Summary
Zeinab Akhavan is a Senior Data Analyst and PhD candidate in Computer Science with 8–12 years of hands-on experience spanning algorithms, databases, computer vision, HCI, networking, and machine learning. She combines academic rigor from the University of New Mexico with practical industry impact—recently applying reinforcement learning for edge resource allocation and building real-time seismic and ICO-detection data pipelines using Spark, Kafka, Dash, and Python. Based in Eugene, Oregon, Zeinab has moved seamlessly between research, teaching, and production analytics roles, now bringing that breadth to Molina Healthcare. Curious and resilient, she specializes in applying ML/deep learning to IoT problems like smart buildings and cities, aiming to translate novel research into deployable systems for industry or academia.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of New Mexico School of Engineering
Bachelor's degree Information Technology, Bachelor's degree Information Technology at University of Tehran
English, Persian