I am a researcher in Computer Science at the
Jeonbuk National University, affiliated with the
Guru technology research group in Nepal.
My current project consists of applying deep learning methods in the field of animal sound behavior analysis, music information retrieval,
music video emotion analysis, music source separation, and object detection, with the aim of devising quantitative measures in affective computing and sound localization.
My research interest includes multi-level classification, unsupervised learning, self-supervised learning, meta-learning and incremental learning.
I received Ph.D. in Computer Engineering from Jeonbuk National University, South Korea. I worked on animal sound localization and classification, affective computing in music video and music source separation.
I proposed five datasets in this domain to train the deep neural network and made public to support new researchers. My thesis work includes music video affective computing with supervised and unsupervised technology.
I proposed novel datasets, convolution techniques, and unimodal and multimodal architectures using music, video, and facial expressions from the music video.
Prior to embarking on the insanity of the doctoral studies, I received an ME in Computer Engineering from the
Pokhara University, Nepal.
In my master thesis work, I worked on data communication and information processing using multiple antenna technology.
A few years before, I received a BE in Computer Engineering from the
Pokhara University, with a thesis investigating home security system using microcontroller and sensor technology.
