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Eric Qu

PhD Student at UC Berkeley


ericqu [at] berkeley [dot] edu

🖋 About Me

I am a first-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), 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. I also have experience in LLMs, sequence modeling, and graph neural networks. In general, I am interested in combining ideas from mathematics with machine learning, and using machine learning to solve interdisciplinary problems.

🔥 News

📝 Publications

CNN Kernels Can Be the Best Shapelets

ICLR 2024 Poster

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

Paper Code

Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer

ICLR 2023 Spotlight

Eric Qu, Xufang Luo, Dongsheng Li

Paper Code Slides Poster

Hyperbolic Convolution via Kernel Point Aggregation

arXiv:2306.08862 (Submitted to TPAMI)

Eric Qu, Dongmian Zou

Paper Code Poster

Autoencoding Hyperbolic Representation for Adversarial Generation

arXiv:2201.12825 (Submitted to JMLR)

Eric Qu, Dongmian Zou

Paper Code Slides

Lorentz Direct Concatenation for Stable Training in Hyperbolic Neural Networks

NeurIPS 2023, NeurReps Workshop Poster

Eric Qu, Dongmian Zou

Paper Poster

💬 Talks

🏆 Awards and Honors

📖 Educations

🏢 Work Experiences

🏫 Services