About Me

Hello, world! I’m Andy. I work at Microsoft. I’m an AI researcher, entrepreneur and VC, and activist. I like to write, but I’d rather build things. I’m fascinated by the ways that technology (when carefully applied) can bring about real impact. I hate injustice.

Things I think I think

I think bringing early-stage technologies to market is a hard, but worthwhile. I’m a Group Program Manager at Microsoft working on bringing new AI technologies to enterprises of all sizes. I previously was the Chief Product Officer for the Intel® Saffron™ Cognitive Solutions Group in Hillsboro, Oregon.

I think success should be measured in terms of global impact. I was a Senior Director for Innovation at Vulcan Inc., where I led teams that tackled some of the world's most important problems, from climate change and clean energy to biodiversity and global health. I co-founded the Vulcan Proving Ground (an early-stage technology incubator) and worked closely with Paul Allen as his Executive Technical Advisor.

I think that small teams can accomplish amazing things. I've founded (and run) three consumer-facing startups: A.R.O. Inc., Swingly, and Extractiv. I also served as CEO of Language Computer Corporation, an amazing natural language processing company that built some of the best systems in question-answering, information extraction, and textual inference in the early 2000s.

I'm not intimidated by hard problems. I've led research in natural language processing, machine learning, artificial intelligence, computer vision, and ubiquitous computing. I even publish (sometimes). My work can be found in the proceedings of AAAI, ACL, SIGIR, and NIPS.


Random headshots from over the years:


An ever-growing list of things I’d like to learn more about:

  • Neuroscience

    • Neuromorphology, neural structure and function

    • Brain Mapping

    • Neurobiology of decision making, especially reasoning under uncertainty

  • Artificial Intelligence and Machine Learning

    • Generative models for language, image, and video

    • Automated training models based on synthetic sources of data

    • Computational perception, including computer vision, digital olfaction

    • Explaining predictions of machine learning-based models

    • Modeling/anticipating sources of bias

    • Semi-supervised learning, active learning, machine teaching

    • Acquisition of common sense knowledge (and other kinds of knowledge)

    • Computational creativity

  • Natural Language Processing and Linguistics

    • Recognition of false and/or contradictory knowledge (“fake news”)

    • Multi-turn dialog agents

    • Computational approaches to inferring discourse structure

    • Machine reading and textual inference

    • Automatic question-answering (including answering complex questions!)

  • Robotics and autonomy

    • Required infrastructure for autonomous vehicles in developing world

    • Quantification of ethical risk / ethical reasoning (“Creepy Trolley”)

    • Robust strategies for locomotion

    • Sensor fusion and SLAM

    • Soft Robots

  • The evolution of cities, and urban planning

    • Traffic design and transportation planning

  • Resource planning, especially under unreliable/scarce supply

  • The evolution of governments and representational systems

    • Tracking changes in government and policy

    • Catalyzing engagement

  • Organizational Psychology, especially operations theory, business process redesign

  • Economic and behavioral incentives, game theory

  • Innovation at scale

    • Incentives for sponsoring cutting-edge R&D, opportunity zones

    • Alternatives to startup incubators, etc.

  • Policy vs. global pandemics

  • Computational biology

    • Gene discovery and editing

    • Automatic discovery of synthesis pathways

  • Conservation and biodiversity

    • Large-scale remote sensing for resource preservation

    • Ocean health; countering ocean acidification and pollution

    • Counter-IUU policy

    • Economic incentives (or dis-incentives) for conservation