MLSys 2026
Professor at UW and VP of AI Systems Software at NVIDIA. His work spans computer architecture, programming languages, machine learning systems, and computing/biology.
Adjunct Professor of Computer Science at Stanford. Her background includes systems, networking, and machine learning, with prior work recognized by MLSys outstanding paper awards.
Assistant Professor of Computer Science at Carnegie Mellon University. His research focuses on efficient, scalable systems for machine learning and emerging AI workloads.
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.
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.
Vartika Singh leads strategic AI initiatives at NVIDIA, working with deep learning frameworks, compiler ecosystems, and partners to optimize AI software on NVIDIA hardware.
Martin Maas is a Senior Staff Research Scientist at Google DeepMind. His research focuses on machine learning for systems, managed runtimes, operating systems, and computer architecture.
Mangpo Phothilimthana is a Technical Member of Staff at OpenAI. Her work focuses on hardware-software co-design and efficient software systems for emerging AI hardware.
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.
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.
Tian Li is an Assistant Professor of Computer Science and Data Science at the University of Chicago. Her research focuses on distributed optimization, federated learning, and trustworthy machine learning.
Stephanie Wang is an Assistant Professor of Computer Science at the University of Washington. Her research focuses on distributed systems and abstractions for high-performance, fault-tolerant systems.
Banghua Zhu is an Assistant Professor at the University of Washington and co-founder of RadixArk. His work focuses on foundation models, machine learning systems, and efficient AI infrastructure.
Xupeng Miao is an Assistant Professor in the School of Computer Science at Peking University. His research focuses on machine learning systems, data management, and distributed computing.
Juncheng Yang is an Assistant Professor of Computer Science at Harvard SEAS. His research focuses on efficient, reliable, and sustainable large-scale data storage and machine learning systems.
Jackson Zhu is affiliated with Lumen Future and supports MLSys conference operations and workflow organization. His broader work spans technology, investing, and community-building around emerging technical fields.
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
