Vice Chairman of the Academic Council Asia at NextGen University International. His awards include world records for patent excellence and international recognition for research innovation. His technical skills span MATLAB/Simulink, Python, UAV system design, and AI applications in aviation. 305 Citations; 67 Documents; h-index: 10

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Khalid, S., & Dwivedi, B. (2011). Power quality issues, problems, standards & their effects in industry with corrective means. International Journal of Advances in Engineering & Technology, 1(2), 1–11. Citations: 167

  2. Nishad, D. K., Tiwari, A. N., Khalid, S., Gupta, S., & Shukla, A. (2024). AI-based UPQC control technique for power quality optimization of railway transportation systems. Scientific Reports, 14(1), 17935. Citations: 31

  3. Khalid, S. (2018). Performance evaluation of Adaptive Tabu Search and Genetic Algorithm optimized shunt active power filter using neural network control for aircraft power utility of 400 Hz. Journal of Electrical Systems and Information Technology, 5(3), 723–734. Citations: 30

  4. Khalid, S., Dwivedi, B., Kumar, N., & Agrawal, N. (2007). A review of state-of-art techniques in active power filters and reactive power compensation. National Journal of Technology, 3(1), 10–18. Citations: 26

  5. Khalid, S., & Dwivedi, B. (2010). Power quality: An important aspect. International Journal of Engineering Science and Technology, 2(11), 6485–6490. Citations: 25

Rong Wang | Artificial Intelligence | Best Researcher Award

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Mrs. Rong Wang | Artificial Intelligence | Best Researcher Award

Postdoc | University of Tuebingen | Germany

Mrs. Rong Wang is a postdoctoral researcher at the Eberhard Karls University of Tübingen, Germany, specializing in computational linguistics and the evaluation and optimization of large language models (LLMs). She holds an M.Sc. in Computational Linguistics (NLP) from the University of Stuttgart (Grade: 1.7, 2024) and a Ph.D. in Digital Humanities from Zhejiang University, China (2016). Her interdisciplinary academic background bridges computer science, linguistics, and AI-driven humanities research, reflecting her ability to apply quantitative and symbolic methods to linguistic and cognitive studies. Professionally, she has served as a Postdoctoral Fellow at the University of Tübingen, AI Engineer at Telus International Digital AI, AGI Engineer Intern at Deepseek AI, Data Scientist at DEKRA GmbH, and Assistant Professor of Linguistics at Hangzhou Dianzi University. Her research focuses on language model evaluation metrics, neural-symbolic reasoning, multimodal semantics, and automated linguistic assessment. She has contributed to projects on enhancing spatial reasoning in LLMs, multi-agent AI systems, and personality recognition models, alongside authoring several publications on machine learning applications in cognitive linguistics and NLP evaluation. Technically proficient in Python, R, JavaScript, and SQL, she is experienced with frameworks such as LangChain, Autogen, Hugging Face, and PyTorch, and cloud platforms including Azure ML and AWS SageMaker. Her certifications include Azure Certified Data Scientist Associate and AWS Certified AI Practitioner. Mrs. Wang is fluent in English, German, and Chinese, with working knowledge of Japanese, and is recognized for her strong teamwork, communication, and leadership abilities. Her recent works have appeared in Data Intelligence, Psychology Methods, and TMLR, demonstrating her innovative contributions to the AI and NLP research community. (0 Citations ; 2 Documents ; 0 h-index.)

Profiles: Scopus | ResearchGate

Featured Publications

Wang, R., Sun, K., & Kuhn, J. (2024, Dec). Dspy-based neural-symbolic pipeline to enhance spatial reasoning in LLMs [Preprint]. arXiv. https://arxiv.org/abs/2411.18564

Wang, R., Sun, K., & Kuhn, J. (2024, Nov). A pipeline of neural-symbolic integration to enhance spatial reasoning in large language models [Preprint]. arXiv. https://arxiv.org/abs/2411.18564

Sun, K., & Wang, R. (2024, Oct). The roles of contextual semantic relevance metrics in human visual processing [Preprint]. arXiv. https://arxiv.org/abs/2410.09921

Wang, R., & Sun, K. (2024, Jul). A novel dependency framework for enhancing discourse data analysis [Preprint]. arXiv. https://arxiv.org/abs/2407.12473

Wang, R., & Sun, K. (2024, Jun). Continuous output personality detection models via mixed strategy training [Article]. arXiv. https://arxiv.org/abs/2406.16223

Feng Mao | Cognitive Science | Best Researcher Award

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Assist. Prof. Dr. Feng Mao | Cognitive Science | Best Researcher Award

Associate Professor | Shanghai University of International Business and Economics | China

Assist. Prof. Dr. Feng Mao is a distinguished Associate Professor and Senior Translator at Shanghai University of International Business and Economics with 28 years of higher education experience, specializing in country and area studies, translation studies, and foreign language education. He is currently pursuing a Ph.D. at Shanghai International Studies University (since 2022) and serves as a Master’s supervisor for MA in Linguistics and MTI programs. Over his career, he has led 11 research projects, including a national-level Social Science Fund project, and collaborated with international scholars from Singapore, Canada, the UK, and Germany, reflecting his strong global research network. His professional experience includes mentoring MA students, peer reviewing for SSCI and AHCI journals, editorial committee service, and contributions to national professional assessments, including CATTI examination grading. His research interests focus on translation and interpreting studies, foreign language education and policy, cross-cultural communication, applied linguistics, audiovisual translation, and country and area studies. MAO Feng has developed advanced research skills in big data analysis for textbook and material compilation, literary analysis, audiovisual translation methods, and educational program evaluation, supporting both theoretical and applied projects. He has authored 64 academic publications, including 20 SSCI/AHCI journal papers with 5 in Q1 journals, and published 5 academic monographs and translations totaling over 2 million words, alongside textbooks and review articles that serve thousands of students. He has also contributed to industry and government consultancy projects such as cultural brand promotion and copyright export research. His awards and honors include national-level recognition for professional degree assessment and leadership roles within the China Association for Educational Linguistics and the Translators Association of China. Overall, MAO Feng’s extensive research, teaching, publications, and international collaborations highlight his exceptional academic leadership and ongoing potential to advance translation studies and foreign language education globally. 7 Citations, 8 Documents, h-index 2.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

Mao, F., & Yang, X. (2024). Literary therapy based on positive psychology: Impact on college students’ happiness. Journal of Poetry Therapy, 37(1), 16–34. https://doi.org/[insert DOI] (Citations: 5)

Mao, F., & Liu, S. (2024). Book review: Networked feminism: How digital media makers transformed gender justice movements (R. Clark-Parsons, California, University of California Press, 2022). Feminist Media Studies, 24(2), 404–406. (Citations: 3)

Feng, M., Wenhui, L., Xinle, Y., & Biyu, W. (2022). Romantic narrative in the film The Battle at Lake Changjin. International Journal of English and Comparative Literary Studies, 3(1), 19–27. (Citations: 3)

Feng, M., Quan, L., & Wu, B. (2021). A review on the compilation of college English textbooks in China based on big data. Sino-US English Teaching, 18(3), 60–65. (Citations: 3)

Feng, M., Quan, L., & Biyu, W. (2021). Exploration of the compilation of English learning materials for Chinese college students based on big data under the guidance of complex dynamic theory. International Journal of Linguistics, Literature and Translation, 4(3), 22–32. (Citations: 2)