Publications
Genie Team.
Genie 3: A new frontier for world models.
Veo Team. Veo: Our state-of-the-art video
generation model.
Gemini Team. "Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality,
Long Context, and Next Generation Agentic Capabilities." arXiv preprint arXiv:2507.06261 (2025).
Gemma Team. "Gemma 2: Improving open language models at a practical size." arXiv preprint arXiv:2408.00118 (2024).
Gemini Team. "Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context." arXiv preprint arXiv:2403.05530 (2024).
Gemma Team. "Gemma 2: Improving open language models at a practical size." arXiv preprint arXiv:2408.00118 (2024).
Gemini Team. "Gemini: A family of highly capable multimodal models, 2024." arXiv preprint arXiv:2312.11805 10 (2024).
Schiemer, Martin, Clemens JS Schaefer, Jayden Parker Vap, Mark James Horeni, Yu Emma Wang, Juan Ye,
and Siddharth Joshi. "Hadamard domain training with integers for class incremental quantized
learning." arXiv preprint arXiv:2310.03675 (2023).
Clemens JS Schaefer, Navid Lambert-Shirzad, Xiaofan Zhang, Chiachen Chou, Tom Jablin, Jian Li,
Elfie Guo, Caitlin Stanton, Siddharth Joshi, and Yu Emma Wang. "Augmenting hessians with inter-layer
dependencies for mixed-precision post-training quantization." arXiv preprint arXiv:2306.04879 (2023).
Clemens JS Schaefer, Elfie Guo, Caitlin Stanton, Xiaofan Zhang, Tom Jablin, Navid Lambert-Shirzad,
Jian Li, Chiachen Chou, Siddharth Joshi, and Yu Emma Wang. "Mixed precision post training
quantization of neural networks with sensitivity guided search." arXiv preprint arXiv:2302.01382 (2023).
Zhang, Xiaofan, Zongwei Zhou, Deming Chen, and Yu Emma Wang. "AutoDistill: An end-to-end framework
to explore and distill hardware-efficient language models." arXiv preprint arXiv:2201.08539 (2022).
Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi
Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P Bosma, Zongwei Zhou, Tao Wang,
Yu Emma Wang et al. "Glam: Efficient scaling of language models with mixture-of-experts." In
International conference on machine learning, pp. 5547-5569. PMLR, 2022.
Phitchaya Mangpo Phothilimthana, Amit Sabne, Nikhil Sarda, Karthik Srinivasa Murthy, Yanqi Zhou,
Christof Angermueller, Mike Burrows, Sudip Roy, Ketan Mandke, Rezsa Farahani, Yu Emma Wang et
al. "A flexible approach to autotuning multi-pass machine learning compilers." In 2021 30th International Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 1-16. IEEE, 2021.
Sameer Kumar, Yu Emma Wang, Cliff Young, James Bradbury, Anselm Levskaya, Blake Hechtman,
Dehao Chen, HyoukJoong Lee, Mehmet Deveci, Naveen Kumar, Pankaj Kanwar, Shibo Wang,
Skye Wanderman-Milne, Steve Lacy, Tao Wang, Tayo Oguntebi, Yazhou Zu, Yuanzhong Xu,
Andy Swing, "Exploring the limits of Concurrency in ML Training on Google TPUs." MLSys (2021).
Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim Hazelwood, David Brooks,
"Exploiting Parallelism Opportunities with Deep Learning Frameworks."
arXiv preprint arXiv:1908.04705 (2019).
Yu Emma Wang, Gu-Yeon Wei, David Brooks, "A Systematic Methodology
for Analysis of Deep Learning Hardware and Software Platforms." MLSys (2020).
(The arXiv version of the above paper) Yu Emma Wang, Gu-Yeon Wei, David
Brooks, "Benchmarking TPU, GPU and CPU for Deep Learning." arXiv
preprint arXiv:1907.10701 (2019).
Yu Emma Wang, Yuhao Zhu, Glenn G. Ko, Brandon Reagen, Gu-Yeon Wei, and
David Brooks. "Demystifying Bayesian Inference Workloads." IEEE International
Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 177-189. IEEE, 2019.
Yu Emma Wang, Victor Lee, Gu-Yeon Wei, and David Brooks. "Predicting New
Workload or CPU Performance by Analyzing Public Datasets." ACM Transactions on
Architecture and Code Optimization (TACO). vol. 15, no. 4 (2019): 53:1–53:21.
Yu Emma Wang, Weikang Qian, Shuchang Zhang, Xiaoyao Liang, and Bo Yuan. "A
Learning Algorithm for Bayesian Networks and Its Efficient Implementation on GPU," IEEE Transactions
on Parallel and Distributed Systems. vol. 27, no. 1 (2016): 17–30.
Weichao Tang, Yu Emma Wang, Haopeng Liu, Tao Zhang, Chao Li, and Xiaoyao
Liang. "Exploring Hardware Profile-Guided Green Datacenter Scheduling."
International Conference on Parallel Processing (ICPP), pp. 11-20. 2015.
Dissertation
Yu Emma Wang. "Performance Analysis for Machine Learning Applications." PhD
Dissertation, Harvard University, Nov 2019.
Patents
Yu Emma Wang, Dehao Chen, Phitchaya Mangpo Phothilimthana, "Deploying optimization
profiles for compiling computer programs in data centers." 2023.
Hyojun Kim, Xiao Yu, Yu Emma Wang, Phitchaya Mangpo Phothilimthana,
"Caching compilation outputs using optimization profiles." 2022.
Yu Emma Wang, Thomas Benjamin Jablin, Caitlin King Stanton, "Workload
scheduling using queues with different priorities." 2022.
Open-Source Software
Feel free to download our software and use in your project. If you do, please cite our corresponding papers.
Professional Service
Technical Program Committee
- Machine Learning and Systems Rising Stars 2024
- Conference on Machine Learning and Systems (MLSys) 2024
- ACM International Conference on Architectural Support for Programming
Languages and Operating Systems (ASPLOS) 2024
- ACM/IEEE Supercomputing Conference (SC) 2023
- MLBench workshop in MLSys'23
- Conference on Machine Learning and Systems (MLSys) 2023
- ACM/IEEE Supercomputing Conference (SC) 2022
- Conference on Machine Learning and Systems (MLSys) 2022
- MLBench workshop in MLSys'21
- IEEE Computer Architecture Letters (CAL)
- ACM Transactions on Architecture and Code Optimization (TACO)
Talks
Demystify Bayesian Inference Workloads
- ISPASS, Madison, WI, March 2019.
- ADA Symposium, Ann Arbor, MI, April 2019.
A Systematic Methodology for Analysis of Deep Learning Platforms
- Google, Aug 2018.
- Google, Aug 2018.
- Google, Sep 2018. (No, the three lines are not typos.)
- Facebook, Sep 2018.
- ADA Center, Dec 2018.
- IBM, March 2019.
- Micron, May 2019.
- MLSys, March 2020.
Photography
I enjoy food, traveling, photographing and interacting with people.
These are samples of the outcome.
For more photos please refer to my 500PX page.
Copyright reserved :)
