Peter Baile Chen 陳百樂

  • Scholarship in 2022 at Massachusetts Institute of Technology

About Peter Baile Chen’s work

Peter Baile Chen’s research in computer science is focused on data systems and machine learning. He aspires to build a unifying data platform capable of supporting integration between data and machine learning (ML) in a scalable and robust environment with easy monitoring and debugging.

Big data stimulates the development of complex and powerful ML models that can leverage the abundance of training data. The aggregation of multiple ML models, where the output of one model becomes the input to the next, forms even more powerful ML pipelines. These pipelines are frequently applied to database systems to facilitate better query optimisation and planning, constituting an area in computer science called ML for systems, which Chen hopes to explore further.

The complexity of these models and pipelines introduces problems such as prolonged training time, tedious and repetitive workflow, and inefficiencies upon retraining. In order to tackle these problems, systems are built by utilising techniques from data management, distributed systems, databases, and related fields, constituting the area called systems for ML. Chen is using techniques from both areas to create a platform that supports highly efficient and sophisticated data analytics.


Peter Baile Chen is a computer science PhD student at Massachusetts Institute of Technology. He graduated from the University of Pennsylvania with a BSE. He is part of the UPenn CIS Undergraduate TA Hall of Fame, and won the Hult Prize@Penn and the Penn Wharton Innovation Fund Implementation Award.