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Qinghao Hu (胡擎昊)

I am a Postdoctoral Associate working with Prof. Song Han at MIT. I also work closely with Prof. Ana Klimović from ETH. I obtained my Ph.D. degree from NTU in 2023, advised by Prof. Tianwei Zhang and Prof. Yonggang Wen. Before that, I received my S.M. degree from National University of Singapore and my B.Eng. degree from Zhejiang University.

I am a recipient of Google PhD Fellowship (2023) and Rising Star in ML and Systems (2024).

I am on the job market. Please reach out if you have any openings.

Email: [email protected]

Address: 38-344,50 Vassar Street, Cambridge, MA 02139

Research Interest

My research focuses on building efficient and scalable machine learning systems. Specifically, I develop full-stack infrastructure that pushes the efficiency frontier across the foundation-model lifecycle, spanning datacenter scheduling, large-scale pre-training, post-training with reinforcement learning, and model serving. My work emphasizes algorithm–system co-design for emerging workloads (long-context, multimodal, reasoning, agentic), and extends to broader system scenarios (networking, robotics).

Publications

[ASPLOS '26]	Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter Qinghao Hu, Shang Yang, Junxian Guo, Xiaozhe Yao, Yujun Lin, Yuxian Gu, Han Cai, Chuang Gan, Ana Klimovic, Song Han Paper / Code
[EuroSys '26]	Zeppelin: Balancing Variable-length Workloads in Data Parallel Large Model Training Chang Chen, Tiancheng Chen, Jiangfei Duan, Qianchao Zhu, Zerui Wang, Qinghao Hu, Peng Sun, Xiuhong Li, Chao Yang, Torsten Hoefler Paper
[NeurIPS '25]	Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search Yuxian Gu, Qinghao Hu, Shang Yang, Haocheng Xi, Junyu Chen, Song Han, Han Cai Paper / Code
[NeurIPS '25]	Scaling up Reasoning to Long Videos in VLMs Yukang Chen, Wei Huang, Baifeng Shi, Qinghao Hu, Hanrong Ye, Ligeng Zhu, Zhijian Liu, Pavlo Molchanov, Jan Kautz, Xiaojuan Qi, Sifei Liu, Hongxu Yin, Yao Lu, Song Han Paper / Code
[SOSP '25]	Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters Foteini Strati, Zhendong Zhang, George Manos, Ixeia Sánchez Périz, Qinghao Hu, Tiancheng Chen, Berk Buzcu, Song Han, Pamela Delgado, Ana Klimovic Paper / Code
[MLSys '25]	LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention Shang Yang, Junxian Guo, Haotian Tang, Qinghao Hu, Guangxuan Xiao, Jiaming Tang, Yujun Lin, Zhijian Liu, Yao Lu, Song Han Paper / Code
[ICLR '25]	LongVILA: Scaling Long-Context Visual Language Models for Long Videos Yukang Chen, Fuzhao Xue, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Ethan He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han Paper / Code
[EuroSys '25]	DeltaServe: Multi-Tenant Language Model Serving via Delta Compression Xiaozhe Yao, Qinghao Hu, Ana Klimovic Paper / Code
[NSDI '24]	Characterization of Large Language Model Development in the Datacenter Qinghao Hu, Zhisheng Ye, Zerui Wang*, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang Paper / System / Data / USENIX ;login:
[SC '24]	TorchGT: A Holistic System for Large-scale Graph Transformer Training Meng Zhang, Jie Sun, Qinghao Hu, Peng Sun, Zeke Wang, Yonggang Wen, Tianwei Zhang Paper / Code / Artifact Badges: Available Functional Reproduced
[ICDE '24]	Sylvie: 3D-adaptive and Universal System for Large-scale Graph Neural Network Training Meng Zhang, Qinghao Hu, Cheng Wan, Haozhao Wang, Peng Sun, Yonggang Wen, Tianwei Zhang Paper / Code
[CSUR '24]	Deep Learning Workload Scheduling in GPU Datacenters: A Survey Zhisheng Ye, Wei Gao, Qinghao Hu*, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen Paper / Awesome List / ACM Computing Surveys
[OSDI '23]	Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters Qinghao Hu, Zhisheng Ye, Meng Zhang, Qiaoling Chen, Peng Sun, Yonggang Wen, Tianwei Zhang Paper / Code / Artifact Badges: Available Functional Reproduced
[ASPLOS '23]	Lucid: A Non-Intrusive, Scalable and Interpretable Scheduler for Deep Learning Training Jobs Qinghao Hu, Meng Zhang, Peng Sun, Yonggang Wen, Tianwei Zhang Paper / Code / Artifact Badges: Available Functional Reproduced Distinguished Paper Award
[ATC '22]	Primo: Practical Learning-Augmented Systems with Interpretable Models Qinghao Hu, Harsha Nori, Peng Sun, Yonggang Wen, Tianwei Zhang Paper / Code / Artifact Badges: Available Functional Reproduced
[SC '21]	Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang Paper / Code / Data / Artifact Badges: Available Functional Reproduced

Preprint

[arXiv '24]	LoongTrain: Efficient Training of Long-Sequence LLMs with Head-Context Parallelism Diandian Gu, Peng Sun, Qinghao Hu, Ting Huang, Xun Chen, Yingtong Xiong, Guoteng Wang, Qiaoling Chen, Shangchun Zhao, Jiarui Fang, Yonggang Wen, Tianwei Zhang, Xin Jin, Xuanzhe Liu Paper / Submitted to a Conference
[arXiv '24]	InternEvo: Efficient Long-Sequence Large Language Model Training via Hybrid Parallelism and Redundant Sharding Qiaoling Chen, Diandian Gu, Guoteng Wang, Xun Chen, Yingtong Xiong, Ting Huang, Qinghao Hu, Xin Jin, Yonggang Wen, Tianwei Zhang, Peng Sun Liu Paper / Submitted to a Conference
[arXiv '23]	AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning Qiaoling Chen, Qinghao Hu, Zhisheng Ye, Guoteng Wang, Peng Sun, Yonggang Wen, Tianwei Zhang Paper / Submitted to a Conference

Professional Services

Workshop Organizer

[CVPR '25]	Workshop: Efficient Large Vision Models Workshop (ELVM)
[MICRO '24]	Workshop: Hardware and Architectural Support for Security and Privacy (HASP)

Conference Reviewer

[ICLR '26]	Reviewer
[CVPR '26]	Reviewer
[ICLR '25]	Reviewer
[EuroSys '23-'25]	Shadow Committee Member
[OSDI '22]	AE Committee Member
[ATC '22]	AE Committee Member
[EuroSys '22]	AE Committee Member
[SOSP '21]	AE Committee Member

Journal Reviewer

[TPDS]	IEEE Transactions on Parallel and Distributed Systems
[TACO]	ACM Transactions on Architecture and Code Optimization
[TOCS]	ACM Transactions on Computer Systems
[CSUR]	ACM Computing Surveys

Awards

Rising Star in ML and Systems	2024
Best Ph.D. Thesis Award	2024
National Scholarship for Outstanding Graduates	2024
Google PhD Fellowship	2023
Distinguished Paper Award of ASPLOS	2023
Best Paper Award of WAIC	2023
Best Undergraduate Thesis Award	2018
Outstanding Graduates of Zhejiang University	2018