I am a Machine Learning Research Engineer at the Bosch Center of Artificial Intelligence, USA. I lead research and development teams that provide sustainable Machine Learning (ML) and Deep Learning (DL) solutions, across Bosch's various business (automotive, healthcare, manufacturing, etc.).
My favorite perk of working in the field of Data Science, is the opportunity to work on a diverse set of applications. At Bosch, I have had the privilege of working on applications that have spanned the whole value-stream of a product. Starting all the way from developing ‘automated optical inspection’ models using deep learning to help improve the manufacturing efficiency of an individual component (for e.g., circuit boards), all the way to developing ML models that interact directly with the end-user (such as 'driver assistance functionality’ that aids vehicle safety).
Incorporating and extending the latest academic breakthroughs in ML and DL to real-world applications are often non-trivial. The challenges that arise when incorporating the latest breakthroughs in ML to a sustainable real-world deployment (such as model monitoring, concept drift, imbalanced labels or the dearth of labels) have driven my recent research efforts in the topics of online learning, concept drift detection and adaptation.
I received my Ph.D. in Computer Science (specializing in Machine Learning) from Michigan State University. Prior to that, I received my M.S. in Computer Science (specializing in Augmented/Virtual Reality) from Michigan State University.
Contact me via LinkedIn
