As an MLOps developer, simulation specialist, and research engineer with over 6 years of experience, I specialize in developing innovative data-driven solutions. My tenure as a postdoc at NC Inc. was marked by leveraging machine learning and synthetic data from finite element simulations for thermal stress analysis in pipe bends, directly addressing industry challenges. In my current role at Arcurve Inc., I utilize cloud services (e.g., Azure and AWS) to develop/maintain end-to-end machine-learning pipelines. Additionally, my personal project 'DocsGPT,' a RAG-based querying app using LangChain and OpenAI's API, demonstrates my proficiency in implementing solutions using generative AI. Let's connect on LinkedIn.
farhad-davaripour / cfrp_reinforced_hdd_overbend Goto Github PK
View Code? Open in Web Editor NEWThis project employs machine learning and synthetic dataset to predict the peak equivalent stress imposed on a CFRP wrapped HDD overbend
Home Page: https://share.streamlit.io/farhad-davaripour/cfrp_reinforced_hdd_overbend/main/my_app/Homepage.py
License: GNU General Public License v3.0