Irina Karabulatova | Artificial Intelligence | Best Researcher Award

Prof. Dr. Irina Karabulatova | Artificial Intelligence | Best Researcher Award

Professor | Heilongjiang University | China

Prof. Dr. Irina S. Karabulatova is an internationally recognized philologist, linguist, and academician known for her pioneering research in applied linguistics, psycholinguistics, neurolinguistics, sociolinguistics, media linguistics, computational psycholinguistics, and digital humanities. She serves as Head of the Research Center for Digital Humanities at Heilongjiang University, Research Professor at RUDN-University, and Senior Researcher at Moscow State University’s Institute for Advanced Research in AI. She has trained more than sixty doctoral and PhD students from multiple countries, authored nearly five hundred publications across leading journals, and contributed to global knowledge in language, brain studies, NLP, emotional artificial intelligence, and cross-cultural communication. She is an elected member of the Russian and European Academies of Natural Sciences, with global academic influence spanning Russia, China, Europe, India, and Kazakhstan. Her career combines rigorous scientific scholarship with cultural preservation, academic leadership, and contributions to international collaboration in linguistics, AI, and intercultural communication.

Profile

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Education

Prof. Dr. Irina Karabulatova graduated with honors in philology from Arkalyk State Pedagogical Institute with a specialization in Russian language and literature. Her early academic focus was on toponymy and linguistic geography, culminating in her candidate dissertation on hydronyms of the Russian Rim, which established her as a rising scholar in Russian linguistics. She later defended her doctoral dissertation at Kuban State University on Russian toponymy in an ethno-psycholinguistic framework, combining theoretical linguistics with cultural identity studies. Her academic formation was marked by recognition from leading foundations supporting research excellence in culture and creativity. She pursued multiple advanced qualifications in philology and linguistics and was awarded the titles of associate professor and later full professor by the Higher Attestation Commission of the Russian Federation. Over her academic journey, she complemented her education with international internships in migration studies, cultural sociology, translation studies, and digital technologies, strengthening her interdisciplinary expertise in linguistics and humanities.

Professional Experience

Prof. Dr. Irina Karabulatova’s professional career spans academia, research, and international collaboration. She began as lecturer and professor at Russian universities before holding leadership positions at Tyumen State University, Kazan Federal University, and RUDN-University. She has served as professor, head of departments, and director of interdisciplinary research centers, combining linguistics with digital technologies, cultural studies, and artificial intelligence. Internationally, she has been visiting professor at universities in Kazakhstan, Turkey, China, Italy, and the United States, delivering courses on psycholinguistics, intercultural communication, digital linguistics, and verification of manipulative media markers. She has held senior research positions at Moscow State University, MIPT, and institutes of the Russian Academy of Sciences. Currently, she leads the Research Center for Digital Humanities at Heilongjiang University, China, where her work integrates NLP, emotional intelligence, and neurocognitive modeling. Her teaching, research supervision, and scientific expertise reflect global recognition, with doctoral students guided under her supervision across multiple continents.

Awards and Honors

Prof. Dr. Irina Karabulatova has received numerous prestigious awards and honors recognizing her contributions to philology, cultural preservation, and interdisciplinary research. She is a laureate of the N. Roerich International Prize for preservation of cultural values and peacemaking, and an Honored Worker of Culture of Kazakhstan. She has been awarded multiple national and international prizes including the All-Russian public award “Success” for women leaders in science, culture, and education, as well as certificates of honor and gratitude from universities, regional authorities, and cultural institutions in Russia, Kazakhstan, and Israel. Her achievements are highlighted by listings in major encyclopedias documenting leading migrationologists and psycholinguists of Russia. She has been recognized by academic, cultural, and governmental institutions for her scholarly books, research contributions, and active promotion of intercultural understanding. Her honors reflect her pioneering role in applied linguistics, psycholinguistics, media linguistics, cultural heritage, and the development of interdisciplinary fields in the digital humanities.

Research Focus

Prof. Dr. Irina Karabulatova’s research focus spans applied linguistics, psycholinguistics, neurolinguistics, sociolinguistics, migration studies, computational linguistics, NLP, sentiment analysis, emotionology, and digital humanities. She is credited with founding new applied branches of linguistics such as digital linguomigration, predictive onomastics, digital folkloristics, and academic emotionology. Her work investigates neuro-psycholinguistic mechanisms of communication, emotional intelligence, and emotional artificial intelligence. She has analyzed the transformation of linguistic consciousness among diasporas, bilingualism and ASD differentiation, social schizophrenia in aggressive media environments, and manipulative markers in mass communication. Her interdisciplinary projects address verification and detection of manipulative discourse, psycholinguistic expertise of digital texts, and digital profiling for sociocultural security. She integrates AI and machine learning into linguistics to model language, brain, and cognition interactions. Her current research emphasizes the preservation of ethnocultural codes, neurocognitive modeling of bilinguals, and the development of computational methods for automatic analysis of potentially dangerous discourses in media and intercultural communication.

Publication

Neuromorphic Elements as a First Step Towards Sociomorphic Systems
Year: 2025

The interpretations of Russian traditional song folklore in the Internet virtual space in the aspect of digital linguistic folklore studies
Year: 2025

Sociomorphic Neuromodeling in Academic Emotionology as an Integration of Neurocognitive and Psycholinguistic Knowledge in Artificial Intelligence
Year: 2025

Metaphorical Terminology in Ancient Texts of Traditional Chinese Medicine: Problems of Understanding and Translation
Year: 2024

Modeling the Socio-Economic and Demographic Development of Transborder Regions (The Example of the Russian-Chinese Border Territories)
Year: 2024

Conclusion

Prof. Dr. Irina S. Karabulatova is highly suitable for recognition through a research award, given her groundbreaking contributions, global academic engagement, and leadership in emerging fields of linguistics and digital humanities. Her innovative approaches to language, cognition, and artificial intelligence mark her as a distinguished scholar whose work continues to shape contemporary linguistic science and intercultural studies, making her a deserving candidate for international academic honors.

Pakezhamu Nuradili | Computer Science and Artificial Intelligence | Best Researcher Award

Dr. Pakezhamu Nuradili| Computer Science and Artificial Intelligence | Best Researcher Award

PhD candidate University of Electronic Science and Technology of China

Pakezhamu Nuradili, a native of China, is a Ph.D. student specializing in Information and Communication Engineering. She is currently enrolled in a joint Ph.D. program between the University of Electronic Science and Technology of China (UESTC) and the University of Trento, Italy. Her expertise spans deep learning-based image processing, semantic segmentation, and thermal infrared imaging. Known for her attention to detail and excellent communication skills in multiple languages, she excels in both technical and interpersonal domains.

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Education 🎓

  • High School: Jiangpu Senior High School, Jiangsu Province, China (2010–2013)
  • Bachelor’s Degree: Electronics and Information Engineering, Hebei University of Science and Technology (2013–2017)
  • Master’s Degree: Radio Physics, Yili Normal University, China, focusing on face recognition algorithms (2017–2020)
  • Ph.D.: Information and Communication Engineering, UESTC, with a joint program at the University of Trento, Italy (2021–Present)

Work Experience 💼

  • Teaching:
    • Substitute Teacher, Basic Computer Applications, Silk Road College of Ili (2017–2018)
    • Graduate Assistant, Basic Computer Applications, Yili Normal University (2018–2019)
    • Substitute Teacher, Advanced and Intermediate Mathematics, Ili Vocational and Technical College (2020–2021)
    • Graduate Teaching Assistant, Principles of Remote Sensing, UESTC (2022)
  • Volunteering: Marathon Distance Race Volunteer, Trento, Italy (2024)

Research Interests 🔬

Pakezhamu’s research focuses on:

  • Deep learning-based image processing and semantic segmentation.
  • Thermal infrared and multispectral imaging for UAV applications.
  • Wetland segmentation using advanced models like SegFormer.

Awards 🏆

  • Hebei Provincial Inspiration Scholarship (2016)
  • Outstanding Graduation Design Award, Hebei University of Science and Technology (2017)
  • Graduate Student Scholarship, Yili Normal University (2018)
  • Xinjiang Autonomous Region Postgraduate Scholarship (2019)
  • UESTC Academic Scholarships (2022, 2023, 2024)
  • Outstanding Teaching Assistant Award, UESTC (2022)

Publications Top Notes: 📚

P. Nuradili et al., “UAV Remote-Sensing Image Semantic Segmentation Strategy Based on Thermal Infrared and Multispectral Image Features,” IEEE Journal on Miniaturization for Air and Space Systems, 4(3): 311-319, Sept. 2023. Cited by: 5

Nuradili, P. et al., “Semantic segmentation for UAV low-light scenes based on deep learning and thermal infrared image features,” International Journal of Remote Sensing, 45(12): 4160–4177, 2024. Cited by: 8

Nuradili, P. et al., “Wetland Segmentation Method for UAV Multispectral Remote Sensing Images Based on SegFormer,” IGARSS 2024 IEEE Symposium, 2024. Cited by: 3

Nuradili, P. et al., “Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery,” Remote Sensing, 16(24): 4777, 2024. Cited by: 6

Nuradili, P. et al., “Fire Detection Based on Deep Learning Segmentation Methods,” Journal TBD, 2024 (Under Process).

Wang, Z. et al., “Removing temperature drift and temporal variation in thermal infrared images of a UAV uncooled thermal infrared imager,” ISPRS Journal of Photogrammetry and Remote Sensing, 203: 392-411, 2023. Cited by: 12