Pengtao Xie (@cmuptx) / X

Pengtao Xie

83 posts

Pengtao Xie

@cmuptx

Cofounder of AIBuildAI. Associate Professor at UC San Diego. PhD@CMU CS. Developing AI agents that automatically build AI models. aibuildai.io

Joined January 2015

Pinned
Pengtao Xie
@cmuptx
Mar 17
🚀 Excited to release AIBuildAI — an AI agent that automatically builds AI models 🏆 #1 on OpenAI MLE-Bench 💻 GitHub: github.com/aibuildai/AI-B… Building AI models still requires a lot of manual work — designing models, writing code, training them, tuning hyperparameters, and
00:00
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Pengtao Xie
@cmuptx
Jun 30, 2025
I am thrilled to be promoted to Associate Professor with tenure at UC San Diego. I am deeply grateful for the outstanding work of my students over the past five years, the strong support of colleagues, the valuable help of collaborators, and the unwavering support of my family!
17K
Pengtao Xie
@cmuptx
Jul 8, 2025
We are excited to organize NeurIPS 2025 2nd Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences. The workshop features a stellar lineup of invited speakers, including Ziv Bar-Joseph, Charlotte Bunne @_bunnech , Simona Cristea @simocristea ,
17K
Pengtao Xie
@cmuptx
Jul 18, 2025
If you are at ICML2025, welcome to attend our workshop "Multi-modal Foundation Models and Large Language Models for Life Sciences" tomorrow (Jul 19 Saturday). The workshop features a stellar lineup of invited speakers, including Valentina Boeva @val_boeva, Manolis Kellis
20K
Pengtao Xie
@cmuptx
Jul 14, 2025
🚀 Excited to share that our work GenSeg has been published in Nature Communications! GenSeg is an end-to-end, downstream-task-guided framework for generating synthetic training data for medical image segmentation. It significantly reduces the need for manual annotations — by a
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Pengtao Xie
@cmuptx
Sep 2, 2025
Our paper "Generative AI enables medical image segmentation in ultra low-data regimes" is selected as Nature Communications Editors’ Highlights ("the 50 best papers recently published")! nature.com/collections/aa… @james_y_zou @_ahmedmalaa @segal_eran
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Pengtao Xie
@cmuptx
Mar 21, 2021
We recently propose a new machine learning framework, Skillearn: machine learning inspired by humans' learning skills. Project page: pengtaoxie.github.io/skillearn.html
Pengtao Xie
@cmuptx
Aug 24, 2020
We are organizing a NeurIPS 2020 workshop: Self-supervised Learning -Theory and Practice. We invite submissions of short papers. The submission deadline is Oct 10. The workshop is featured with 13 invited talks. The website of the workshop is sslneuips20.github.io
Pengtao Xie
@cmuptx
Aug 5, 2025
We are excited to share the Call for Papers for the NeurIPS 2025 2nd Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences. We welcome paper submissions that are up to 4 pages in length (excluding references) formatted using NeurIPS 2025 paper
openreview.net
NeurIPS 2025 Workshop FM4LS
Welcome to the OpenReview homepage for NeurIPS 2025 Workshop FM4LS
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Pengtao Xie
@cmuptx
Jul 1, 2025
Excited to share our recent work DreamPRM, a multi-modal LLM reasoning method achieving first place on the MathVista leaderboard. DreamPRM is an LLM-agnostic framework that can be applied to any multi-modal LLM for improving its reasoning capabilities. It is a bi-level
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Pengtao Xie
@cmuptx
Feb 8, 2021
Our workshop "Trustworthy AI for Healthcare" organized at AAAI will be held tomorrow (8:30 am - 6:50 pm PST on Feb 9). The workshop is featured with 13 speakers and 23 accepted papers. Welcome to attend! Zoom link: zoom.us/j/3305983771?p…
Pengtao Xie
@cmuptx
Dec 12, 2020
Our NeurIPS workshop on Self-supervised Learning - Theory and Practice will be held tomorrow: 8:50 am to 6:40 pm PST on Dec 12. Welcome to attend. The workshop is featured with 13 invited talks and 45 accepted papers. Workshop webpage: neurips.cc/virtual/2020/p…
Pengtao Xie
@cmuptx
Jul 6, 2020
I am happy to share our recent work "Differentially-private Federated Neural Architecture Search" arxiv.org/abs/2006.10559… Code: github.com/UCSD-AI4H/DP-F…
Pengtao Xie
@cmuptx
Jan 16, 2025
I am excited to receive the NIH Maximizing Investigators' Research Award (MIRA) for Early Stage Investigators. I am deeply grateful to my students for their great work over the past few years and to my collaborators for their strong support and help!
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