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RAISE 2025 panel statement on aligning AI to clinical values
Recently, I attended the Responsible AI for Social and Ethical Healthcare 2025 “2.0” Symposiu...
Some Lessons on Reviews and Rebuttals
Writing and responding to reviews is the bread and butter of any academic and especially in AI research, PhD students are confronted with both rather...
Thoughts on Watermarking AI-Generated Content
Watermarking AI-generated content has the potential to address various problems that generative AI threatens to aggravate — misinformation, impe...
Thoughts and Lessons for Planning Rater Studies in AI
With the goal of deploying generative AI systems, rater studies are becoming increasingly common and important. This means more and more researchers a...
Computer Vision Research
Open-Sourcing Relabeled MedQA and Dermatology DDx Datasets
Dealing with rater disagreement is becoming more important in AI, especially for LLMs and in specialized domains such as health. In the past year, I h...
Thinking About Research Ideas vs. Technology
In this article, I want to share some thoughts on the difference between research ideas and technology, particularly in machine learning. This distinc...
The Importance of Effectively Experimenting in an AI PhD
Engineering and running experiments are a key component of most PhDs in AI. While there are plenty of more theoretical topics that are often limited t...
FAQ for our Monte Carlo Conformal Prediction
Over the past months, I have given several talks about Monte Carlo conformal prediction and the problem of calibrating ...
Documenting your PhD — Keeping Track of Meetings, Experimen…
A PhD can be a difficult endeavour. While becoming an expert in tackling a specific problems, it is easy to lose track of things: Have I read this pap...
On NeurIPS’ High School Paper Track
The decision to have a separate High School Project Track at NeurIPS 2024 has sparked quit...