Ms. Soree Hwang | Healthcare Intelligence Awards | Best Sensor for Health Monitoring Award

Ms. Soree Hwang, Korea Institute of Science and Technology (KIST), South Korea

So Ree Hwang is a dedicated researcher in the field of biomedical engineering currently pursuing her Ph.D. at Korea University. She holds a Master’s degree in Design and Engineering from Seoul National University of Science and Technology and a Bachelor’s degree in Mechanical Engineering from Korea Aerospace University. Since May 2022, she has been a student researcher at the Korea Institute of Science and Technology (KIST), where she contributes to the development of AI-based health management platforms, including lifelog acquisition systems and fatigue and stress detection technologies. Her research also focuses on gait analysis and stroke assessment using motion signal processing and wearable devices. So Ree has published numerous papers as a main and co-author in reputable journals such as Sensors, Frontiers in Human Neuroscience, and IEEE journals. Her work integrates machine learning and biomedical signal analysis to advance rehabilitation technologies and health monitoring systems.

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Summary of Suitability for Best Researcher Award – So Ree Hwang

Dr. So Ree Hwang is a highly suitable candidate for the Best Researcher Award in the domain of health monitoring and biomedical engineering, with a strong multidisciplinary background and an impressive portfolio of impactful, AI-integrated sensor-based research.

🎓 Education

Ph.D. in Biomedical Engineering
Korea University, Seoul, Republic of Korea (2021 – Present)
M.S. in Design and Engineering
Seoul National University of Science and Technology, Seoul, Republic of Korea (2018 – 2020)
B.S. in Mechanical Engineering
Korea Aerospace University, Goyang-si, Republic of Korea (2011 – 2017)

💼 Work Experience

Student Researcher – Korea Institute of Science and Technology (KIST)
📍 Seoul, Republic of Korea (2022.05.01 – Present)
- 🧠 Developed a lifelog system and AI-based fatigue/stress management platform
- 🚶‍♂️ Contributed to gait analysis tech for knee disorder recovery
- 🧪 Worked on motion signal-based stroke assessment technologies
Research Intern – Korea Institute of Science and Technology (KIST)
📍 Seoul, Republic of Korea (2020.03.01 – 2021.12.31)
- 🧠 Focused on stroke assessment using motion signal analysis

🏆 Achievements & Research Contributions

📝 8 SCI-indexed papers as main or co-author, including in top journals like Sensors, Frontiers in Human Neuroscience, and IEEE
- 📊 Topics: Gait phase classification, stroke severity assessment, fatigue detection using AI, wearable systems
⚙️ First-author of applied engineering papers on 3D printing and IMU validation
🤖 Integrated machine learning models (CNN-LSTM-Attention, RNNs) into biomedical signal analysis
🧩 Contributed to the advancement of intelligent health monitoring and gait recovery systems

Publication Top Notes:

Prediction of lower extremity multi-joint angles during overground walking by using a single IMU with a low frequency based on an LSTM recurrent neural network

CITED:50

Classification of stroke severity using clinically relevant symmetric gait features based on recursive feature elimination with cross-validation

CITED:20

Classification of gait phases based on a machine learning approach using muscle synergy

CITED:14

Property analysis of photo-polymerization-type 3d-printed structures based on multi-composite materials

CITED:8

Machine learning based abnormal gait classification with IMU considering joint impairment

CITED:5

User-centered Design of a Multi-material 3D Printer

CITED:1

Prof Dr. Isak Shabani, Faculty of Electrical and Computer Engineering, University of Prishtina, Albania

Isak Shabani, born on November 3, 1976, in Albania, is a distinguished Full Professor of Computer Engineering at the University of Prishtina’s Faculty of Electrical and Computer Engineering. He obtained his Bachelor’s degree in Computing and Telecommunication in 2002, followed by a Master’s degree in Computer Engineering in 2007, and a Ph.D. in Computer Sciences in 2012 from the same institution. Prof. Shabani’s research interests encompass a wide range of topics, including big data analytics, artificial intelligence, and cloud computing, with a particular focus on applications in government and healthcare. He has published extensively, with 58 scientific papers, 28 textbook chapters, and 128 abstracts to his name. His notable contributions include studies on IoT devices for health monitoring, student dropout rates, and electronic voting systems utilizing blockchain technology.

Education

PhD in Computer Sciences
University of Prishtina, Faculty of Electrical and Computer Engineering
Date: June 2, 2012

Magister of Computer Engineering
University of Prishtina, Faculty of Electrical and Computer Engineering
Date: July 7, 2007

Computing and Telecommunication
University of Prishtina, Faculty of Electrical and Computer Engineering
Date: April 17, 2002

Work Experience

Full Professor
University of Prishtina, Faculty of Electrical and Computer Engineering “Hasan Prishtina”
Date: September 10, 2022 – Present

[Previous Academic Positions]
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