⏳ One month to go! This is your chance to contribute to transforming healthcare. Let’s bring your #MachineLearning breakthroughs to the world stage!🗺️ Review our call for participation. Mark your calendar for the #ML4H2023 Sep 7 deadline. 🔗ml4health.github.io/2023/call_for_…

⏳ Only 3 days left to join our Reviewer Mentorship Program! Want to review a ML4H paper but don't feel confident yet to do it alone? Interested in guiding early-stage researchers on reviewing? 💯 Sign up before Aug 30! 🔗 forms.gle/zRJjqYskMUvxoR…

Just ONE week left to submit your groundbreaking ML research to #ML4H! Dive into themes like 'ML for Health Equity & Global Health' or 'Generative AI for Health.'✨ 📑 Proceedings Track 🔍 Findings Track (including non-traditional research!) Submit now! 🔗ml4health.github.io/2023/call_for_…

📢 Good news for #ML4H contributors! Submission deadline is now extended to Sept 12 AoE. 🚀 But you must create your submission on OpenReview by Sept 7 AoE with title, authors, track, subject, & modality. Edits to metadata after 7th won't be accepted. #DeadlineExtension 📌🗓️

📣A massive shoutout to Google for being an incredible sponsor for #ML4H2023! 🫶 Your support is pushing the boundaries of machine learning in healthcare, bringing innovative solutions closer to reality. Together, we’re reshaping the future of health! 🤖🩺 #ThankYouGoogle

Thinking about tech in #publichealth? Our study of 4mil public-sector vaccinations in clinic or via health workers w/ mobile phones provides important considerations for deployment of tech at scale journals.plos.org/globalpubliche… PLOS Global Public Health NYUGPHBiostats NYU Tandon nyupublichealth

I am recruiting PhD students for Fall '24! Please apply to Cornell CS if you are interested in ML, data science, health, or inequality. Feel free to retweet! We are based in NYC - here's the view from our island campus (taken during Pride - note the rainbow lights!)

It's that time of the year again, so re-surfacing this: github.com/shaily99/advice (It is not advice from me, it is just a dump of my bookmarks to helpful articles from when I was applying to grad school)

📢 I am recruiting Ph.D. students for my new lab at New York University! Please apply, if you want to work on understanding deep learning and large models, and do a Ph.D. in the most exciting city on earth. Details on my website: izmailovpavel.github.io. Please spread the word!

Thanks to the generosity of our sponsors, we are pleased to offer travel grants for early career trainees in need of financial assistance. If you are in need of travel support, please fill out this form by November 8: forms.gle/GkkpnGSrXxpcj7…

🌟 Keynote Alert! 🌟 We're thrilled to announce Dr. Elaine O. Nsoesie as one of the keynote speakers for #ML4H! A prominent advocate for health equity, she's a game-changer in leveraging data and AI to address social disparities in healthcare. 🏥🌍

🌟 ML4H 2023 kicks off tomorrow! 🌟 We can't wait to welcome you all. Spread the word: on-site registrations are available on a first-come, first-served basis at the check-in desk. See you there!

It was an absolute wonder organizing ML4H with these awesome folks! I'll be around at neurips until Friday! I'm also on the job market, feel free to grab me to chat!

On Friday (tomorrow), join me in running back and forth between the overlapping NeurIPS Distribution Shift and Algorithmic Fairness workshop poster sessions and roundtables for discussion on work related to the intersection of fairness, distribution shift, and causality.

At the AFT poster session (10:20-11), Vishwali Mhasawade will discuss her work with me and Alexander D'Amour (@alexdamour.bsky.social), "A Casual Perspective on Label Bias", that aims to use casual models to better understand the fairness issues posed by the use of biased proxy labels.

Our #CallForParticipation is out! Machine Learning for Health (ML4H) is back! It will be in-person in Vancouver, Canada on December 15 & 16, co-located with NeurIPS Conference Be sure to retweet and follow ML4H for more details! ahli.cc/ml4h/call-for-…

Calling all potential mentors! Many talented early-career students have signed up for our mentorship programs, and they need you! For both reviewer mentorship & career mentorship! Sign up before Aug 30!

New paper and software alert! arxiv.org/abs/2408.14620 Interested in modern mediation analysis methods with machine learning and multivariate mediators? Take a look at this joint work with Richard Liu, @nickWillyamz , and Kara Rudolph Short 🧵...

Our latest work on data, AI and public health out in PNASNews We uncover robustness issues in Google Street View data and also show the necessity of causal frameworks for trustworthy decision making using AI pnas.org/doi/10.1073/pn…

We’re thrilled to announce Adarsh Subbaswamy Adarsh Subbaswamy, Regulatory Scientist at the FDA, as a speaker at #ML4H! His pioneering work focuses on reducing algorithmic bias and improving the reliability of machine learning models in healthcare. 🏥💻 #ML4H2024