Eric Qu

PhD Student at UC Berkeley

google scholar
github
linkedin

About Me

I am a first-year Computer Science PhD Student at University of California, Berkeley, advised by Aditi Krishnapriyan. I revived my B.Sc. with distinction in Data Science from Duke University and Duke Kunshan 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

  • [May 2023] Duke Kunshan University reported my undergrad story (in Chinese) here.
  • [May 2023] I graduated from Duke Kunshan University with distinction! 🎓
  • [Feb 2023] I am admitted to the EECS Ph.D. program of UC Berkeley!
  • [Jan 2023] Our work "Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer" is accepted (Spotlight) by ICLR'23! 🎉
  • [May 2022] I joined as a research intern in Microsoft Research Asia. 👨‍💼
  • [Aug 2021] Times Higher Education (Duke Kunshan University) reported our work in the news here.

Publications & Manuscripts

Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer

ICLR 2023 Spotlight (Notable Top 25%)

Eric Qu, Xufang Luo, Dongsheng Li

[Link] [Code] [Slides] [Poster]

CNN Kernels Can Be the Best Shapelets

Preprint (Submitted to NeurIPS 2023)

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

[Preprint] [Code]

Hyperbolic Convolution via Kernel Point Aggregation

arXiv:2306.08862, (Submitted to TPAMI)

Eric Qu, Dongmian Zou

[Preprint] [Code] [Poster]

Autoencoding Hyperbolic Representation for Adversarial Generation

arXiv:2201.12825, (Submitted to JMLR)

Eric Qu, Dongmian Zou

[Preprint] [Code] [Slides]

Lorentz Direct Concatenation for Stable Training in Hyperbolic Neural Networks

NeurIPS NeurReps Workshop, Poster, (2022)

Eric Qu, Dongmian Zou

[Link] [Poster]

Quantifying Nanoparticle Assembly States in a Polymer Matrix through Deep Learning

Macromolecules, 54 (7), 3034-3040, (2021)

Eric Qu, Andrew Matthew Jimenez, Sanat K. Kumar, Kai Zhang

[Link] [Code] [Dataset] [News]

→ Full list of projects and abstract

Experiences

Oral Presentation

Oral 6 Track 5: Applications & Deep Learning
ICLR 2023

May 2023 · Kigali, Rwanda

Poster Presentation

NeurReps Workshop,
NuerIPS 2022

Dec 2022 · New Orleans, USA

Exchange Student

Fall 2022,
Duke University

Aug 2022 - Dec 2022 · Durham, USA

Research Intern

Shanghai AI/ML Group,
Microsoft Research Asia

May 2022 - Jun 2023 · Shanghai, China

Teaching Assistant

STATS 303 Statistical Machine Learning,
Duke Kunshan University

Jan 2022 - May 2022 · Jiangsu, China

Research Assistant

Duke Kunshan University

Nov 2019 - May 2023 · Jiangsu, China

Mentored by Prof. Kai Zhang and Prof. Dongmian Zou

Awards & Honors

  • Graduation with Distinction (Top 5%) - Duke Kunshan University May 2023

  • Graduation with Latin Honors cum laude - Duke Kunshan University May 2023

  • Zu Chongzhi Math Signature Work Award - DKU Zu Chongzhi Center May 2023

  • Conference Travel Grant (ICLR 2023) - Duke Kunshan University May 2023

  • Conference Travel Grant (NeurIPS 2022) - Duke Kunshan University Dec 2022

  • Summer Research Scholar - Duke Kunshan University Jun 2020, Jun 2022

  • Dean's List - Duke Kunshan University Fall 2019, Fall 2020, Sring 2021,
    Fall 2021, Spring 2022


Last Updated: 7/25/2023, 7:24:59 AM