Tianqi Chen, an assistant professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University, has received a Faculty Early Career Development Program (CAREER) award from the National Science Foundation (NSF).The NSF CAREER award is the foundation's most prestigious honor for early career faculty members and supports research and education activities led by junior faculty considered likely to become academic leaders in their fields.SCS Professor TQ Chen received an NSF CAREER Award for his work in machine learning systems.Chen's research focuses on machine learning systems, with an emphasis on the intersection of AI models, systems and hardware. His work centers on building scalable, open-source machine learning infrastructure and deployment systems. He has contributed to several widely adopted machine learning platforms and tools, including XGBoost, Apache TVM, Apache MXNet and MLC-LLM.At CMU, Chen leads the Catalyst Group, which studies machine learning systems and AI infrastructure across the software and hardware stack. His research explores how learning systems can become more efficient, accessible and deployable across a wide range of computing environments.For more information, visit the NSF CAREER Award website.
Chen Receives NSF CAREER Award for Research in Machine Learning Systems
Tianqi Chen, an assistant professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University, has received a Faculty Early Career Development Program (CAREER) award from the National Science Foundation (NSF).The NSF CAREER award is the foundation's most prestigious honor for early career faculty members and supports research and education activities led by junior faculty considered likely to become academic leaders in their fields.SCS Professor TQ Chen received an NSF CAREER Award for his work in machine learning systems.Chen's research focuses on machine learning systems, with an emphasis on the intersection of AI models, systems and hardware. His work centers on building scalable, open-source machine learning infrastructure and deployment systems. He has contributed to several widely adopted machine learning platforms and tools, including XGBoost, Apache TVM, Apache MXNet and MLC-LLM.At CMU, Chen leads the Catalyst Group, which studies machine learning systems and AI infrastructure across the software and hardware stack. His research explores how learning systems can become more efficient, accessible and deployable across a wide range of computing environments.For more information, visit the NSF CAREER Award website.
