General Chair
Matei Zaharia
UC Berkeley and Databricks
Matei Zaharia is an Associate Professor of Computer Science at Stanford (moving to UC Berkeley later this year) and Chief Technologist and Cofounder of Databricks. His research has spanned distributed systems, databases, security and machine learning, with the most recent focus on systems for machine learning, natural language processing, and information retrieval. Matei started and contributed to multiple widely used open source projects including Apache Spark (his PhD project at UC Berkeley), MLflow, Dolly, Delta Lake, and ColBERT. His research was recognized through the 2014 ACM Doctoral Dissertation Award, an NSF CAREER Award, and the US Presidential Early Career Award for Scientists and Engineers (PECASE).
Matei Zaharia is an Associate Professor of Computer Science at Stanford (moving to UC Berkeley later this year) and Chief Technologist and Cofounder of Databricks. His research has spanned distributed systems, databases, security and machine learning, with the most recent focus on systems for machine learning, natural language processing, and information retrieval. Matei started and contributed to multiple widely used open source projects including Apache Spark (his PhD project at UC Berkeley), MLflow, Dolly, Delta Lake, and ColBERT. His research was recognized through the 2014 ACM Doctoral Dissertation Award, an NSF CAREER Award, and the US Presidential Early Career Award for Scientists and Engineers (PECASE).
Program Chair
Gauri Joshi
Carnegie Mellon University
Program Chair
Yingyan (Celine) Lin
Georgia Tech
Artifact Evaluation Chair
Xupeng Miao
Purdue
Artifact Evaluation Chair
Minjia Zhang
UIUC
Minjia Zhang is an Assistant Professor at the University of Illinois Urbana-Champaign. His research focuses on machine learning systems, large-scale AI infrastructure, and efficient distributed training and inference.
Minjia Zhang is an Assistant Professor at the University of Illinois Urbana-Champaign. His research focuses on machine learning systems, large-scale AI infrastructure, and efficient distributed training and inference.
Workflow Chair
Zhenyu (Sherry) Xue
MLSys Staff
Panel and Young Professional Activities Chair
Dan Fu
UCSD
Dan Fu is an Assistant Professor at UC San Diego and VP of Kernels at Together AI. His work focuses on making machine learning models faster and more efficient through efficient architectures, algorithms, and GPU kernels.
Dan Fu is an Assistant Professor at UC San Diego and VP of Kernels at Together AI. His work focuses on making machine learning models faster and more efficient through efficient architectures, algorithms, and GPU kernels.
Panel and Young Professional Activities Chair
Hui Guan
Assistant Professor
University of Massachusetts, Amherst; Amazon
Hui Guan is an Assistant Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst, the flagship campus of the UMass system. Her research interest resides at the intersection of programming systems and machine learning, with a focus on improving the speed, scalability, and reliability of machine learning through innovations in algorithms and programming systems (e.g., compilers and runtime). Hui is currently working at Amazon on AIOps.
Hui Guan is an Assistant Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst, the flagship campus of the UMass system. Her research interest resides at the intersection of programming systems and machine learning, with a focus on improving the speed, scalability, and reliability of machine learning through innovations in algorithms and programming systems (e.g., compilers and runtime). Hui is currently working at Amazon on AIOps.
Sponsor Chair
Wenming Ye
Model AI Corp
Wenming Ye works on product and AI systems at Google, with a focus on GenAI and JAX frameworks. He has been an active organizer and sponsor chair for major machine learning and systems conferences.
Wenming Ye works on product and AI systems at Google, with a focus on GenAI and JAX frameworks. He has been an active organizer and sponsor chair for major machine learning and systems conferences.
Publications Chair
Tian Li
U Chicago
Publications Chair
Ang Li
University of Maryland, College Park
Travel Grant Chair
Zhijian Liu
UCSD
Travel Grant Chair
Hanrui Wang
UCLA
Assistant Professor in Computer Science at UCLA. His research focuses on efficient AI computing, hardware-architecture-algorithm co-design, quantum systems, and generative AI systems.
Assistant Professor in Computer Science at UCLA. His research focuses on efficient AI computing, hardware-architecture-algorithm co-design, quantum systems, and generative AI systems.
Logistics Chair
Mary Ellen Perry
Admin.
MLSys Staff
Mary Ellen Perry is a longtime academic conference organizer and administrator who has helped manage major machine learning conferences including NeurIPS and ICML. She served as Executive Director of the NeurIPS Foundation while affiliated with the Salk Institute, and has also been listed in ICML conference operations and contact roles. Her work has supported the logistics, administration, and execution of some of the world’s leading machine learning research conferences
Mary Ellen Perry is a longtime academic conference organizer and administrator who has helped manage major machine learning conferences including NeurIPS and ICML. She served as Executive Director of the NeurIPS Foundation while affiliated with the Salk Institute, and has also been listed in ICML conference operations and contact roles. Her work has supported the logistics, administration, and execution of some of the world’s leading machine learning research conferences
Logistics Chair
Susan Perry
MLSys Staff
Logistics Chair
Max Wiesner
MLSys Staff
