Overview:
The MADUV Challenge 2025 was part of INTERSPEECH 2025, inviting researchers worldwide to develop models that classify mice as either wild-type or ASD models based on high-frequency ultrasound vocalizations. Advanced signal processing techniques were used to handle complex audio data in this globally recognized event.
My Contribution:
- Swin Transformer Implementation: Explored multiple Swin Transformer variants by reviewing recent research papers, implementing the approaches, and conducting thorough experiments.
- Mel-Spectrogram Conversion Pipeline: Developed an end-to-end pipeline to convert raw ultrasound vocalizations into mel-spectrograms for robust feature extraction.
- Achievement: Secured 3rd Place in the challenge.
For more details, visit the MADUV Challenge website or see the MADUV Challenge 2025 documentation.
Overview:
Participated in a Statistics Competition organized by the Department of Statistics at Konkuk University in November 2024.
Achievement:
- Awarded 3rd Place for outstanding performance in statistical analysis and problem-solving.
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Languages:
- C, C++
- JavaScript (Node.js, React)
- Python (Django)
- Java, R
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Databases:
- MongoDB, MySQL
- Data Structures & Algorithms (Baekjoon)
- React.JS & Node.JS – In-depth study of modern JavaScript frameworks
- Start Date: March 28, 2024
- Resources:
- Deep Learning from Scratch
- CS231n