Yaqin Wu | Computer Science | Excellence in Research Award

Ms. Yaqin Wu | Computer Science | Excellence in Research Award

Shanxi Agricultural University | China

Ms. Yaqin Wu is an accomplished researcher and educator specializing in acoustic signal analysis, deep learning, and multimodal information fusion, with a research record reflecting 80 citations across 78 documents, 9 publications, and an h-index of 3. She holds a Master of Engineering in Electronic and Communication Engineering from Tianjin University and a Bachelor’s degree in Communication Engineering from Dalian Maritime University. Currently serving as a full-time faculty member at the School of Software, Shanxi Agricultural University, she teaches courses such as Speech Signal Processing, Natural Language Processing, and Human-Computer Interaction. Ms. Wu has led and contributed to several cutting-edge research projects, including pathological voice restoration, multimodal animal behavior monitoring, and AVS audio codec development. She has authored multiple SCI-indexed papers and holds several patents and software copyrights related to voice signal processing. Her technical proficiency spans Python, MATLAB, Linux systems, and MySQL databases. Notably, her master’s thesis earned the Outstanding Achievement Award of Engineering Master’s Practice from Tianjin University. Through her innovative contributions in signal processing and intelligent systems, Ms. Wu continues to advance the intersection of engineering and artificial intelligence research.

Profiles : Scopus | Orcid

Featured Publications

Zhang, J., Wu, Y., & Zhang, T. (2025). Fusing time-frequency heterogeneous features with cross-attention mechanism for pathological voice detection. Journal of Voice. Advance online publication.

Li, X., Wang, K., Chang, Y., Wu, Y., & Liu, J. (2025). Combining Kronecker-basis-representation tensor decomposition and total variational constraint for spectral computed tomography reconstruction. Photonics, 12(5), 492.

Seunghyun Oh | Computer Science | Best Researcher Award

Mr. Seunghyun Oh | Computer Science | Best Researcher Award

Yonsei University | South Korea

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Mr. Seunghyun Oh began his academic journey at the Global School of Media, Soongsil University, where he earned his Bachelor of Science degree in February 2025. Throughout his undergraduate studies, he demonstrated a strong aptitude for advanced technical subjects, securing A+ grades in key courses such as Image Processing, Computer Vision, and Machine Learning. His early academic record reflects a solid foundation in both theoretical concepts and applied computing.

💼 Professional Endeavors

Mr. Oh’s professional growth was marked by a series of impactful roles and experiences. In 2023, he joined the Reality Lab at Soongsil University, where he later served as Lab Leader and contributed as an undergraduate researcher until April 2025. His commitment extended beyond academia—he spearheaded a web development training initiative for a Cambodian team to build a school website, showcasing leadership and global engagement. Currently, he is working as a research intern at MAI-LAB, Yonsei University, where he continues to push the boundaries of machine intelligence.

🧠 Contributions and Research Focus

Mr. Oh’s research is centered on computer vision and medical artificial intelligence, with a particular focus on optimization and domain generalization. His notable project, Baseball Player Pose Corrector (BPPC), introduces a refined framework for enhancing 2D pose estimation using 3D motion priors. This work, accepted by ICT-Express (SCIE, IF: 4.1), highlights his innovative approach to human pose estimation in dynamic environments. Additionally, he is actively exploring feature-level domain generalization and disentanglement techniques to improve performance in ultrasound image segmentation, addressing efficiency concerns in medical imaging.

🏅 Accolades and Recognition

Mr. Oh’s dedication to research has already gained peer recognition. In 2024, he delivered an oral presentation at the Annual Symposium of KIPS (ASK 2024), showcasing his work on motion-guided pose correction. His accepted publication in a reputed journal further cements his status as a promising researcher in the field of AI-driven vision systems.

🌍 Impact and Influence

Beyond his technical contributions, Mr. Oh has had a tangible social and educational impact. His web training leadership for Cambodian school developers reflects a blend of technological expertise and social responsibility. Within research communities, he is known for his collaborative spirit and his ability to translate complex models into practical, optimized solutions—particularly in environments where precision and efficiency are critical, such as medical AI.

🔭 Legacy and Future Contributions

As he continues his journey in AI research, Mr. Seunghyun Oh is poised to make significant contributions to medical imaging, optimization algorithms, and domain generalization. His forward-thinking mindset, coupled with technical depth and leadership experience, positions him to be a transformative force in both academic and applied artificial intelligence research. With a strong publication record already underway and promising collaborations in progress, the future holds immense potential for this rising star in computer vision and medical AI.

Publications


📝 Accurate Baseball Player Pose Refinement Using Motion Prior Guidance

Authors: Seunghyun Oh, Heewon Kim
Journal: ICT Express
Year: 2025


📝 Motion Prior-Guided Refinement for Accurate Baseball Player Pose Estimation

Authors: Seunghyun Oh, Heewon Kim
Conference: Annual Conference of KIPS
Year: 2024


Bing Cai | Computer Science | Best Researcher Award

Mr. Bing Cai | Computer Science | Best Researcher Award

Anhui Institute of Information Technology | China

Author Profile

Scopus

Orcid

Google Scholar

Early Academic Pursuits 🎓

Mr. Bing Cai embarked on his academic journey with a strong foundation in engineering. He earned his Bachelor of Engineering in Electronics and Information Engineering from Anhui University in 2014, where he developed a keen interest in computing and information systems. His thirst for advanced knowledge led him to pursue a Master of Engineering in Computer Technology at Anhui Polytechnic University, completing his degree in 2024 with a commendable GPA of 3.36. His rigorous academic training laid the groundwork for his expertise in software development and multi-view clustering techniques.

Professional Endeavors 🌟

Mr. Cai has accumulated extensive professional experience in both academia and industry. From 2014 to 2017, he worked as a Software Engineer at iFLYTEK Co., Ltd., where he contributed to the development of Android and iOS applications. His responsibilities included designing app frameworks, optimizing performance, and conducting comprehensive testing for speech synthesis systems. His tenure at iFLYTEK honed his skills in software architecture, application development, and embedded systems testing. Transitioning to academia in 2017, Mr. Cai served as a Corporate Teacher at Anhui Institute of Information Technology. Here, he played a pivotal role in teaching Web Front-End Development, guiding students in research and graduation projects, and mentoring them for competitions. His ability to bridge theoretical knowledge with practical applications made him a valuable asset in the field of computer and software engineering education.

Contributions and Research Focus 📚

Mr. Cai's research primarily focuses on multi-view clustering, tensor subspace clustering, and machine learning methodologies. His scholarly contributions include several high-impact publications in prestigious journals such as IEEE Transactions on Multimedia, Pattern Recognition, and Signal Processing. His research introduces innovative clustering techniques using tensorized and low-rank representations, significantly advancing the field of multi-view learning. Notably, his studies on high-order manifold regularization and tensorized bipartite graph clustering have provided new insights into handling large-scale and incomplete multi-view data. His work is instrumental in improving data representation and clustering efficiency in artificial intelligence applications.

Accolades and Recognition 🏆

Mr. Cai's dedication to excellence has been recognized with several prestigious awards. In 2023, he won the Bronze Prize in the Anhui Province "Internet+" College Student Innovation and Entrepreneurship Competition, highlighting his innovative approach to problem-solving. He also received the Outstanding Paper Award from the Anhui Association for Artificial Intelligence in 2022, further cementing his reputation as a leading researcher in his field. His academic excellence was also acknowledged through the National Scholarship for Postgraduate Students in 2022, a testament to his scholarly contributions.

Impact and Influence 🌍

Mr. Cai's work has had a profound impact on both academia and industry. His contributions to multi-view clustering have influenced the development of more robust and efficient data analysis techniques in AI and machine learning. His research findings are widely cited, reflecting their significance in advancing computational intelligence. Furthermore, his role as an educator has shaped the next generation of computer scientists, inspiring students to engage in research and innovation.

Legacy and Future Contributions 🚀

With a strong foundation in research and industry, Mr. Cai is poised to make even greater contributions to the field of computer technology. His ongoing work in multi-view clustering and tensor-based machine learning will likely lead to more breakthroughs in AI-driven data processing. As he continues to explore innovative clustering methodologies, his research is expected to influence a wide range of applications, from big data analytics to artificial intelligence-driven decision-making systems. His commitment to excellence ensures that he will remain at the forefront of technological advancements in the years to come.

 

Publications


  • 📄 Multi-view subspace clustering with a consensus tensorized scaled simplex representation
    Author(s): Hao He, Bing Cai, Xinyu Wang
    Journal: Information Sciences
    Year: 2025-03


  • 📄 Tensorized Scaled Simplex Representation for Multi-View Clustering
    Author(s): Bing Cai, Gui-Fu Lu, Hua Li, Weihong Song
    Journal: IEEE Transactions on Multimedia
    Year: 2024


  • 📄 Aligned multi-view clustering for unmapped data via weighted tensor nuclear norm and adaptive graph learning
    Author(s): Bing Cai, Gui-Fu Lu, Liang Yao, Jiashan Wan
    Journal: Neurocomputing
    Year: 2024


  • 📄 Complete multi-view subspace clustering via auto-weighted combination of visible and latent views
    Author(s): Bing Cai, Gui-Fu Lu, Guangyan Ji, Weihong Song
    Journal: Information Sciences
    Year: 2024


  • 📄 Auto-weighted multi-view clustering with the use of an augmented view
    Author(s): Bing Cai, Gui-Fu Lu, Jiashan Wan, Yangfan Du
    Journal: Signal Processing
    Year: 2024


 

Doohyun Park | Computer Science | Best Researcher Award

Dr. Doohyun Park | Computer Science | Best Researcher Award

VUNO Inc. | South Korea

Author Profile

Orcid

Early Academic Pursuits 🎓

Dr. Doohyun Park embarked on his academic journey at Yonsei University, where he earned his Bachelor's degree in Electrical and Electronic Engineering (2012-2016). His deep interest in medical applications of technology led him to pursue a Ph.D. at the same institution. His doctoral thesis focused on artificial intelligence-based preoperative prediction of axillary lymph node metastasis in breast cancer using whole slide images, which showcases his commitment to integrating AI in healthcare. His academic path laid the foundation for his future contributions to biomedical research and medical image analysis.

Professional Endeavors 💼

Dr. Park’s professional career is marked by his significant role at VUNO Inc., where he is part of the Lung Vision AI team. His work involves the development of computer-aided detection and diagnosis (CADe/CADx) on lung CT, focusing on innovative solutions for lung health. He has also worked on projects assessing the severity of COVID-19 and anomaly detection in spine CT. His expertise in the intersection of AI and healthcare has positioned him as a key contributor to advanced diagnostic technologies, reflecting his ability to bridge academia and industry.

Contributions and Research Focus 🔬

Dr. Park's research interests are centered around biomedical and clinical research, with a particular emphasis on computer-aided detection, diagnosis, and medical image analysis. He has published numerous papers on topics ranging from deep learning-based joint effusion classification to the development of AI models for lung cancer screening. His research has garnered recognition in top-tier journals, reinforcing his role in advancing AI applications in healthcare. He also holds multiple international and domestic patents related to prognosis prediction using image features, underscoring his contributions to the global research community.

Accolades and Recognition 🏆

Dr. Park’s outstanding contributions to medical image analysis have earned him several prestigious awards. Notably, he won the Best Paper Award at the 2023 MICCAI Grand Challenge for Aorta Segmentation and secured third place in the competition. His academic excellence has also been recognized through scholarships, including the Brain Korea 21 Scholarship and various research and teaching assistant scholarships during his time at Yonsei University. His consistent track record of achievements highlights his dedication to both research and education.

Impact and Influence 🌍

Dr. Park's work has had a profound impact on the field of medical AI, particularly in improving diagnostic tools for lung and breast cancer. His development of cutting-edge algorithms for image analysis has the potential to revolutionize early detection and prognosis in clinical settings. His invited talks at high-profile forums like the Global Engagement & Empowerment Forum on Sustainable Development (GEEF) further showcase his influence on global health initiatives, particularly in the context of the United Nations' Sustainable Development Goals.

Legacy and Future Contributions ✨

As Dr. Park continues his career, his legacy is being built on the foundations of innovation, interdisciplinary collaboration, and a commitment to improving healthcare outcomes. His ongoing projects, including AI-based lung cancer screening and prognosis prediction for adenocarcinoma, promise to shape the future of diagnostic medicine. With a robust portfolio of patents, publications, and collaborative research, Dr. Park is poised to make lasting contributions to both academic and clinical communities, further solidifying his role as a pioneer in medical AI.

 

Publications


📝 Deep Learning-Based Joint Effusion Classification in Adult Knee Radiographs: A Multi-Center Prospective Study
Authors: Hyeyeon Won, Hye Sang Lee, Daemyung Youn, Doohyun Park, Taejoon Eo, Wooju Kim, Dosik Hwang
Journal: Diagnostics
Year: 2024


📝 M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography
Authors: Yunsu Byeon, Hyeseong Kim, Kyungwon Kim, Doohyun Park, Euijoon Choi, Dosik Hwang
Journal: Book Chapter
Year: 2024


📝 Weakly Supervised Deep Learning for Diagnosis of Multiple Vertebral Compression Fractures in CT
Authors: Euijoon Choi, Doohyun Park, Geonhui Son, Seongwon Bak, Taejoon Eo, Daemyung Youn, Dosik Hwang
Journal: European Radiology
Year: 2023


📝 Development and Validation of a Hybrid Deep Learning–Machine Learning Approach for Severity Assessment of COVID-19 and Other Pneumonias
Authors: Doohyun Park, Ryoungwoo Jang, Myung Jin Chung, Hyun Joon An, Seongwon Bak, Euijoon Choi, Dosik Hwang
Journal: Scientific Reports
Year: 2023


📝 Importance of CT Image Normalization in Radiomics Analysis: Prediction of 3-Year Recurrence-Free Survival in Non-Small Cell Lung Cancer
Authors: Doohyun Park, Daejoong Oh, MyungHoon Lee, Shin Yup Lee, Kyung Min Shin, Johnson SG Jun, Dosik Hwang
Journal: European Radiology
Year: 2022