diff --git a/_config.yml b/_config.yml index db53770..2da35ce 100644 --- a/_config.yml +++ b/_config.yml @@ -1,8 +1,8 @@ title: "DAPLab" -tagline: "Data, Agents, and Processes | Columbia University" -description: "DAPLab at Columbia University advances research on agent-based automation across systems, AI, HCI, and operations research. We make automation more accountable, reliable, and efficient." +tagline: "Infrastructure for Trustworthy Agent Automation | Columbia University" +description: "DAPLab at Columbia University develops full-stack infrastructure for trustworthy AI agent automation in real-world environments. We vertically integrate expertise across operating systems, data systems, AI, HCI, security, and enterprise workflows to build end-to-end agentic systems with real guarantees around reliability, observability, safety, and control." author: "DAPLab, Columbia University" -keywords: "DAPLab, Columbia University, agent-based systems, AI, systems research, HCI, automation, large language models, trustworthy AI, cloud computing, RL, ML" +keywords: "DAPLab, Columbia University, trustworthy AI agents, agent automation, agentic systems, systems research, HCI, data systems, safety, reliability, observability, large language models, vertical integration" og_image: "/daplab_logo.png" baseurl: "" # Keep this blank for GitHub Pages root url: "https://daplab.cs.columbia.edu" # Full site URL without trailing slash diff --git a/_layouts/default.html b/_layouts/default.html index dcb44b8..90950bf 100644 --- a/_layouts/default.html +++ b/_layouts/default.html @@ -11,7 +11,7 @@ {% assign base_url = site.url | default: "https://daplab.cs.columbia.edu" %} {% assign page_title = page.title %} {% assign full_title = page_title | append: " | " | append: site_title %} - {% assign raw_desc = page.description | default: page.excerpt | default: site.description | default: "DAPLab at Columbia University advances research on agent-based automation across systems, AI, HCI, and operations research. We make automation more accountable, reliable, and efficient." %} + {% assign raw_desc = page.description | default: page.excerpt | default: site.description | default: "DAPLab at Columbia University develops full-stack infrastructure for trustworthy AI agent automation in real-world environments." %} {% assign meta_description = raw_desc | strip_html | normalize_whitespace | truncate: 200 %} {% assign meta_keywords = page.keywords | default: site.keywords | default: "DAPLab, Columbia University, agent-based systems, AI, systems research, HCI, automation" %} {% assign rel_image = page.image | default: site.og_image | default: "/daplab_logo.png" | relative_url %} @@ -46,7 +46,7 @@ "@context": "https://schema.org", "@type": "Organization", "name": "{{ site.title | default: 'DAPLab' }}", - "description": "{{ site.description | default: 'DAPLab at Columbia University advances research on agent-based automation across systems, AI, HCI, and operations research. We make automation more accountable, reliable, and efficient.' }}", + "description": "{{ site.description | default: 'DAPLab at Columbia University develops full-stack infrastructure for trustworthy AI agent automation in real-world environments.' }}", "address": { "@type": "PostalAddress", "addressLocality": "New York, New York", diff --git a/index.html b/index.html index dcefa34..170526b 100644 --- a/index.html +++ b/index.html @@ -9,12 +9,14 @@
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Building the Foundations for Trustworthy Agent Automation

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- The Data, Agents, and Processes Lab (DAPLab) at Columbia University is building the foundations for a future where AI agents safely and reliably automate complex work. We bring together researchers in data systems, applied AI, operating systems, HCI, algorithms, and business to invent the infrastructure, algorithms, and design principles needed to deploy agents in the real world. + The Data, Agents, and Processes Lab (DAPLab) at Columbia University develops the systems, infrastructure, and interaction principles required for AI agents to safely and reliably automate real work.

- Our work spans the full stack—from systems and training frameworks to human–agent interaction, process automation, and digital twins. We build open-source tools, collaborate closely with industry partners, and prototype agentic technologies that reimagine how work gets done. Based in the heart of New York City—home to some of the world’s largest enterprises—we are uniquely positioned to explore how agent automation transforms real organizational processes. DAPLab is a home for students, researchers, and partners who want to shape the next generation of AI-native systems. + We believe trustworthy agent automation cannot be solved at a single layer of the stack. DAPLab vertically integrates expertise across operating systems, data systems, AI, HCI, security, and enterprise workflows to build end-to-end agentic systems with real guarantees around reliability, observability, safety, and control.

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Why Vertical Integration Matters

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AI agents fail across the entire stack: models hallucinate, retrieval misses critical context, execution environments lack isolation, workflows leak data, and human oversight breaks under scale. Fixing only one layer is not enough.

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DAPLab brings together researchers across systems, databases, AI, HCI, security, and organizational workflows because trustworthy automation requires coordinated advances across the full agent stack — from infrastructure and state management to evaluation, safety, and human interaction.

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+ Human Interaction + ↑ + Agent Reasoning + Learning + ↑ + Retrieval + Memory + ↑ + Workflow + Policies + ↑ + Data + Execution Systems + ↑ + OS + Infrastructure +
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Trustworthy Automation Requires Integration Across Layers

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{% if site.ug_ms_application_url and site.ug_ms_application_url != '' %} diff --git a/projects/index.html b/projects/index.html index 4539e31..7c105e0 100644 --- a/projects/index.html +++ b/projects/index.html @@ -1,7 +1,7 @@ --- layout: default title: Projects -description: Explore DAPLab projects and software releases. +description: DAPLab develops the infrastructure needed to make AI agents safe, reliable, and deployable in real-world organizations. Explore our research projects and software releases. --- +
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Reliable and Trustworthy Agent Automation

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DAPLab develops the infrastructure needed to make AI agents safe, reliable, and deployable in real-world organizations. Our work spans four tightly connected research thrusts:

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Trustworthy Agent Execution
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Sandboxing, branching, checkpointing, isolation, and stateful execution environments for agents.
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Agent Safety and Governance
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Data flow control, policy enforcement, provenance tracking, and trustworthy automation constraints.
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Reliable Agent Evaluation
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Benchmarks, exploratory QA, simulation environments, and continuous evaluation infrastructure.
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Human-Agent Interaction and Usability
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Interaction design, human oversight interfaces, collaborative workflows, and usability research for humans working with and supervising AI agents.
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Projects