Quanqi Hu / 胡筌淇 google scholar LinkedIn

I am a research scientist at Meta. I obtained my PhD in computer science from Texas A&M University. I was fortunate to be advised by Dr. Tianbao Yang. Before Texas A&M, I spent three years in the Applied Mathematical and Computational Sciences program at University of Iowa and recieved my master's degree in mathematics. I recieved my bachelor's degree in mathematics from the Pennsylvania State University.

Experience

• Research Scientist, Meta, June 2025 - Now
  

• AI/ML PhD Intern, GE Healthcare, May - Aug. 2024
  - Utilized a latent diffusion model to generate synthetic 3D cardiac CT volumes along with their corresponding segmentation masks.
  - Enhanced segmentation performance on 3D cardiac CT volumes by incorporating the generated synthetic volumes and masks into the training process.
  - Further improved segmentation accuracy through the application of a self-supervised learning pretraining procedure.
  

• Research Scientist Intern, KLA, May - Aug. 2023
  - Improved the defect detection performance on scanning electron microscope (SEM) images using self-supervised pretrained Vision Transformer (ViT).
  - Applied Low-Rank Adaptation (LoRA) to further improve the training efficiency.
  

Publications

• Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions [Preprints]
  Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang.
  To appear in Conference on Neural Information Processing Systems (NeurIPS), 2024.

• Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization [Preprints]
  Quanqi Hu, Dixian Zhu, Tianbao Yang.
  In Conference on Neural Information Processing Systems (NeurIPS), 2023.

• Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization [Preprints]
  Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang.
  In International Conference on Machine Learning (ICML), 2023.

• Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization [Preprints]
  Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang.
  In International Conference on Machine Learning (ICML), 2023.

• Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization [Preprints]
  Quanqi Hu, Yongjian Zhong, Tianbao Yang.
  In Conference on Neural Information Processing Systems (NeurIPS), 2022.

• Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence [Preprints]
  Zi-Hao Qiu*, Quanqi Hu*, Yongjian Zhong, Lijun Zhang, Tianbao Yang.
  In International Conference on Machine Learning (ICML), 2022.

• A Stochastic Momentum Method for Min-max Bilevel Optimization [PDF]
  Quanqi Hu, Bokun Wang, Tianbao Yang.
  In NeurIPS Workshop on Optimization for Machine Learning (OPT), 2021.

* Denotes Equal Contribution.

Preprints

• Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning [Preprints]
  Qi Qi, Quanqi Hu, Qihang Lin, Tianbao Yang.
  

• Randomized Stochastic Variance-Reduced Methods for Multi-Task Stochastic Bilevel Optimization [Preprints]
  Zhishuai Guo, Quanqi Hu, Lijun Zhang, Tianbao Yang.
  

Teaching Assistant

• MATH:1560 Engineer Math II: Multivariable Calculus, University of Iowa, Fall 2021

• MATH:1260 The Mathematics of Pokemon Go, University of Iowa, Spring 2021

• MATH:2560 Engineer Math IV: Differential Equations, University of Iowa, Fall 2020

• MATH:1440 Mathematics for the Biological Sciencess, University of Iowa, Fall 2020

• MATH:1460 Calculus for the Biological Sciences, University of Iowa, Spring 2020

• MATH:1380 Calculus and Matrix Algebra for Business, University of Iowa, Spring 2020

• MATH:3800 Elementary Numerical Analysis, University of Iowa, Fall 2019

• MATH:3600 Intro to Ordinary Differential Equations, University of Iowa, Fall 2019

Selected Awards

• Travel Award, Conference on Neural Information Processing Systems (NeurIPS), 2022

• Travel Award, International Conference on Machine Learning (ICML), 2022

• Steven and Sherry McCrystal Award, Penn State, April 2018

• Women in Math Scholarship, Penn State, April 2018

Services

• Conference Reviewer of ICML, NeurIPS.