--- title: From MIT to IBM, expediting AI and quantum deployment description: A profile of three MIT-affiliated researchers now at IBM Research who worked with the MIT-IBM Computing Research Lab (formerly MIT-IBM Watson AI Lab) during... canonical: https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: From MIT to IBM, expediting AI and quantum deployment | daily.dev og:description: A profile of three MIT-affiliated researchers now at IBM Research who worked with the MIT-IBM Computing Research Lab (formerly MIT-IBM Watson AI Lab) during... og:url: https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d og:image: https://api.daily.dev/og/posts/zOJFfF78d.png og:image:alt: From MIT to IBM, expediting AI and quantum deployment og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # From MIT to IBM, expediting AI and quantum deployment **[MIT News](https://daily.dev/sources/mit)** · 7 min read · 0 upvotes · 0 comments ## Summary A profile of three MIT-affiliated researchers now at IBM Research who worked with the MIT-IBM Computing Research Lab (formerly MIT-IBM Watson AI Lab) during their PhDs or postdocs. Zhang-Wei Hong applies curiosity-driven reinforcement learning to agentic frameworks and self-evolving model weights at deployment time. Irene Ko works on trustworthy AI, building vLLM Hook, a lightweight inference engine plugin that accesses internal model signals like hidden states to detect prompt-injection and hallucination risks without the overhead of low-rank adapters. Srinivasan Arunachalam focuses on quantum machine learning theory, contributing to papers on Hamiltonian learning and quantum kernels that provide rigorous guarantees and theoretical evidence for quantum advantages over classical methods. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is vLLM Hook and how does it help with trustworthy AI in LLM inference? vLLM Hook is a lightweight inference engine plugin framework developed by IBM researcher Irene Ko that provides direct access to internal model signals, such as hidden states and activations, during LLM decoding. It analyzes safety scores like prompt-injection likelihood and hallucination risk by acting on transformer modules, offering a bridge between AI development and deployment without the overhead of low-rank adapters. _daily.dev surfaces research like this for engineers building safer LLM inference pipelines._ ## Similar posts on daily.dev - [The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing](https://daily.dev/posts/the-mit-ibm-computing-research-lab-launches-to-shape-the-future-of-ai-and-quantum-computing-xtloa8jtb) · MIT News · 0 upvotes · 0 comments - [MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact](https://daily.dev/posts/mit-ibm-watson-ai-lab-seed-to-signal-amplifying-early-career-faculty-impact-slepnceti) · MIT News · 0 upvotes · 0 comments - [Creating AI that matters](https://daily.dev/posts/creating-ai-that-matters-nljax0avj) · MIT News · 0 upvotes · 0 comments - [AI at MIT](https://daily.dev/posts/ai-at-mit-dnjiniz46) · MIT Technology Review · 0 upvotes · 0 comments - [Charting the future of AI, from safer answers to faster thinking](https://daily.dev/posts/charting-the-future-of-ai-from-safer-answers-to-faster-thinking-ueq97jy7f) · MIT News · 0 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#quantum-computing](https://daily.dev/tags/quantum-computing), [#reinforcement-learning](https://daily.dev/tags/reinforcement-learning), [#ibm](https://daily.dev/tags/ibm) [View this post on daily.dev](https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"From MIT to IBM, expediting AI and quantum deployment","url":"https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d"},"datePublished":"2026-09-02T20:28:36.930Z","dateModified":"2026-09-02T22:23:05.283Z","description":"A profile of three MIT-affiliated researchers now at IBM Research who worked with the MIT-IBM Computing Research Lab (formerly MIT-IBM Watson AI Lab) during...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/28d362eaad9c6e3a3618f423766c1af9?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/28d362eaad9c6e3a3618f423766c1af9?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"MIT News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"MIT News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/881e20a40aa44b12ba4bd27f5c14289d","url":"https://daily.dev/sources/mit"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"llm,quantum-computing,reinforcement-learning,ibm","timeRequired":"PT7M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"MIT News","item":"https://daily.dev/sources/mit"},{"@type":"ListItem","position":3,"name":"From MIT to IBM, expediting AI and quantum deployment"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/from-mit-to-ibm-expediting-ai-and-quantum-deployment-zojfff78d#faq","mainEntity":[{"@type":"Question","name":"What is vLLM Hook and how does it help with trustworthy AI in LLM inference?","acceptedAnswer":{"@type":"Answer","text":"vLLM Hook is a lightweight inference engine plugin framework developed by IBM researcher Irene Ko that provides direct access to internal model signals, such as hidden states and activations, during LLM decoding. 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