profile pic

Eric Qu

PhD Student at UC Berkeley

CV

ericqu [at] {berkeley [dot] edu, meta [dot] com}

🖋 About Me

I am a second-year Computer Science PhD Student at University of California, Berkeley, Berkeley AI Research Lab (BAIR), advised by Aditi Krishnapriyan. I am also a visiting researcher at Meta Fundamental AI Research (FAIR), FAIR Chemistry Group, advised by Brandon Wood and Zachary Ulissi. I received my B.Sc. with distinction in Data Science from Duke Kunshan University and Duke University, where I was mentored by Dongmian Zou and Kai Zhang. I also worked as a research intern at Microsoft Research Asia, Shanghai AI/ML Group led by Dongsheng Li.

My research interest mainly falls on Geometric Deep Learning and AI for Science. Recently, I have been particularly interested in exploring how to scale up machine learning models to tackle complex challenges in scientific domains. More broadly, I am interested in combining ideas from mathematics with machine learning, and using machine learning to solve interdisciplinary problems.

🔥 News

📝 Publications

The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains

NeurIPS 2024 Poster

Eric Qu, Aditi Krishnapriyan

Paper Code

CNN Kernels Can Be the Best Shapelets

ICLR 2024 Poster

Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li

Paper Code

Hyperbolic Kernel Convolution: A Generic Framework

Learning on Graphs Conference (2024)

Eric Qu, Lige Zhang, Habib Debaya, Yue Wu, Dongmian Zou

Paper Code Poster

Autoencoding Hyperbolic Representation for Adversarial Generation

Transactions on Machine Learning Research (2024)

Eric Qu, Dongmian Zou

Paper Code Slides

Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer

ICLR 2023 Spotlight

Eric Qu, Xufang Luo, Dongsheng Li

Paper Code Slides Poster

Show/Hide More Publications

💬 Talks

🏆 Awards and Honors

📖 Educations

🏢 Work Experiences

🏫 Services

✈️ Travel Plans