Home | Learning from Time Series for Health
NeurIPS Workshop on Learning from Time Series for Health.
🩺📈 The "Learning from Time-series for Health (TS4H)" workshop is BACK at NeurIPS 2025 🥳!
This workshop unites researchers across health time-series domains (from wearables to clinical systems) to tackle shared challenges. Details: timeseries4health.github.io 🧵 (1/6)
18.07.2025 19:56 — 👍 1 🔁 1 💬 1 📌 0
Excited we have some papers accepted to ICML'25 in collaboration with some tremendous folks 🎉
Looking forward to Vancouver to discuss model editing for LLMs/VLMs and improving medical benchmarking!
11.05.2025 12:34 — 👍 1 🔁 0 💬 0 📌 0
Happy to share our ICLR'25 paper to be presented by @snagaraj.bsky.social! It's the first method to capture how label noise can change over time in sequential classification tasks. Many implications, one being towards better models of labelers' behavior over time, even for non-time series tasks 🎉
13.04.2025 23:52 — 👍 1 🔁 0 💬 0 📌 0
Super excited to share our new work on keeping LLMs factually up-to-date for long periods of time 🎉
13.04.2025 23:50 — 👍 1 🔁 0 💬 0 📌 0
machine learning for health at microsoft research, based in cambridge UK 🌻 she/her
PhD Student at Northeastern, working to make LLMs interpretable
Incoming Assistant Professor at UC Berkeley in CS and Computational Precision Health. Postdoc at Microsoft Research, PhD in CS at Stanford. Research in AI, graphs, public health, and computational social science.
https://serinachang5.github.io/
Assistant Prof at UCSD. I work on safety, interpretability, and fairness in machine learning. www.berkustun.com
IMPRS-IS PhD Student with Zeynep Akata and Matthias Bethge at the University of Tübingen and Helmholtz Munich, working on continually adapting foundation models.
Assistant professor of CS at UC Berkeley, core faculty in Computational Precision Health. Developing ML methods to study health and inequality. "On the whole, though, I take the side of amazement."
https://people.eecs.berkeley.edu/~emmapierson/
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Professor, researcher, author of Atlas of AI.
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Rightwing billionaires want to privatize NIH and use it to control universities.
We work to cure diseases like cancer.
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I'm a physician-scientist working in clinical NLP and LLM safety/evaluation. You'll find me in the lab or the rad onc clinic | BWH | DFCI | Harvard Medical School
www.bittermanlab.org
Assistant Professor @ Purdue CS.
Interested in machine learning and robotics.
CS PhD Student, Northeastern University - Machine Learning, Interpretability https://ericwtodd.github.io
Interpretable Deep Networks. http://baulab.info/ @davidbau
VP and Distinguished Scientist at Microsoft Research NYC. AI evaluation and measurement, responsible AI, computational social science, machine learning. She/her.
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Research Scientist @GoogleDeepMind. Representation learning for multimodal understanding and generation.
mitscha.github.io
