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I am Tzu-Yun Hung, a dedicated and passionate music composer and researcher with a strong background in sound and music computing. I have a Master's degree from Queen Mary University of London and previous advanced experience from National Taiwan Normal University and UC Berkeley. I am highly skilled in electronic music composition, audio programming, and music informatics, and have contributed to academic research and practical projects that focus on expressive musical performance and piece classification. I enjoy blending technology with music, creating innovative compositions that incorporate electronic and acoustic elements. With hands-on expertise in Python, music production software, and data visualization, I focus on both artistic creation and scientific exploration, aiming to push the boundaries of music technology and expression.…I am Tzu-Yun Hung, a dedicated and passionate music composer and researcher with a strong background in sound and music computing. I have a Master's degree from Queen Mary University of London and previous advanced experience from National Taiwan Normal University and UC Berkeley. I am highly skilled in electronic music composition, audio programming, and music informatics, and have contributed to academic research and practical projects that focus on expressive musical performance and piece classification. I enjoy blending technology with music, creating innovative compositions that incorporate electronic and acoustic elements. With hands-on expertise in Python, music production software, and data visualization, I focus on both artistic creation and scientific exploration, aiming to push the boundaries of music technology and expression.

Tzu-Yun Hung

Music Composer, Composer, Music Producer, +1

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I am Tzu-Yun Hung, a dedicated and passionate music composer and researcher with a strong background in sound and music computing. I have a Master's degree from Queen Mary University of London and previous advanced experience from National Taiwan Normal University and UC Berkeley. I am highly skilled in electronic music composition, audio programming, and music informatics, and have contributed to academic research and practical projects that focus on expressive musical performance and piece classification. I enjoy blending technology with music, creating innovative compositions that incorporate electronic and acoustic elements. With hands-on expertise in Python, music production software, and data visualization, I focus on both artistic creation and scientific exploration, aiming to push the boundaries of music technology and expression.…I am Tzu-Yun Hung, a dedicated and passionate music composer and researcher with a strong background in sound and music computing. I have a Master's degree from Queen Mary University of London and previous advanced experience from National Taiwan Normal University and UC Berkeley. I am highly skilled in electronic music composition, audio programming, and music informatics, and have contributed to academic research and practical projects that focus on expressive musical performance and piece classification. I enjoy blending technology with music, creating innovative compositions that incorporate electronic and acoustic elements. With hands-on expertise in Python, music production software, and data visualization, I focus on both artistic creation and scientific exploration, aiming to push the boundaries of music technology and expression.

Available to hire

I am Tzu-Yun Hung, a dedicated and passionate music composer and researcher with a strong background in sound and music computing. I have a Master’s degree from Queen Mary University of London and previous advanced experience from National Taiwan Normal University and UC Berkeley. I am highly skilled in electronic music composition, audio programming, and music informatics, and have contributed to academic research and practical projects that focus on expressive musical performance and piece classification.

I enjoy blending technology with music, creating innovative compositions that incorporate electronic and acoustic elements. With hands-on expertise in Python, music production software, and data visualization, I focus on both artistic creation and scientific exploration, aiming to push the boundaries of music technology and expression.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

Sound model Intern at Nemisindo

January 1, 2025 - Present

Improved the sound quality of the Footstep models. Performed data visualization with libraries such as Librosa, Essentia, and sonic visualizer, and feature extraction techniques.

Research Assistant at Institute of Information Science, Academia Sinica (Music and Culture Technology Lab)

August 31, 2024 - August 6, 2025

Developed a notation database program (NTSO) to store and organize musical form, harmony, and instrument performance data from orchestra scores. Conducted research on orchestra texture classification, including data cleaning and modeling. Collaborated with a team of researchers to brainstorm ideas and develop research plans.

Research student at Institute of Information Science, Academia Sinica

December 31, 2023 - August 6, 2025

Conducted projects on generative music using expressive musical terms. Developed a Python-based prototype for analyzing performance dynamics. Collected and annotated Beethoven's Complete Piano Sonata Movement I motifs. Implemented data visualization frameworks using Pandas and Matplotlib to compare 11 musical expressive term features.

Research student at Department of Music, National Taiwan Normal University

December 31, 2023 - August 6, 2025

Focused on computer music composition and nurturing collaboration abilities with other realms of artists. Strengthened electronic and contemporary music skills through research and composition.

Music Private Instructor at Freelancer, Taiwan

December 31, 2023 - August 6, 2025

Taught over 20 students in piano, music theory, dictation, and ear training; placed students in regional competitions. Developed adapted teaching methods tailored to each student's comprehension level, using alternative explanations or practical demonstrations to ensure consistent understanding.