Rupesh Sapkota
Student, Computer Science, Universität Paderborn
Paderborn, Deutschland
Über mich
Passionate Machine Learning Engineer, aspiring to excel in the industry by focusing on real-world applications of AI. With a blend of academic knowledge and professional expertise, I bring a proven track record in developing end-to-end machine learning systems and innovative solutions with a zeal to learn and develop further. • 2 years of Professional Working Experience. • Contribution to open-source projects (Python-Scalpel) and development of Machine Learning and Explainable AI framework. • Research Interests include Explainable AI, Fairness in AI, and Secure Systems Engineering.
Werdegang
Berufserfahrung von Rupesh Sapkota
8 Monate, Juni 2023 - Jan. 2024
Student Research Assistant
University of Paderborn
Developed and integrated Fully Qualified Name Resolution API using call-graph analysis in the Python-Scalpel framework Worked on the implementation of context sensitivity for code analysis in PyCG, a Python static analysis tool for call graph generation Enhanced code quality and documentation of multiple projects; contributed to open-source libraries (Python-Scalpel, TypeEvalPy) Performed prompt engineering and fine-tuning of LLMs to assess static analysis capabilities of state-of-the-art language models
Advanced algorithm development and optimization, enhancing data analysis and AI model performance along with comprehensive code documentation. Worked on and developed end-to-end processes for complex data analysis using large datasets while significantly improving existing code infrastructures. Practical experience also includes developing recommender systems, time-series forecasting, and building predictive analysis models.
2 Monate, Juli 2018 - Aug. 2018
Developer Intern
EveryCrave Webtech
Developed a responsive website from scratch using Python and Django. Learned and used various web-development tools such as HTML, CSS, JavaScript, SQL and GoogleMapsAPI.
Ausbildung von Rupesh Sapkota
Bis heute 3 Jahre und 3 Monate, seit Apr. 2021
Computer Science
Universität Paderborn
Developed end-to-end Knowledge Graph-based question answering system using Deep Learning and Natural Language Processing techniques with results comparable to state-of-the-art systems. Presented academic seminars on Reinforcement Learning and Secure Systems Engineering. Master’s thesis on “Evaluation of Logical and Subgraph Explanations of Node Classifiers on Knowledge Graphs” with Graph-based Machine Learning.
Sprachen
Englisch
Fließend
Deutsch
Gut