Summary
Artur Gasparyan is a Research Engineer at KTH with nine years of experience applying generative models and embodied AI to real-world problems. He has bridged academic and industrial work—from extending NeRFs with diffusion models for autonomous driving during his master’s thesis to building production LLM-powered search and RAG pipelines at Ericsson serving thousands of users. His recent research blends multimodal perception (including novel olfactory integration) with contrastive learning and diffusion-based visual decoding, reflecting a curiosity for sensor-rich embodied systems. Comfortable scaling experiments on multi-GPU clusters and deploying containerized ML services, he focuses on solutions that are both technically innovative and practically useful. Open to collaborations across research, open-source, and product projects, he brings a thoughtful, engineering-first approach to pushing the boundaries of machine learning.
9 years of coding experience
2 years of employment as a software developer
Gymnasieexamen Teknikvetenskap, Gymnasieexamen Teknikvetenskap at Tullängsgymnasiet
Master of Engineering - MEng Computer Science and Engineering, Master of Engineering - MEng Computer Science and Engineering at Chalmers University of Technology
English, Swedish, Russian