Dr. Alex Johnson ☕️

Dr. Alex Johnson

(he/him)

Senior AI Research Scientist

Meta AI

Professional Summary

Alex Johnson is a Senior AI Research Scientist at Meta AI. His research has been published in top conferences like NeurIPS and ICML, with over 10,000 citations. Alex is passionate about pushing the boundaries of AI while ensuring ethical development.

Education

PhD Computer Science

2015-09-01
2019-06-30

Stanford University

MS Computer Science

2013-09-01
2015-05-31

Carnegie Mellon University

BS Computer Science

2009-09-01
2013-05-31

MIT

Interests

Large Language Models Computer Vision Reinforcement Learning AI Ethics
📚 My Research

Use this area to speak to your mission. I’m a research scientist in the Moonshot team at DeepMind. I blog about machine learning, deep learning, and moonshots.

I apply a range of qualitative and quantitative methods to comprehensively investigate the role of science and technology in the economy.

Please reach out to collaborate 😃

Featured Publications
An example preprint / working paper featured image

An example preprint / working paper

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Best Paper Award An example conference paper featured image

An example conference paper

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Dr. Alex Johnson
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Recent Publications
Recent & Upcoming Talks
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Create Beautiful Presentations with Markdown

Discover how to create stunning, interactive presentations using simple Markdown — no PowerPoint, Keynote, or vendor lock-in required.

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Recent News

The AI Governance Services Companies Actually Pay For

Ask ten executives what “AI governance” means and you will get ten different answers. Ask their finance departments what they are actually invoicing for, and the picture gets …

Agent Identity and Delegated Authority for Risk Managers

Autonomous agents stopped being a lab experiment sometime in the last eighteen months. They now book travel, adjust pricing, reconcile invoices, write code, and answer customers …

An AI Governance Platform, Just an Expensive Dashboard?

AI Governance Platforms: A Buying Guide for GRC Leaders AI governance is quickly outgrowing spreadsheets and internal policy documents. This guide breaks down what an AI governance …

The Architecture Decisions CAIOs Cannot Delegate to Engineering

How Machine Learning Systems Evolve Toward Production-Grade Architecture Failures in production for new AI systems usually trace back to a decision made in the initial week of a …

How an Enforceable Control Plane Protects AI ROI

Operationalizing AI Governance Risks and Controls: Why policy documents stop shadow AI on paper only, and what a tested, signed, audited control chain looks like once it runs …

How Large Language Models Evolve Into Autonomous AI Agents

Enterprise AI has shifted from single-turn chatbots to autonomous agents, but few engineering teams actually understand the underlying architecture end-to-end. This guide breaks …

New Book AI Risk Quantification: A Practical Roadmap for Chief AI Officers

A practitioner framework for turning ambiguous AI exposure into decision-grade evidence. AI governance has a credibility problem. Many teams still document model inventory, assign …

AI ROI Adoption Plan For Cost And Revenue Gains

Deploying artificial intelligence inside a modern enterprise is rarely a purely technical hurdle. The harsh reality of the current market is that up to ninety five percent of …

Practitioner Disciplines That Separate Profitable AI From Expensive AI

A field guide for Chief AI Risk Officers, CTOs, auditors, and general counsels who own what happens after the model ships A model that hits 96 percent accuracy in validation can …

Critical Cost Discipline for Your AI Systems

A 3x cost differential for comparable performance on token consumption is not a procurement problem. It is an architectural failure waiting to happen. I sat in a review where the …