# Sharon Zhou

> Source: https://aiwiki.ai/wiki/sharon_zhou
> Updated: 2026-11-05
> Categories: AI Research, People
> License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) - attribute to "AI Wiki (aiwiki.ai)"
> Cite as: AI Wiki. "Sharon Zhou." aiwiki.ai, 5 Nov 2026. https://aiwiki.ai/wiki/sharon_zhou
> From AI Wiki (https://aiwiki.ai), the free encyclopedia of artificial intelligence. Reuse freely with attribution.

**Sharon Zhou** is an artificial intelligence researcher, entrepreneur and educator. She co-founded the enterprise language-model company Lamini and served in AI leadership roles at [AMD](https://aiwiki.ai/wiki/amd). In November 2026, she announced that she had joined [Anthropic](https://aiwiki.ai/wiki/anthropic), describing the move as a return to frontier-model research.[1][4][5]

Her research includes the evaluation of generated images, the structure of learned representations, and training systems for GPU kernel generation. She has also taught courses on [generative adversarial networks](https://aiwiki.ai/wiki/generative_adversarial_network), [diffusion models](https://aiwiki.ai/wiki/diffusion_model) and [fine-tuning](https://aiwiki.ai/wiki/fine_tuning).[7][8][9][10][11][12]

## Education and academic work

Zhou studied computer science and Classics at [Harvard University](https://aiwiki.ai/wiki/harvard_university). In a 2021 interview with the Stanford Institute for Human-Centered Artificial Intelligence, she described becoming interested in computing through user-experience design and later moving from a product-management role at Google into doctoral research at [Stanford University](https://aiwiki.ai/wiki/stanford_university).[2]

She completed a Stanford doctorate in generative AI, as described in her subsequent first-person account and conference biography. [Andrew Ng](https://aiwiki.ai/wiki/andrew_ng) was her doctoral adviser.[4][5] Stanford's Center for Artificial Intelligence in Medicine and Imaging lists her as an adjunct lecturer in computer science.[3]

## Career

### Lamini

Zhou co-founded Lamini in 2022 and served as its CEO. In a November 2023 interview, she dated the company's start to the previous year, before ChatGPT's release. She described its purpose as helping enterprises adapt and run language models using their own data.[4]

Her account of the platform covered data ingestion, model fine-tuning, retrieval, reinforcement learning from feedback and inference. It also discussed supporting different computing environments, including AMD GPUs. These were descriptions of Lamini's product and engineering approach, rather than independent comparisons of its performance against other platforms.[4]

DeepLearning.AI's August 2023 announcement of *Finetuning Large Language Models* identified Zhou as Lamini's co-founder and CEO. Later conference biographies describe that role as preceding her work at AMD.[5][13]

### AMD

A 2025 conference biography identified Zhou as AMD's corporate vice president of AI. AMD's own 2026 *Advancing AI* event page listed her as AI Chief of Staff.[5][6] The company's public announcement of that appointment said it was intended to support AI leadership, partnerships and customer work.[14]

In her November 2026 departure announcement, Zhou said she had built and led an AI research organization at AMD and served as executive sponsor for its frontier-laboratory partnerships. She also described work on reinforcement-learning approaches to kernel optimization, and said some colleagues had accompanied her from Lamini to AMD.[1]

### Anthropic

Zhou's November 2026 announcement stated that she had joined Anthropic. She said she wanted to return to research on frontier models and thanked her former AMD team and Lisa Su. The post establishes the move, but does not identify the particular model, team or research program she would work on.[1]

## Research

Zhou's publications span generative-model evaluation and systems for training and deploying models. Selected work includes:

| Work | Research subject | Publication and scope |
| --- | --- | --- |
| *HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models* | Human assessment of generated-image realism, using timed perception and an untimed real-versus-generated-image test | Zhou is a co-author of the 2019 paper. It evaluates specified image-generation systems and datasets, rather than defining a universal measure of generative-model quality.[7] |
| *Evaluating the Disentanglement of Deep Generative Models through Manifold Topology* | Measuring disentanglement through the topological similarity of conditional submanifolds in a model's learned representation | Zhou is first author. The work has supervised and unsupervised variants; it was published at ICLR 2021.[8] |
| *AMDKernelVault: Large-Scale Datasets and Agentic Training for AMD GPU Kernel Optimization* | HIP and Triton kernel datasets, generation pipelines, compilation and execution checks, and model training for AMD hardware | Zhou is a co-author of the September 2026 preprint. Its experiments distinguish correctness, compilation and execution-speed results; leading one measure does not imply leading all of them.[9] |

The AMDKernelVault paper describes pipelines that turn PyTorch references into kernels, validate candidates under ROCm and profile their execution. It demonstrates supervised fine-tuning and execution-aware reinforcement learning with Qwen3-8B. The paper's results concern the reported workloads and evaluation budgets, rather than every AMD GPU or every kernel-generation task.[9]

Zhou was also a co-author of the June 2024 preprint *Banishing LLM Hallucinations Requires Rethinking Generalization*. The arXiv record marks the paper as withdrawn in September 2025. Its earlier model claims should therefore not be presented as established evidence that Lamini, or language models generally, solved [hallucination](https://aiwiki.ai/wiki/hallucination).[15]

## Teaching

Zhou has taught practical generative-AI courses through DeepLearning.AI and Coursera. The course pages describe different areas of model development:

| Course | Documented subject |
| --- | --- |
| *Generative Adversarial Networks (GANs) Specialization* | Building and evaluating GANs, conditional generation, image-to-image translation, bias and privacy. The current instructor list includes Zhou, Eda Zhou and Eric Zelikman.[10] |
| *How Diffusion Models Work* | Implementing diffusion-model sampling, training a noise-prediction network and conditioning image generation.[11] |
| *Finetuning Large Language Models* | Deciding when to fine-tune, preparing data, training a model and evaluating the result.[12] |

DeepLearning.AI announced its GAN specialization in September 2020 with Zhou as the course instructor. Its 2023 fine-tuning course announcement connects her teaching to her work at Lamini.[13][16]

## Recognition

MIT Technology Review included Zhou in its global *Innovators Under 35* list in 2022, recognizing her work on benchmarks for evaluating generated content and images.[17]

## References

1. Sharon Zhou (@realSharonZhou). [Announcement that she had joined Anthropic](https://x.com/realSharonZhou/status/2118032064016748630). X, November 4, 2026 UTC; rendered post inspected November 5, 2026.
2. Stanford HAI. [Sharon Zhou: We Can't Solve Society's Problems While Working in Silos](https://hai.stanford.edu/news/sharon-zhou-we-cant-solve-societys-problems-while-working-silos). January 4, 2021.
3. Stanford Center for Artificial Intelligence in Medicine and Imaging. [Sharon Zhou](https://aimi.stanford.edu/people/sharon-zhou). Academic directory, accessed November 5, 2026.
4. Matt Turck and Sharon Zhou. [Lamini: Fine-Tuning LLMs for the Enterprise with CEO Sharon Zhou](https://www.mattturck.com/podcast/lamini-fine-tuning-llms-for-the-enterprise-with-ceo-sharon-zhou). The MAD Podcast, November 8, 2023. Interview and transcript.
5. The AI Conference. [Sharon Zhou, 2025 speaker biography](https://aiconference.com/speakers/sharon-zhou-2025/). Accessed November 5, 2026.
6. AMD. [Advancing AI 2026](https://www.amd.com/en/corporate/events/advancing-ai.html). Official event and speaker page, accessed November 5, 2026.
7. Sharon Zhou et al. [HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models](https://arxiv.org/abs/1904.01121). arXiv:1904.01121, April 1, 2019; revised October 31, 2019.
8. Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar Carlsson and Stefano Ermon. [Evaluating the Disentanglement of Deep Generative Models through Manifold Topology](https://arxiv.org/abs/2006.03680). arXiv:2006.03680; ICLR 2021.
9. Ji Liu et al. [AMDKernelVault: Large-Scale Datasets and Agentic Training for AMD GPU Kernel Optimization](https://arxiv.org/abs/2609.12471). arXiv:2609.12471, September 11, 2026.
10. DeepLearning.AI. [Generative Adversarial Networks (GANs)](https://www.deeplearning.ai/specializations/generative-adversarial-networks-gans). Course and instructor information, accessed November 5, 2026.
11. DeepLearning.AI. [How Diffusion Models Work](https://www.deeplearning.ai/courses/diffusion-models). Accessed November 5, 2026.
12. DeepLearning.AI. [Finetuning Large Language Models](https://www.deeplearning.ai/courses/finetuning-large-language-models). Accessed November 5, 2026.
13. DeepLearning.AI Community Team. [Enroll in Finetuning Large Language Models](https://community.deeplearning.ai/t/enroll-in-finetuning-large-language-models/426067). August 23, 2023.
14. AMD. [Announcement of Zhou's AI Chief of Staff appointment](https://www.linkedin.com/posts/amd_congratulationssharon-zhou-phdon-your-activity-7445579967389724672-eI4k). Public company post, accessed November 5, 2026.
15. Johnny Li et al. [Banishing LLM Hallucinations Requires Rethinking Generalization](https://arxiv.org/abs/2406.17642). Original preprint June 25, 2024; arXiv records withdrawal on September 3, 2025.
16. DeepLearning.AI. [Introducing the Generative Adversarial Networks Specialization](https://www.deeplearning.ai/the-batch/introducing-the-generative-adversarial-networks-specialization/). September 30, 2020.
17. MIT Technology Review. [Sharon Zhou, Innovators Under 35](https://www.innovatorsunder35.com/the-list/sharon-zhou/). Global list, 2022.