Intersectional/Interdisciplinary ML research @datascicolumbia. Physics PhD. Passionate about responsible, empowering, ethical tech. Always stay humble and kind.

Joined April 2015
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Just wrapped teaching my first semester of AI Ethics! My first full semester course and entirely designed from scratch…I’ll have many more thoughts to share but for now very thankful to my students for their engagement and willingness to think across disciplines 1/
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Happy to be in my favorite space at NeurIPS! To me, AI is political and my queerness is political and @QueerinAI holds space for me to embrace that rather than trying to suppress it. Beautiful discussions about community building in research and the world.
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I wish I had been in this room (or actually out as queer) in grad school. This space is an absolute treasure πŸ’•
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Also can’t wait for @willie_agnew co-design workshop!
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Super excited for this panel discussion on one of my favorite topics: the role of world models in building AI (especially AI for science)!
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I’m heading to Vancouver for NeurIPS! I’ll be speaking at the ML4PS workshop, the Regulatable ML workshop, and the Symmetry and Geometry workshop! Will share more details but my favorite part is always chatting with folks so please hmu if you’d like to grab coffee or a drink!
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Next up, this afternoon I'll be on a panel "AI for All: Advancing Responsibility, Fairness, & Queer Representation in Technology" at @Hunter_College , hosted by my friend/colleague Raj Korpan. Such an important topic as building truly useful & trustworthy AI takes everyone!
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actionable cybersecurity recommendations. Much of this work is led by my amazing students Selena Ding and Keri Yu. In addition to presenting our research, I'm very excited to discuss the way AI is reshaping the cyber threat landscape with so many public policy experts 2/
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I'm speaking at three very exciting events this week! First up today, the Columbia and New York State Conference on Cyber Regulation and Harmonization at Columbia | SIPA. I'll be presenting our research using customized AI models to identify, extract, and categorize 1/
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I’m at my first @AIESConf! Presenting my paper on AI Hype tonight. Hit me up if you’re around!
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Savannah Thais πŸ‘©πŸΌβ€πŸ’» retweeted
AI is unpredictable. Can physics make it trustworthy? Read our Q&A with @DataSciColumbia ’s Savannah Thais: bit.ly/3U9t0Ht #AI #DataForGood #Ethics

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Leaning into the Nobel Prize excitement, I'm very excited to share my new piece in Nature Reviews Physics @NatRevPhys exploring how physics data and approaches can help us develop more trustworthy AI (read for free here!) rdcu.be/dWfr3 1/

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While of course trustworthy AI is ultimately a sociotechnical problem and science cannot get us all the way there, I fundamentally believe that science has a critical role to play. 6/
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I'm thankful to have been working and learning in this rich interdisciplinary space for nearly a decade now and so excited to see how in continues to grow with increased education opportunities and industrial and governmental investment 7/7
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Savannah Thais πŸ‘©πŸΌβ€πŸ’» retweeted
Understanding what cutting-edge AI models do 'under the hood' requires not just theoretical research but also computational experiments. In this Comment, Savannah Thais @basicsciencesav explains why physics datasets may be the testing ground that's needed nature.com/articles/s42254-0…
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