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Shreya Shankar
@sh_reya
Incoming asst. professor @CSDatCMU. I ♥️ Databases, HCI, AI. Created docetl.org and evals.info. PhD @Berkeley_EECS; undergrad @Stanford CS.
Berkeley, CA
sh-reya.com
Born December 5
Joined January 2014
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    Shreya Shankar
    @sh_reya
    May 12
    I'm joining Carnegie Mellon's CS Department (and HCII by courtesy) as an assistant professor in Fall 2027! I'll be recruiting PhD students next cycle. If you're interested in AI systems or human-AI collaboration, list me in your application. Stay tuned for more about my new lab!
    217K
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    Shreya Shankar
    @sh_reya
    Oct 10, 2020
    how it started how it's going
  • user avatar
    Shreya Shankar
    @sh_reya
    Sep 25, 2025
    I’m tired of being “absolutely right!” when coding with an agent
    263K
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    Shreya Shankar
    @sh_reya
    Jul 5, 2021
    Recently I realized that the biggest benefit of going to Stanford is not the high quality of education or the network of successful people. It is the entitlement we develop, which the industry mistakes for confidence, that allows us to aim high and actually achieve our goals.
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    Shreya Shankar
    @sh_reya
    May 4, 2022
    I probably should have written this years ago, but here are some MLOps principles I think every ML platform (codebase, data management platform) should have: 1/n
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    Shreya Shankar
    @sh_reya
    Jul 18, 2020
    Got my invite to the @OpenAI GPT-3 API from @gdb. I actually think it deserves more hype than it’s getting, but not necessarily for the magical reasons Twitter touts. Why? My quick thoughts and impressions: (1/11)
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    Shreya Shankar
    @sh_reya
    Jul 19, 2020
    After many hours of retraining my brain to operate in this "priming" approach, I also now have a sick GPT-3 demo: English to LaTeX equations! I'm simultaneously impressed by its coherence and amused by its brittleness -- watch me test the fundamental theorem of calculus. cc @gdb
    00:00
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    Shreya Shankar
    @sh_reya
    Dec 23, 2022
    Visiting my family for the holidays, and my 17 y/o sister said that “everyone at school used chatGPT for their final essays” and asked me if I “have W riz”
    483K
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    Shreya Shankar
    @sh_reya
    Jul 28, 2025
    no one asked for a list of every AI evals question ever, but Hamel made it anyway 🤯
    Blog post screenshot showing the table of contents for an AI evaluation FAQ, including sections on fundamentals, error analysis, metrics, annotation, and tools.
    56K
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    Shreya Shankar
    @sh_reya
    May 25, 2023
    once again I spent 30m pair programming with chatgpt to debug something only to find that the first google search result (stackoverflow link) immediately answered my question
    299K
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    Shreya Shankar
    @sh_reya
    Apr 29, 2025
    it's happening 🥳🎉 I'm having a lot of fun writing this if you know of any papers or blog posts I should reference, please comment with the links!
    207K
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    Shreya Shankar
    @sh_reya
    Sep 12, 2023
    thinking about how, in the last year, > 5 ML engineers have told me, unprompted, that they want to do less ML & more software engineering. not because it’s more lucrative to build ML platforms & devtools, but because models can be too unpredictable & make for a stressful job
    333K
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    Shreya Shankar
    @sh_reya
    Sep 24, 2024
    LLMs have made exciting progress on hard tasks! But they still struggle to analyze complex, unstructured documents (including today's Gemini 1.5 Pro 002). We (UC Berkeley) built 📜DocETL, an open-source, low-code system for LLM-powered data processing: data-people-group.github.io/blogs/2024/09/…
    341K
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    Shreya Shankar
    @sh_reya
    Sep 20, 2022
    Our understanding of MLOps is limited to a fragmented landscape of thought pieces, startup landing pages, & press releases. So we did interview study of ML engineers to understand common practices & challenges across organizations & applications:
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    arxiv.org
    Operationalizing Machine Learning: An Interview Study
    Organizations rely on machine learning engineers (MLEs) to operationalize ML, i.e., deploy and maintain ML pipelines in production. The process of operationalizing ML, or MLOps, consists of a...