Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award

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Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award 

Ms. Minkyung Sung, Chung-Ang University, South Korea

Min-Kyung Sung is a dedicated Master’s student at the Department of Artificial Intelligence at Chung-Ang University, where she studies under the guidance of Professor Jaesung Lee. With a Bachelor of Science degree in Software from Anyang University, she has developed a strong foundation in artificial intelligence and image segmentation, particularly focusing on on-device AI applications. Min-Kyung has made significant contributions to the field, publishing her work in prominent international conferences such as the IEEE International Conference on Consumer Electronics and presenting research on open vocabulary segmentation based on vision-language pre-trained models. Her recent projects include developing a deep learning CT shortening algorithm for structural adhesive inspection at Hyundai and an AI pediatric behavioral analysis system for children with autism spectrum disorder (ASD). Recognized for her excellence, she received the Best Paper Award at the Spring Academic Conference of the Korean Society for Emotion and Sensibility in 2023. Proficient in Python, LaTeX, and various machine learning tools such as PyTorch and TensorFlow, Min-Kyung is poised to make significant advancements in the artificial intelligence domain.

Professional Profile:

GOOGLE SCHOLAR

Suitability for the Research for Best Researcher Award: Min-Kyung Sung

Min-Kyung Sung is an exemplary candidate for the Research for Best Researcher Award, showcasing significant achievements in artificial intelligence and image segmentation through a blend of rigorous academic training and impactful research contributions.

🎓 Education

  • Master’s Student in Department of AI, Chung-Ang University (2023 – Present)
    Academic Adviser: Prof. Jaesung Lee
  • B.S. in Software Engineering at Anyang University (2019 – 2023)

💼 Work Experience

  • Researcher at Chung-Ang University, focusing on Artificial Intelligence and Image Segmentation.
  • Project Contributor for various AI-related projects including:
    • Development of a Deep Learning CT Shortening Algorithm for Hyundai (2024 – Present)
    • AI Pediatric Behavioral Analysis System for ASD (March 2023 – July 2023)
    • Virtual-based Diet Assistant Application (March 2022 – November 2022)
    • Participation in the AI Bookathon Competition (November 2021)

🏆 Achievements

  • Best Paper Award at the Spring Academic Conference (Korean Society for Emotion and Sensibility, 2023) for outstanding research contributions.

🏅 Awards and Honors

  • 2023: Best Paper Award at the Spring Academic Conference, Korean Society for Emotion and Sensibility.

🛠️ Skills

  • Programming Languages: Python, LaTeX, Git, Android platforms
  • Machine Learning Tools: PyTorch, TensorFlow, scikit-learn

Publication Top Notes:

 

Ms. Hyunseo Kim | Computer Vision Awards | Best Researcher Award

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Ms. Hyunseo Kim | Computer Vision Awards | Best Researcher Award 

Ms. Hyunseo Kim, Konkuk University, South Korea

Hyunseo Kim is an ambitious student pursuing dual degrees in Biomedical Science and Engineering and Computer Science and Engineering at Konkuk University in Seoul, South Korea. With a strong focus on applying artificial intelligence techniques to the medical domain, he is currently engaged in research at the AI & CV Lab, where he works on projects involving computer vision and audio data for medical applications, including MRI data analysis and hearing loss classification. Hyunseo’s passion for healthcare technology led him to participate in various competitions, winning first place in a medical hackathon for developing a drug side effect management program and third place in a software convergence competition for creating a DNA editing application. Fluent in Korean and proficient in English and Chinese, he is well-equipped for interdisciplinary collaboration. As he approaches graduation, Hyunseo is eager to leverage his skills in AI and programming to contribute to advancements in healthcare and improve the quality of life for individuals.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Hyunseo Kim

Hyunseo Kim demonstrates a strong foundation in interdisciplinary research and technological innovation, making her a promising candidate for the Best Researcher Award. Below is an evaluation of her qualifications and accomplishments

Education 🎓

  • Bachelor of Science in Biomedical Science and Engineering
    Konkuk University, Seoul, Republic of Korea
    Expected Graduation: August 2024
  • Bachelor of Science in Computer Science and Engineering
    Konkuk University, Seoul, Republic of Korea
    Double Major Acceptance: March 2022

Work Experience 💻

  • AI & CV Lab (June 2022 – Present)
    • Conducting projects on MRI data, including tasks for lacunar detection, Enlarged Perivascular Spaces (EPVS) detection, and microbleed detection.
    • Engaged in audio data projects, including a study on hearing loss classification and participating in the ADRESSM Challenge, where the team won first place in Alzheimer’s Disease classification tasks.

Achievements 🏆

  • 1st Place in Medical Hackathon (March 2022 – September 2022)
    • Developed a drug side effect management program in collaboration with school seniors, focusing on patient medication tracking and side effect reporting.
  • 3rd Place in SW Convergence Competition (August 2022 – November 2022)
    • Created a DNA editing program in partnership with a senior, enhancing the efficiency of DNA sequence editing compared to existing programs.
  • 2nd Place in Big Data Analysis Competition (November 2022)
    • Participated in a competition organized by CJ Enterprises, focusing on exploratory data analysis (EDA) of corporate financial statements.

Awards and Honors 🎖️

  • ICASSP 2023 Workshop Participation
    • Gained valuable experience and recognition through the team’s first-place win in the ADRESSM Challenge, leading to participation in the ICASSP 2023 workshop.

Publication Top Notes:

EEG-RegNet: Regressive Emotion Recognition in Continuous VAD Space Using EEG Signals