Dr. Soyul Han, Seoul National University South, Korea
Soyul Han is a distinguished researcher specializing in data science and healthcare analytics. After completing her Ph.D. in Statistics from Chung-Ang University, Korea, she embarked on an academic and professional career focused on real-world big data applications, particularly in healthcare and medical data analysis. Soyul’s interdisciplinary expertise spans deep learning, signal processing, and big data, leading to groundbreaking contributions in heart murmur detection and voice spoofing. Her research is characterized by collaborations across various sectors, including academia and industry, with a strong emphasis on using cutting-edge technologies to enhance public health services.
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Suitability for the Research for Best Researcher Award
Soyul Han demonstrates exceptional potential for the ‘Research for Best Researcher Award’ based on her academic background, research contributions, and impactful publications. Holding a Ph.D. in Statistics from Chung-Ang University, Han has further honed her expertise through a postdoctoral position at Seoul National University and several research roles at prominent institutions. Her diverse experience, ranging from clinical research coordination to deep learning applications in healthcare, positions her as an outstanding candidate for this award.
Education
Soyul Han’s educational background is rooted in statistics, having completed her Ph.D. in 2024 at Chung-Ang University, Korea. Her dissertation, supervised by Il-Youp Kwak, explored innovative approaches to analyzing big healthcare data. She holds an M.S. in Statistics (2017) from the same institution and a B.S. in Statistics from Hannam University (2015). Her rigorous academic training, coupled with her hands-on research experience, has equipped her with the skills to develop data-driven solutions for complex healthcare problems.
Professional Experience
Soyul Han has built a distinguished career in academia and industry. Currently, she is a Postdoctoral Researcher at the Institute for Data Innovation in Science, Seoul National University. Her previous roles include Research Associate in both the Admissions Office and Analysis Department at Chung-Ang University, and clinical research coordinator at the National Cancer Center. With extensive experience in deep learning and big data analytics, Soyul has contributed to numerous projects, including data-driven healthcare innovations and participation in prestigious data competitions, such as the Audio Deepfake Detection challenge.
Awards and Recognition
Soyul Han’s work has been recognized internationally, with several notable awards. Her team’s success at the 2023 Audio Deepfake Detection Challenge, where they secured 3rd place, and the George B. Moody PhysioNet Challenges, where they earned recognition in two categories, highlights her expertise. Additionally, she has received recognition for her innovative contributions to healthcare data analysis, including multiple publications in high-impact journals such as Engineering Applications of Artificial Intelligence and The Korean Journal of Internal Medicine.
Research Skills
Soyul Han is skilled in statistical analysis, deep learning, and big data applications, particularly in healthcare. She has expertise in developing predictive models for heart murmur detection and voice spoofing, and has employed state-of-the-art technologies such as deep neural networks, deepfake detection systems, and data visualization techniques. Her research also involves the development of healthcare prognostic models using national insurance claims data, showcasing her ability to handle large, complex datasets and extract actionable insights.
Publictaion Top Notes
Title: Low-quality fake audio detection through frequency feature masking
- Authors: IY Kwak, S Choi, J Yang, Y Lee, S Han, S Oh
Citation: Proceedings of the 1st International Workshop on Deepfake Detection for …
Cited by: 13
Year: 2022
Title: Deep learning based heart murmur detection using frequency-time domain features of heartbeat sounds
- Authors: J Lee, T Kang, N Kim, S Han, H Won, W Gong, IY Kwak
Citation: 2022 Computing in Cardiology (CinC) 498, 1-4
Cited by: 12
Year: 2022
Title: Voice spoofing detection through residual network, max feature map, and depthwise separable convolution
- Authors: IY Kwak, S Kwag, J Lee, Y Jeon, J Hwang, HJ Choi, JH Yang, SY Han, …
Citation: IEEE Access 11, 49140-49152
Cited by: 11
Year: 2023
Title: Mastering data visualization with Python: practical tips for researchers
- Authors: S Han, IY Kwak
Citation: Journal of Minimally Invasive Surgery 26 (4), 167
Cited by: 9
Year: 2023
Title: Experimental Study: Enhancing Voice Spoofing Detection Models with wav2vec 2.0
- Authors: T Kang, S Han, S Choi, J Seo, S Chung, S Lee, S Oh, IY Kwak
Citation: arXiv preprint arXiv:2402.17127
Cited by: 6
Year: 2024