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Lecture Series In AI w/ Alibaba
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| With Jingren Zhou (CTO, Alibaba Cloud). |
| Columbia, 530 W 120th St, Davis Auditorium, Rm 412 |
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Nov 21 (Fri) , 2025 @ 10:30 AM
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FREE |
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| DETAILS |
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Schedule:
10:30-11:00am Check-in
11:00-12:00pm Lecture
Advance registration required for both Columbia non-affiliates & Columbia affiliates.
About the Speaker
Jingren Zhou is the Chief Technology Officer at Alibaba Cloud, where he drives technology innovation & product development across a wide range of cloud computing services. He also leads the development of AI foundation models, such as Qwen & Wan models, & their applications in diverse business applications within Alibaba Cloud. Prior to this role, he played a key role in building Alibaba's cloud-scale distributed data analytics platform & developing advanced techniques for personalized search, product recommendation, & advertising on Alibaba's e-commerce platform. Before joining Alibaba, he was a veteran at Microsoft, focusing on big data & database research & development. His research interests include cloud computing, distributed systems, databases, & large-scale machine learning. He has served as PC co-chair & core committee member for many academic conferences & technical forums. He received his PhD in Computer Science from Columbia University. He is a Fellow of ACM & IEEE.
About the Lecture
"Building Foundation Models at Scale: System Experiences & Challenges"
The rapid evolution of AI has led to the emergence of massive & complex foundation models that require enormous computational resources, making efficient training & inference systems essential. Training such models requires large-scale distributed computation, effective overlap of computation & communication, sophisticated parallelization strategies, & robust fault-tolerant mechanisms. Inference systems, on the other hand, must support diverse workloads with varying service-level agreements (SLAs), rapidly integrate engineering optimizations, & carefully balance trade-offs among throughput, latency, cost, & availability, particularly in distributed environments. In this talk, I will discuss the major systems challenges in building large-scale foundation models, focusing on our experiences developing Qwen (large language models) & Wan (video generative models). I will also present ongoing research & system designs that enhance the efficiency of training & inference at scale, enabling more effective management of complex AI workloads in cloud environments.
Campus Access
In accordance with the University's current visitor guidelines, all non-Columbia guests will receive a QR code within a few hours of the event date. The code will be sent to you via email from CU Guest Access & must be presented for campus entry, along with a government-issued ID.
Accessibility
Columbia University makes every effort to accommodate individuals with disabilities. If you require disability accommodations to attend an event at Columbia University, please contact the Office of Disability Services at 212.854.2388 or access@columbia.edu.
Photography/Videography
Columbia Engineering reserves the right to capture & use images (including video, photo, audio) of student participants at this event in its current or future marketing materials. These materials include but are not limited to: social media, digital and/or print posters, email & web-based materials. By attending & participating in this event, you are consenting to having your image captured for these purposes. If you have concerns about your likeness being used, please reach out to engineeringcommunications@columbia.edu & we will accommodate your request.
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