Abhijeet Ainapure

About Abhijeet Ainapure

As a Data Scientist at Predictronics Corp, I apply machine learning and deep learning techniques to industrial data for predictive maintenance. I work on projects involving signal processing, feature engineering, anomaly detection, fault diagnosis, and remaining useful life estimation. I also participate in conferences, data challenges, and AI forums to share my research and learn from peers. Before joining Predictronics, I was a Graduate Research Assistant at the NSF Industry/University Cooperative Research Center for Intelligent Maintenance Systems (IMS) at the University of Cincinnati, where I earned my MS in Mechanical Engineering. At IMS, I conducted state-of-the-art research on domain adaptation and conditional anomaly detection for multi-component systems in evolving environments. I collaborated with various industry partners such as Mitsubishi Electric, Procter & Gamble, Foxconn Group, Mazak North America, Power Solutions International etc, and ranked fourth in the Aramis Innovation Data Challenge for Prognostics and Health Management (PHM). I have published multiple papers and patents in the field of machine learning and PHM.

Experience

1. Data Scientist

   Predictronics Corp

   Jun 2021 — Present · Cincinnati, OH, US

   Developed data-driven health models utilizing an end-to-end predictive analytics and Industrial AI (Artificial Intelligence) software platform, resulting in a 20% increase in production efficiency for our industrial customers. • Collaborated with cross-functional teams to make functional, architectural, and user interface improvements to the platform based on industrial needs. • Engaged in architecting, configuring, & deploying scalable solutions to industrial customers in a timely & …