I want to be able to make the world a better place and I believe I can best do this by developing and applying AI.
I’m currently a PhD Candidate at the University of Washington studying reinforcement learning, planning, robotics. I'm advised by Sidd Srinivasa and supported by an NDSEG Fellowship. I run marathons, rock climb, backpack, read, and cook in my spare time.
For anything queer related, please contact me at william dot agnew at ostem dot org for privacy reasons.
September 2021: Published Rebuilding Trust: Queer in AI Approach to Artificial Risk Management in response to the NIST AI Risk Management RFI
August 2021: My paper Documenting Large Corpora: A Case Study on the Colossal Clean Crawled Corpus accepted to EMNLP! See coverage in Unite.AI: Minority Voices ‘Filtered’ Out of Google Natural Language Processing Models
June 2021: Released a new paper The Values Encoded in Machine Learning Research!
June 2021: My work with Queer in AI profiled in MIT Tech Review: Inside the fight to reclaim AI from Big Tech's control
June 2021: Gave the D&I keynote at NAACL'21: Give Your Time to Radical Communities, Not Your Boss
May 2021: I'm serving as a social chair for ICLR '22!
February 2021: Talked about "bad" words and impacts on NLP models in Wired: AI and the List of Dirty, Naughty, Obscene, and Otherwise Bad Words
January 2021: Discussed LGBTQ research in "‘This deserves our attention.’ New data highlight LGBTQ scientists’ workplace challenges" from Science Magazine
Moderated the panel "What are We Going to Do About Computer Vision?"
November 2020: I'm organizing the Queer in AI @ CoRL Social
October 2020: My paper Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity was accepted to CoRL 2020 as an oral (20/~485)!
October 2020: New preprint Relevance-Guided Modeling of Object Dynamics for Reinforcement Learning on arxiv
July 2020: My paper Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity was accepted for a spotlight the the ICML Object-Oriented Learning (OOL): Perception, Representation, and Reasoning workshop
July 2020: I co-organized the Queer in AI ICML 2020 workshop and socials
May 2020: I gave a talk on amodal 3D reconstruction in cluttered environments to MIT CoCoSci
My current research focus is making AI that perceives, learns, and plans like humans. Humans learn much faster and generalize much better than AI. To close these gaps, I'm working on a variety of projects on object oriented representations and learning:
How should the world be represented as objects?
How can we perceive objects?
How can we quickly create 3D object reconstructions in cluttered environments?
How can we use an object representation to make learning and planning sample efficient, robust, transferable, and explainable?
I'm just as interested in understanding and working to solve the many problems AI creates and amplifies, and envisioning AI research, communities, institutions, and companies that use AI and the power it creates to radically change the world for the better. I explore these issues as an organizer for the wonderful Radical AI community.
I chose to research AI because AI will transform the world, and I want to help make sure AI transforms the world for the better.
Everyone will be affected by AI, so everyone should have an equitable voice in its development:
I founded Queer in AI in 2018 to make the AI community more accepting of queer researchers and raise awareness of problems AI can cause for queer people
I chaired the first Queer in AI @ NeurIPS satellite workshop, featuring talks by queer AI researchers and a panel on AI ethics for the queer community. I helped organize the Queer in AI ICML 2019, NeurIPS 2019, and ICML 2020 workshops, in addition to many Queer in AI socials
I served on the Diversity and Inclusion Advisory Board for the NeurIPS 2018 D&I co-chairs, helping make NeurIPS more welcoming to queer people
I serve as the Vice President of External STEM Partnerships of oSTEM
I helped start UW CSE's queer prospectives reception at our prospective grad student visit days
Robotics competitions gave me the opportunity to learn many of the skills I use as a researcher. Giving students the same opportunities is incredibly meaningful (and fun!) for me.
I've served on the planning committee of Georgia BEST
As an undergraduate at Georgia Tech, I helped start and lead the Undergraduate Research Ambassadors Program and the Big O Theoretical Computer Science Club, both of which have provided incredible opportunities, mentorship, and community for countless undergrads interested in research. I also proposed and organized the first Home Depot Deep Learning Competition which gives Georgia Tech students at a hands-on introduction to deep learning each year.
Mentoring brilliant students is one of the most impactful and meaningful things I do. If you are interested in working with me, please email me your resume and 2-3 paragraphs describing your interests.