I am Sunil Regmi, an IT and AI professional with a Master’s in Information Technology, currently working as a Lecturer in the Department of Artificial Intelligence at Kathmandu University. My expertise lies in Natural Language Processing, Large Language Models, Computer Vision, Machine Learning, and Deep Learning, with a strong focus on developing AI-driven solutions for low-resource languages. My research includes Nepali speech recognition, Named Entity Recognition (NER), and Part-of-Speech (POS) tagging, with publications in international conferences such as ICON and LREC-COLING. I also work extensively with IoT and edge computing, designing sensor-based solutions for environmental monitoring, including air quality and heatwave detection systems. Alongside my academic and research career, I have industry experience as an AI researcher, IoT consultant, and IT project manager, collaborating with organizations like The Asia Foundation and Green Decision Labs. Additionally, I am passionate about music composition and perform as part of a band, blending my technical and creative pursuits to explore the intersection of technology and art.
I am deeply interested in Natural Language Processing (NLP) and its applications in low-resource languages, particularly focusing on Large Language Models (LLMs), Speech Recognition, Named Entity Recognition (NER), and Part-of-Speech (POS) tagging for the Nepali language. My research also extends to Machine Learning (ML) and Deep Learning (DL) techniques for language modeling, text generation, and multimodal AI.
In addition, I explore the intersection of Artificial Intelligence (AI) and Internet of Things (IoT), working on edge computing solutions for environmental monitoring, including air quality assessment, heatwave detection, and early warning systems for disaster resilience. I am also passionate about computer vision, geospatial analysis, and remote sensing, integrating AI-driven solutions for urban resilience and environmental sustainability.
For my future research, I am highly interested in Brain-Computer Interaction (BCI) and neural signal processing, particularly in decoding brain signals, recreating dreams, and understanding cognitive processes using AI. My goal is to explore how EEG-based AI models and deep learning techniques can be leveraged to interpret brain activity, enhance human-computer interaction, and push the boundaries of neurotechnology for applications in mental health, assistive technologies, and neuroscience research.