I'm Kamal Shrestha,
I am currently working on impactful projects centered around Large Language Models (LLM) and harnessing its powerful generative text capabilities.
With a postgraduate degree in Computer Science and Engineering from the Indian Institute of Technology Hyderabad and an undergraduate degree in Computer Engineering from Kathmandu University, I bring over three and a half years of work experience in the AI domain.
I am as pure as a CS student can be.
Having served as a Machine Learning Engineer and Curriculum Engineer in the past, I've cultivated expertise in both applied and theoretical ML, DL, and NLP, not just from a student but also from an instructor's point of view. From data mining and cleaning to model building and deployment, my journey has focused on delivering impactful and tangible results that drive critical business decisions. Currently, my emphasis is on Natural Language Processing, specifically integrating the power of LLMs for optimization and efficiency.
For more insights into my professional and academiv journey, visit my website : Kamal Shrestha - Professional Updates
I'm enthusiastic about the potential in NLP and eager to connect with you.
Download my CV : Kamal Shrestha - CV
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Possess a comprehensive theoretical and practical foundation in natural language processing, machine learn- ing and deep learning combined with hands-on experience in experimental design methodologies adn applied research for business applications.
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Proficient in executing learning pipeline encompassing various stages such as data extraction, analysis, cleaning, pre-processing, modelling, training, and evaluating, and deployment primarily utilizing PyTorch, Langchain, Streamlit, Scikit-learn, Transformers and other necessary libraries to achieve optimal results.
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Demonstrate excellent teamwork, communication, and writing skills honed through multiple years of industry experience, academic qualification, research publications, poster presentations, and teaching engagements.
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Professional Career/Research Interests: Intersection of applied NLP, DL, and Classical ML Techniques