Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

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Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

Student, Guangxi University, China

Pingjie Ou is a passionate master’s student at Guangxi University, China, specializing in edge computing, cloud computing, and machine learning. With a strong academic foundation and growing research portfolio, he is actively contributing to next-generation computing paradigms. His early contributions in deep reinforcement learning applications for vehicular networks have already gained traction within the academic community. ๐Ÿง ๐Ÿ’ก

Professional Profile

Scopus

๐ŸŽ“ Education Background

Pingjie Ou is currently pursuing his master’s degree at Guangxi University, one of the prominent institutions in China. His academic focus lies in electrical and computer engineering, with emphasis on distributed computing and artificial intelligence. ๐Ÿ“˜๐Ÿซ

๐Ÿ’ผ Professional Experience

Although a student, Pingjie Ou has engaged in substantial research activities under funded projects including The National Natural Science Foundation of China (No. 62162003) and GuikeZY24212059 supported by the Guangxi Province. His active involvement in real-time research scenarios demonstrates promising professional potential. ๐Ÿ”ฌ๐Ÿ“Š

๐Ÿ… Awards and Honors

As an emerging scholar, Pingjie Ou has not yet accumulated major awards but has gained recognition through impactful publications and research citations. His growing citation record and h-index reflect the potential for future accolades. ๐Ÿ†๐Ÿ“ˆ

๐Ÿ” Research Focus

His core research interests include edge computing, cloud computing, vehicular networks, and machine learning. He is particularly focused on cooperative caching, resource management, and optimizing network efficiency using artificial intelligence approaches such as deep reinforcement learning. ๐Ÿš—โ˜๏ธ๐Ÿ“ถ

๐Ÿงพ Conclusion

Pingjie Ou is a driven young researcher dedicated to advancing intelligent computing technologies. With strong academic grounding, collaborative research exposure, and early citation impact, he stands as a promising candidate for recognition in the domain of computer science and engineering. His scholarly journey is on a clear upward trajectory. ๐Ÿš€๐Ÿ“š

๐Ÿ“š Publication Top Note

  1. PDRL-CM: An efficient cooperative caching management method for vehicular networks based on deep reinforcement learning
    ๐Ÿ“… Published Year: 2025
    ๐Ÿ“– Journal: Ad Hoc Networks
    ๐Ÿ”— 10.1016/j.adhoc.2025.103888

 

Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

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Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

PhD, ASIA UNIVERSITY, TAIWAN

Ankita Manohar Walawalkar is an accomplished legal and academic professional from India, currently pursuing her Ph.D. in Business Administration at Asia University, Taiwan, with a strong focus on Artificial Intelligence, Corporate Governance, Human Resource Management, and Supply Chain. With a unique blend of legal expertise and international business experience, Ankita has spent over two decades navigating corporate procurement, translation, teaching, and research. Fluent in English, Hindi, and Chinese, she bridges cultural and linguistic gaps, making her a versatile contributor in academia and international business diplomacy. Her academic versatility, fieldwork experience, and multilingual proficiency make her a standout scholar and practitioner on global platforms.

Publication Profile

๐ŸŽ“ Education Background

Ankita is presently enrolled in a Ph.D. program in Business Administration at Asia University, Taiwan (2023โ€“Present), focusing on interdisciplinary support areas such as AI, corporate governance, and HR. She holds a Master of Laws (LL.M.) in Corporate and Commercial Law from Amity University, Mumbai (2020โ€“2021), where she deepened her expertise in IP, company law, and securities. Her foundational legal education was completed with a BLS-LLB from KES Jayantilal H. Patel Law College, University of Mumbai (2014โ€“2020). Additionally, she completed a one-year Chinese Language Training at Zhengzhou University, China (2017โ€“2018) under the prestigious Confucius Institute Scholarship.

๐Ÿ’ผ Professional Experience

Ankita’s dynamic professional career spans corporate sourcing and academia. From 2021 to 2023, she worked as a Sourcing Specialist at Algol Chemicals India Pvt. Ltd., New Delhi, specializing in Chinese supplier coordination, procurement, and logistics compliance. She has over five years of experience as a Freelance Interpreter and Translator, working with companies like VOXCO Pigments, Podar Enterprise, and Kohinoor Group, and participating in over 15 international exhibitions and conferences including the China-India Economic and Trade Conference. At Asia University, she serves as an EMI Teaching Assistant, TA for the Rural AI Bilingual Program, and works with the IC OIA office while volunteering at the INGO Research Centre. Her freelance work includes judicial interpretations, educational instruction for YCT/HSK levels, and market research projects for global clients.

๐Ÿ† Awards and Honors

Ankita was awarded the Confucius Institute Scholarship for a year-long language training program at Zhengzhou University, China (2017โ€“2018), a testament to her dedication to language proficiency and cross-cultural studies. Her consistent participation in high-impact conferences and scholarly publications with global collaborators is a reflection of her ongoing academic recognition.

๐Ÿ”ฌ Research Focus

Ankitaโ€™s research interests are deeply rooted in AI Ethics, Corporate Governance, Human-AI Interaction, and Blockchain in HR, as reflected in her recent contributions to IGI Global book chapters and international conferences. She is actively involved in interdisciplinary explorations, combining law, ethics, and technology, with a notable focus on Human-AI collaboration in corporate decision-making, DEI challenges in hospital management, and the use of AI in education and language preservation.

๐Ÿ“Œ Conclusion

Ankita Manohar Walawalkarย  stands at the unique intersection of law, language, and artificial intelligence, bringing over 20 years of diverse administrative, academic, and international experience to her work. Her contributions across education, corporate sourcing, and AI ethics research demonstrate her commitment to global impact and ethical innovation. As she continues her doctoral journey, her voice in the field of AI governance and multilingual education is becoming increasingly influential.

๐Ÿ“ Top Publication Notes

  1. Foundations of AI Ethics โ€“ 2024, IGI Global
    Cited by: 3 articles (as of 2024)
    Authors: Walawalkar, A. M., Moslehpour, M., Phattanaviroj, T., & Kumar, S.

  2. Utilization of Blockchain Technology to Manage Human Resources Data: Security Issues in Government Agencies โ€“ 2024, IGI Global
    Cited by: 2 articles
    Authors: Yati, P. P., & Walawalkar, A.

  3. Data Ethics and Privacy โ€“ 2024, IGI Global
    Cited by: 2 articles
    Authors: Phattanaviroj, T., Moslehpour, M., & Walawalkar, A. M.

  4. The Future of Ethical AI โ€“ 2024, IGI Global
    Cited by: 3 articles
    Authors: Firmansyah, G., Bansal, S., Walawalkar, A. M., Kumar, S., & Chattopadhyay, S.

  5. Investigating Human-AI Collaboration in Corporate Decision-Making for Sustainable Business Practices: An Extended UTAUT2 Modelย โ€“ 2025 (Upcoming), ICHESPAN Conference
    Status: Accepted, not yet cited
    Authors: Walawalkar, A. M., Moslehpour, M., Gupta, V., Rizaldy, H.

Ulas Bagci | Artificial Intelligence | Outstanding Scientist Award

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Assoc. Prof. Dr. Ulas Bagci | Artificial Intelligence | Outstanding Scientist Award

Assoc. Prof., Northwestern University, United States

Dr. Ulas Bagci is a distinguished researcher and tenured Associate Professor at Northwestern University, specializing in Radiology, Electrical and Computer Engineering, and Biomedical Engineering. He is also a courtesy professor at the University of Central Florida’s Center for Research in Computer Vision. As the Director of the Machine and Hybrid Intelligence Lab, Dr. Bagci focuses on the integration of artificial intelligence, deep learning, and medical imaging. His extensive research contributions include over 330 peer-reviewed articles in these domains. Previously, he was a staff scientist and lab co-manager at the National Institutes of Health (NIH), where he played a pivotal role in advancing AI-driven medical imaging applications. Dr. Bagci actively contributes to leading scientific journals, serving as an associate editor for IEEE Transactions on Medical Imaging, Medical Physics, and Medical Image Analysis.

Publication Profile

๐ŸŽ“ Education

Dr. Ulas Bagci holds a Ph.D. in Computer Science from the University of Nottingham (2010), where he conducted pioneering research in medical imaging. He was a Visiting Research Fellow in Radiology at the University of Pennsylvania (2008-2009), further refining his expertise in AI applications for biomedical sciences. He earned his M.Sc. in Electrical and Computer Engineering from Koรง University (2005) and his B.Sc. in Electrical and Computer Engineering from Bilkent University (2003).

๐Ÿ’ผ Experience

Dr. Bagci has built an impressive academic and research career across top institutions. Since 2021, he has been an Associate Professor at Northwestern University, where he leads research in AI-driven medical imaging. Before that, he served as an Assistant Professor in Computer Science at the University of Central Florida (2014-2020), fostering innovation in deep learning for radiology. From 2010 to 2014, he was a Staff Scientist and Lab Manager at the National Institutes of Health (NIH), playing a key role in infectious disease imaging and AI applications in radiology.

๐Ÿ… Awards and Honors

Dr. Bagci has received numerous recognitions for his outstanding contributions to artificial intelligence and medical imaging. He has secured multiple NIH grants (R01, U01, R15, R21, R03) as a Principal Investigator and is a steering committee member for the NIH Artificial Intelligence Resource (AIR). Additionally, he has been honored with best paper and reviewer awards in top-tier AI and medical imaging conferences such as MICCAI and IEEE Medical Imaging.

๐Ÿ”ฌ Research Focus

Dr. Bagciโ€™s research revolves around artificial intelligence, deep learning, radiology, and computer vision. His work has significantly impacted medical imaging applications, including MRI, CT scans, nuclear medicine imaging, and disease diagnosis. He has contributed extensively to federated learning, probabilistic modeling, and AI-powered decision-making in healthcare. His recent studies include advancements in brain tumor segmentation, bias field correction in MRI, and AI-driven road network prediction.

๐Ÿ”š Conclusion

Dr. Ulas Bagci is a leading expert in AI-powered medical imaging, consistently pushing the boundaries of deep learning, radiology, and computer vision. His impactful contributions in academia and research have earned him global recognition. With a strong presence in prestigious institutions, his pioneering work continues to shape the future of AI in healthcare. ๐Ÿš€

๐Ÿ“š Publications

Evidential Federated Learning for Skin Lesion Image Classificationย (2025) โ€“ Published in a book chapter DOI: 10.1007/978-3-031-78110-0_23 ๐Ÿ“–

Paradoxical Response to Neoadjuvant Therapy in Undifferentiated Pleomorphic Sarcomaย (2025) โ€“ Published in Cancers DOI: 10.3390/cancers17050830 ๐Ÿฅ

Foundational Artificial Intelligence Models and Modern Medical Practiceย (2025) โ€“ Published in BJR | Artificial Intelligence DOI: 10.1093/bjrai/ubae018 ๐Ÿง 

A Probabilistic Hadamard U-Net for MRI Bias Field Correctionย (2024) โ€“ Published in arXiv arXiv:2403.05024 ๐Ÿ–ฅ๏ธ

AI-Powered Road Network Prediction with Fused Low-Resolution Satellite Imagery and GPS Trajectoryย (2024) โ€“ Published in Earth Science Informatics ๐ŸŒ

Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentationย (2024) โ€“ Presented at the IEEE/CVF Winter Conference on Applications of Computer Vision ๐Ÿค–

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation ย (2024) โ€“ Published in arXiv arXiv:2405.18383 ๐Ÿฅ